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37 Commits

Author SHA1 Message Date
Pratik Mankawde
87ed778efe refactor(telemetry): migrate integration test and docs from Jaeger to Tempo API
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-31 22:29:30 +01:00
Pratik Mankawde
d0ff82801c fix: use docker/telemetry/data/ for runtime data and add .gitignore
Move xrpld data paths from ./data/ to docker/telemetry/data/ so runtime
files stay within the docker telemetry directory. Add .gitignore to
exclude the data directory from version control.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-31 22:29:30 +01:00
Pratik Mankawde
f940290866 Phase 5: Documentation, deployment configs, integration test infrastructure
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-31 22:29:30 +01:00
Pratik Mankawde
014060370a fix(telemetry): move quorum/proposers attributes to consensus.accept span
Move validation_quorum and proposers_validated attributes from
consensus.accept.apply to consensus.accept span to match the design
spec. Both values are available in onAccept() scope.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-31 22:28:33 +01:00
Pratik Mankawde
8c222b9e05 feat(telemetry): add consensus validation span enrichment (Task 4.8)
Add validation ledger hash and full-validation flag to
consensus.validation.send spans, plus quorum and proposer count to
consensus.accept spans for trace-level agreement analysis.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-31 22:28:33 +01:00
Pratik Mankawde
95f0c8bf51 docs: add Task 4.8 consensus validation span enrichment for external dashboard parity
Adds ledger_hash, validation.full to validation send/receive spans,
and validation_quorum, proposers_validated to consensus.accept spans.
Foundation for Phase 7 ValidationTracker agreement computation.

Part of the external dashboard parity initiative across phases 2-11.
See docs/superpowers/specs/2026-03-30-external-dashboard-parity-design.md

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-31 22:28:33 +01:00
Pratik Mankawde
a127711b86 Phase 4: Consensus tracing - round lifecycle, proposals, validations, close time
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-31 22:28:33 +01:00
Pratik Mankawde
715c531512 feat(telemetry): add peer version attribute to tx.receive spans (Task 3.7)
Tag transaction receive spans with the relaying peer's rippled version
to enable version-mismatch correlation during network upgrades.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-31 22:28:27 +01:00
Pratik Mankawde
e6508a5bbc docs: add Task 3.8 TX span peer version attribute for external dashboard parity
Adds xrpl.peer.version attribute to tx.receive spans for version-mismatch
correlation during network upgrades.

Part of the external dashboard parity initiative across phases 2-11.
See docs/superpowers/specs/2026-03-30-external-dashboard-parity-design.md

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-31 22:28:27 +01:00
Pratik Mankawde
88d17e4c04 Phase 3: Transaction tracing - protobuf context propagation, PeerImp, NetworkOPs
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-31 22:28:27 +01:00
Pratik Mankawde
9ab8570153 docs(telemetry): replace Jaeger references with Tempo in Phase 2-5 task lists
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-31 22:28:22 +01:00
Pratik Mankawde
8f2507a945 feat(telemetry): add node health attributes to RPC spans (Task 2.8)
Add amendment_blocked and server_state span attributes to every
rpc.command.* span so operators can correlate RPC behavior with node state.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-31 22:28:22 +01:00
Pratik Mankawde
befffc573c docs: add Task 2.8 RPC span attribute enrichment for external dashboard parity
Adds node health context (amendment_blocked, server_state) to rpc.command.*
spans, inspired by the community xrpl-validator-dashboard.

Part of the external dashboard parity initiative across phases 2-11.
See docs/superpowers/specs/2026-03-30-external-dashboard-parity-design.md

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-31 22:28:22 +01:00
Pratik Mankawde
945faac770 Phase 2: RPC tracing - span macros, attributes, WebSocket, command spans
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-31 22:28:22 +01:00
Pratik Mankawde
c8b1686ce4 Phase 1b: Telemetry core infrastructure - CMake, Conan, SpanGuard, config
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-31 22:28:22 +01:00
Pratik Mankawde
ba92ccad14 Phase 1b: Telemetry core infrastructure - CMake, Conan, SpanGuard, config
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-31 22:28:22 +01:00
Pratik Mankawde
012e453997 Phase 1c: RPC integration - ServerHandler tracing, telemetry config wiring
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-31 22:28:17 +01:00
Pratik Mankawde
79b95c8cc6 Phase 1b: Telemetry core infrastructure - CMake, Conan, SpanGuard, config
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-31 22:28:17 +01:00
Pratik Mankawde
34d0f40ee7 Phase 1b: Telemetry core infrastructure - CMake, Conan, SpanGuard, config
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-31 22:28:17 +01:00
Pratik Mankawde
8421134420 refactor(telemetry): remove Jaeger service, exporter, and datasource
Tempo is now the sole trace backend. Remove Jaeger all-in-one service
from docker-compose, otlp/jaeger exporter from OTel Collector config,
and Jaeger Grafana datasource provisioning file.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-31 22:28:12 +01:00
Pratik Mankawde
a7470615be Phase 1b: Telemetry core infrastructure - CMake, Conan, SpanGuard, config
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-31 22:28:12 +01:00
Pratik Mankawde
33b09d29e1 docs(telemetry): replace Jaeger with Tempo in architecture diagram
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-31 22:22:34 +01:00
Pratik Mankawde
f135842071 docs: correct OTel overhead estimates against SDK benchmarks
Verified CPU, memory, and network overhead calculations against
official OTel C++ SDK benchmarks (969 CI runs) and source code
analysis. Key corrections:

- Span creation: 200-500ns → 500-1000ns (SDK BM_SpanCreation median
  ~1000ns; original estimate matched API no-op, not SDK path)
- Per-TX overhead: 2.4μs → 4.0μs (2.0% vs 1.2%; still within 1-3%)
- Active span memory: ~200 bytes → ~500-800 bytes (Span wrapper +
  SpanData + std::map attribute storage)
- Static memory: ~456KB → ~8.3MB (BatchSpanProcessor worker thread
  stack ~8MB was omitted)
- Total memory ceiling: ~2.3MB → ~10MB
- Memory success metric target: <5MB → <10MB
- AddEvent: 50-80ns → 100-200ns

Added Section 3.5.4 with links to all benchmark sources.
Updated presentation.md with matching corrections.
High-level conclusions unchanged (1-3% CPU, negligible consensus).

Also includes: review fixes, cross-document consistency improvements,
additional component tracing docs (PathFinding, TxQ, Validator, etc.),
context size corrections (32 → 25 bytes).

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-30 15:55:26 +01:00
Pratik Mankawde
a9bc525f22 moved presentation.md file
Signed-off-by: Pratik Mankawde <3397372+pratikmankawde@users.noreply.github.com>
2026-03-30 15:55:26 +01:00
Pratik Mankawde
5c9102bd9a Remove effort estimates from implementation phases document
Strip effort/risk columns from task tables and remove the §6.9 Effort
Summary section with its pie chart and resource requirements table.
Renumber §6.10 Quick Wins → §6.9.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-30 15:55:26 +01:00
Pratik Mankawde
c556f3471b Add Phase 4a implementation status to plan docs
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-30 15:55:26 +01:00
Pratik Mankawde
2fb6124412 Appendix: add 00-tracing-fundamentals.md and POC_taskList.md to document index
Split document index into Plan Documents and Task Lists sections.
These files were introduced in this branch but missing from the index.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-30 15:55:26 +01:00
Pratik Mankawde
e482b56f58 Phase 1a: OpenTelemetry plan documentation
Add comprehensive planning documentation for the OpenTelemetry
distributed tracing integration:

- Tracing fundamentals and concepts
- Architecture analysis of rippled's tracing surface area
- Design decisions and trade-offs
- Implementation strategy and code samples
- Configuration reference
- Implementation phases roadmap
- Observability backend comparison
- POC task list and presentation materials

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-30 15:55:26 +01:00
dependabot[bot]
de671863e2 ci: [DEPENDABOT] bump actions/deploy-pages from 4.0.5 to 5.0.0 (#6684)
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
2026-03-30 14:09:57 +00:00
dependabot[bot]
e0cabb9f8c ci: [DEPENDABOT] bump codecov/codecov-action from 5.5.3 to 6.0.0 (#6685)
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
2026-03-30 13:57:32 +00:00
Pratik Mankawde
3d9c545f59 fix: Guard Coro::resume() against completed coroutines (#6608)
Signed-off-by: Pratik Mankawde <3397372+pratikmankawde@users.noreply.github.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-27 18:52:18 +00:00
Vito Tumas
9b944ee8c2 refactor: Split LoanInvariant into LoanBrokerInvariant and LoanInvariant (#6674) 2026-03-27 18:35:42 +00:00
Ayaz Salikhov
509677abfd ci: Don't publish docs on release branches (#6673) 2026-03-26 14:11:37 +00:00
Jingchen
addc1e8e25 refactor: Make function naming in ServiceRegistry consistent (#6390)
Signed-off-by: JCW <a1q123456@users.noreply.github.com>
Co-authored-by: Ed Hennis <ed@ripple.com>
2026-03-26 14:11:16 +00:00
Valentin Balaschenko
faf69da4b0 chore: Shorten job names to stay within Linux 15-char thread limit (#6669) 2026-03-26 14:10:51 +00:00
Vito Tumas
76e3b4fb0f fix: Improve loan invariant message (#6668) 2026-03-26 12:40:26 +00:00
Ayaz Salikhov
e8bdbf975a ci: Upload artifacts only in public repositories (#6670) 2026-03-26 12:37:37 +00:00
653 changed files with 20943 additions and 6389 deletions

View File

@@ -1,6 +1,4 @@
---
# This entire group of checks was applied to all cpp files but not all header files.
# ---
Checks: "-*,
bugprone-argument-comment,
bugprone-assert-side-effect,
@@ -10,26 +8,26 @@ Checks: "-*,
bugprone-chained-comparison,
bugprone-compare-pointer-to-member-virtual-function,
bugprone-copy-constructor-init,
# bugprone-crtp-constructor-accessibility, # has issues
bugprone-crtp-constructor-accessibility,
bugprone-dangling-handle,
bugprone-dynamic-static-initializers,
# bugprone-empty-catch, # has issues
bugprone-empty-catch,
bugprone-fold-init-type,
# bugprone-forward-declaration-namespace, # has issues
# bugprone-inaccurate-erase,
# bugprone-inc-dec-in-conditions,
# bugprone-incorrect-enable-if,
# bugprone-incorrect-roundings,
# bugprone-infinite-loop,
# bugprone-integer-division,
bugprone-forward-declaration-namespace,
bugprone-inaccurate-erase,
bugprone-inc-dec-in-conditions,
bugprone-incorrect-enable-if,
bugprone-incorrect-roundings,
bugprone-infinite-loop,
bugprone-integer-division,
bugprone-lambda-function-name,
# bugprone-macro-parentheses, # has issues
bugprone-macro-parentheses,
bugprone-macro-repeated-side-effects,
bugprone-misplaced-operator-in-strlen-in-alloc,
bugprone-misplaced-pointer-arithmetic-in-alloc,
bugprone-misplaced-widening-cast,
bugprone-move-forwarding-reference,
# bugprone-multi-level-implicit-pointer-conversion, # has issues
bugprone-multi-level-implicit-pointer-conversion,
bugprone-multiple-new-in-one-expression,
bugprone-multiple-statement-macro,
bugprone-no-escape,
@@ -39,13 +37,13 @@ Checks: "-*,
bugprone-pointer-arithmetic-on-polymorphic-object,
bugprone-posix-return,
bugprone-redundant-branch-condition,
# bugprone-reserved-identifier, # has issues
# bugprone-return-const-ref-from-parameter, # has issues
bugprone-reserved-identifier,
bugprone-return-const-ref-from-parameter,
bugprone-shared-ptr-array-mismatch,
bugprone-signal-handler,
bugprone-signed-char-misuse,
bugprone-sizeof-container,
# bugprone-sizeof-expression, # has issues
bugprone-sizeof-expression,
bugprone-spuriously-wake-up-functions,
bugprone-standalone-empty,
bugprone-string-constructor,
@@ -62,7 +60,7 @@ Checks: "-*,
bugprone-suspicious-string-compare,
bugprone-suspicious-stringview-data-usage,
bugprone-swapped-arguments,
# bugprone-switch-missing-default-case, # has issues
bugprone-switch-missing-default-case,
bugprone-terminating-continue,
bugprone-throw-keyword-missing,
bugprone-too-small-loop-variable,
@@ -73,7 +71,7 @@ Checks: "-*,
bugprone-unhandled-self-assignment,
bugprone-unique-ptr-array-mismatch,
bugprone-unsafe-functions,
# bugprone-use-after-move, # has issues
bugprone-use-after-move,
bugprone-unused-raii,
bugprone-unused-return-value,
bugprone-unused-local-non-trivial-variable,
@@ -87,11 +85,9 @@ Checks: "-*,
cppcoreguidelines-use-default-member-init,
cppcoreguidelines-virtual-class-destructor,
hicpp-ignored-remove-result,
misc-const-correctness,
misc-definitions-in-headers,
misc-header-include-cycle,
misc-misplaced-const,
misc-redundant-expression,
misc-static-assert,
misc-throw-by-value-catch-by-reference,
misc-unused-alias-decls,
@@ -99,49 +95,46 @@ Checks: "-*,
modernize-deprecated-headers,
modernize-make-shared,
modernize-make-unique,
llvm-namespace-comment,
performance-faster-string-find,
performance-for-range-copy,
performance-implicit-conversion-in-loop,
performance-inefficient-vector-operation,
performance-move-const-arg,
performance-move-constructor-init,
performance-no-automatic-move,
performance-trivially-destructible,
# readability-avoid-nested-conditional-operator, # has issues
# readability-avoid-return-with-void-value, # has issues
# readability-braces-around-statements, # has issues
# readability-const-return-type, # has issues
# readability-container-contains, # has issues
# readability-container-size-empty, # has issues
# readability-convert-member-functions-to-static, # has issues
readability-avoid-nested-conditional-operator,
readability-avoid-return-with-void-value,
readability-braces-around-statements,
readability-const-return-type,
readability-container-contains,
readability-container-size-empty,
readability-convert-member-functions-to-static,
readability-duplicate-include,
# readability-else-after-return, # has issues
# readability-enum-initial-value, # has issues
# readability-implicit-bool-conversion, # has issues
# readability-make-member-function-const, # has issues
# readability-math-missing-parentheses, # has issues
readability-else-after-return,
readability-enum-initial-value,
readability-implicit-bool-conversion,
readability-make-member-function-const,
readability-math-missing-parentheses,
readability-misleading-indentation,
readability-non-const-parameter,
# readability-redundant-casting, # has issues
# readability-redundant-declaration, # has issues
# readability-redundant-inline-specifier, # has issues
# readability-redundant-member-init, # has issues
readability-redundant-casting,
readability-redundant-declaration,
readability-redundant-inline-specifier,
readability-redundant-member-init,
readability-redundant-string-init,
readability-reference-to-constructed-temporary,
# readability-simplify-boolean-expr, # has issues
# readability-static-definition-in-anonymous-namespace, # has issues
# readability-suspicious-call-argument, # has issues
readability-simplify-boolean-expr,
readability-static-definition-in-anonymous-namespace,
readability-suspicious-call-argument,
readability-use-std-min-max
"
# ---
# other checks that have issues that need to be resolved:
# checks that have some issues that need to be resolved:
#
# llvm-namespace-comment,
# misc-const-correctness,
# misc-include-cleaner,
# misc-redundant-expression,
#
# readability-inconsistent-declaration-parameter-name, # in this codebase this check will break a lot of arg names
# readability-static-accessed-through-instance, # this check is probably unnecessary. it makes the code less readable
# readability-identifier-naming, # https://github.com/XRPLF/rippled/pull/6571
# readability-identifier-naming,
#
# modernize-concat-nested-namespaces,
# modernize-pass-by-value,
@@ -155,6 +148,12 @@ Checks: "-*,
# modernize-use-starts-ends-with,
# modernize-use-std-numbers,
# modernize-use-using,
#
# performance-faster-string-find,
# performance-for-range-copy,
# performance-inefficient-vector-operation,
# performance-move-const-arg,
# performance-no-automatic-move,
# ---
#
CheckOptions:
@@ -196,6 +195,5 @@ CheckOptions:
bugprone-unused-return-value.CheckedReturnTypes: ::std::error_code;::std::error_condition;::std::errc
# misc-include-cleaner.IgnoreHeaders: '.*/(detail|impl)/.*;.*(expected|unexpected).*;.*ranges_lower_bound\.h;time.h;stdlib.h;__chrono/.*;fmt/chrono.h;boost/uuid/uuid_hash.hpp'
#
HeaderFilterRegex: '^.*/(test|xrpl|xrpld)/.*\.(h|hpp)$'
ExcludeHeaderFilterRegex: '^.*/protocol_autogen/.*\.(h|hpp)$'
# HeaderFilterRegex: '^.*/(src|tests)/.*\.(h|hpp)$'
WarningsAsErrors: "*"

View File

@@ -34,6 +34,8 @@ libxrpl.server > xrpl.server
libxrpl.shamap > xrpl.basics
libxrpl.shamap > xrpl.protocol
libxrpl.shamap > xrpl.shamap
libxrpl.telemetry > xrpl.basics
libxrpl.telemetry > xrpl.telemetry
libxrpl.tx > xrpl.basics
libxrpl.tx > xrpl.conditions
libxrpl.tx > xrpl.core
@@ -93,6 +95,7 @@ test.csf > xrpld.consensus
test.csf > xrpl.json
test.csf > xrpl.ledger
test.csf > xrpl.protocol
test.csf > xrpl.telemetry
test.json > test.jtx
test.json > xrpl.json
test.jtx > xrpl.basics
@@ -177,10 +180,12 @@ test.toplevel > xrpl.json
test.unit_test > xrpl.basics
test.unit_test > xrpl.protocol
tests.libxrpl > xrpl.basics
tests.libxrpl > xrpld.telemetry
tests.libxrpl > xrpl.json
tests.libxrpl > xrpl.net
tests.libxrpl > xrpl.protocol
tests.libxrpl > xrpl.protocol_autogen
tests.libxrpl > xrpl.telemetry
xrpl.conditions > xrpl.basics
xrpl.conditions > xrpl.protocol
xrpl.core > xrpl.basics
@@ -214,6 +219,7 @@ xrpl.server > xrpl.shamap
xrpl.shamap > xrpl.basics
xrpl.shamap > xrpl.nodestore
xrpl.shamap > xrpl.protocol
xrpl.telemetry > xrpl.basics
xrpl.tx > xrpl.basics
xrpl.tx > xrpl.core
xrpl.tx > xrpl.ledger
@@ -223,6 +229,7 @@ xrpld.app > xrpl.basics
xrpld.app > xrpl.core
xrpld.app > xrpld.consensus
xrpld.app > xrpld.core
xrpld.app > xrpld.telemetry
xrpld.app > xrpl.json
xrpld.app > xrpl.ledger
xrpld.app > xrpl.net
@@ -232,11 +239,14 @@ xrpld.app > xrpl.rdb
xrpld.app > xrpl.resource
xrpld.app > xrpl.server
xrpld.app > xrpl.shamap
xrpld.app > xrpl.telemetry
xrpld.app > xrpl.tx
xrpld.consensus > xrpl.basics
xrpld.consensus > xrpld.telemetry
xrpld.consensus > xrpl.json
xrpld.consensus > xrpl.ledger
xrpld.consensus > xrpl.protocol
xrpld.consensus > xrpl.telemetry
xrpld.core > xrpl.basics
xrpld.core > xrpl.core
xrpld.core > xrpl.json
@@ -247,6 +257,7 @@ xrpld.overlay > xrpl.basics
xrpld.overlay > xrpl.core
xrpld.overlay > xrpld.core
xrpld.overlay > xrpld.peerfinder
xrpld.overlay > xrpld.telemetry
xrpld.overlay > xrpl.json
xrpld.overlay > xrpl.protocol
xrpld.overlay > xrpl.rdb
@@ -264,6 +275,7 @@ xrpld.perflog > xrpl.json
xrpld.rpc > xrpl.basics
xrpld.rpc > xrpl.core
xrpld.rpc > xrpld.core
xrpld.rpc > xrpld.telemetry
xrpld.rpc > xrpl.json
xrpld.rpc > xrpl.ledger
xrpld.rpc > xrpl.net
@@ -274,3 +286,4 @@ xrpld.rpc > xrpl.resource
xrpld.rpc > xrpl.server
xrpld.rpc > xrpl.tx
xrpld.shamap > xrpl.shamap
xrpld.telemetry > xrpl.telemetry

View File

@@ -1,7 +1,7 @@
name: Check PR commits
on:
pull_request_target:
pull_request:
# The action needs to have write permissions to post comments on the PR.
permissions:

View File

@@ -36,7 +36,7 @@ env:
BUILD_DIR: build
# ubuntu-latest has only 2 CPUs for private repositories
# https://docs.github.com/en/actions/reference/runners/github-hosted-runners#standard-github-hosted-runners-for--private-repositories
NPROC_SUBTRACT: ${{ github.event.repository.visibility == 'public' && '2' || '1' }}
NPROC_SUBTRACT: ${{ github.event.repository.private && '1' || '2' }}
jobs:
build:
@@ -81,13 +81,13 @@ jobs:
cmake --build . --target docs --parallel ${BUILD_NPROC}
- name: Create documentation artifact
if: ${{ (github.repository_owner == 'XRPLF' || github.event.repository.visibility == 'public') && github.event_name == 'push' }}
if: ${{ github.event_name == 'push' }}
uses: actions/upload-pages-artifact@7b1f4a764d45c48632c6b24a0339c27f5614fb0b # v4.0.0
with:
path: ${{ env.BUILD_DIR }}/docs/html
deploy:
if: ${{ (github.repository_owner == 'XRPLF' || github.event.repository.visibility == 'public') && github.event_name == 'push' }}
if: ${{ github.event_name == 'push' }}
needs: build
runs-on: ubuntu-latest
permissions:

View File

@@ -101,7 +101,7 @@ jobs:
steps:
- name: Cleanup workspace (macOS and Windows)
if: ${{ runner.os == 'macOS' || runner.os == 'Windows' }}
uses: XRPLF/actions/cleanup-workspace@c7d9ce5ebb03c752a354889ecd870cadfc2b1cd4
uses: XRPLF/actions/cleanup-workspace@cf0433aa74563aead044a1e395610c96d65a37cf
- name: Checkout repository
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
@@ -199,7 +199,7 @@ jobs:
fi
- name: Upload the binary (Linux)
if: ${{ (github.repository_owner == 'XRPLF' || github.event.repository.visibility == 'public') && runner.os == 'Linux' }}
if: ${{ github.event.repository.visibility == 'public' && runner.os == 'Linux' }}
uses: actions/upload-artifact@bbbca2ddaa5d8feaa63e36b76fdaad77386f024f # v7.0.0
with:
name: xrpld-${{ inputs.config_name }}
@@ -263,18 +263,6 @@ jobs:
[ "$COVERAGE_ENABLED" = "true" ] && BUILD_NPROC=$(( BUILD_NPROC - 2 ))
./xrpld --unittest --unittest-jobs "${BUILD_NPROC}" 2>&1 | tee unittest.log
- name: Show test failure summary
if: ${{ failure() && !inputs.build_only }}
working-directory: ${{ runner.os == 'Windows' && format('{0}/{1}', env.BUILD_DIR, inputs.build_type) || env.BUILD_DIR }}
run: |
if [ ! -f unittest.log ]; then
echo "unittest.log not found; embedded tests may not have run."
exit 0
fi
if ! grep -E "failed" unittest.log; then
echo "Log present but no failure lines found in unittest.log."
fi
- name: Debug failure (Linux)
if: ${{ failure() && runner.os == 'Linux' && !inputs.build_only }}
run: |

View File

@@ -78,12 +78,12 @@ jobs:
id: run_clang_tidy
continue-on-error: true
env:
TARGETS: ${{ inputs.files != '' && inputs.files || 'src tests' }}
FILES: ${{ inputs.files }}
run: |
run-clang-tidy -j ${{ steps.nproc.outputs.nproc }} -p "${BUILD_DIR}" -quiet -allow-no-checks ${TARGETS} 2>&1 | tee clang-tidy-output.txt
run-clang-tidy -j ${{ steps.nproc.outputs.nproc }} -p "$BUILD_DIR" $FILES 2>&1 | tee clang-tidy-output.txt
- name: Upload clang-tidy output
if: ${{ (github.repository_owner == 'XRPLF' || github.event.repository.visibility == 'public') && steps.run_clang_tidy.outcome != 'success' }}
if: ${{ github.event.repository.visibility == 'public' && steps.run_clang_tidy.outcome != 'success' }}
uses: actions/upload-artifact@bbbca2ddaa5d8feaa63e36b76fdaad77386f024f # v7.0.0
with:
name: clang-tidy-results

View File

@@ -64,7 +64,7 @@ jobs:
steps:
- name: Cleanup workspace (macOS and Windows)
if: ${{ runner.os == 'macOS' || runner.os == 'Windows' }}
uses: XRPLF/actions/cleanup-workspace@c7d9ce5ebb03c752a354889ecd870cadfc2b1cd4
uses: XRPLF/actions/cleanup-workspace@cf0433aa74563aead044a1e395610c96d65a37cf
- name: Checkout repository
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2

View File

@@ -141,7 +141,7 @@ Alternatively, you can pull our recipes from the repository and export them loca
```bash
# Define which recipes to export.
recipes=('abseil' 'ed25519' 'grpc' 'm4' 'mpt-crypto' 'openssl' 'secp256k1' 'snappy' 'soci' 'wasm-xrplf' 'wasmi')
recipes=('abseil' 'ed25519' 'grpc' 'm4' 'mpt-crypto' 'nudb' 'openssl' 'secp256k1' 'snappy' 'soci' 'wasm-xrplf' 'wasmi')
# Selectively check out the recipes from our CCI fork.
cd external

View File

@@ -117,6 +117,18 @@ if(rocksdb)
target_link_libraries(xrpl_libs INTERFACE RocksDB::rocksdb)
endif()
# OpenTelemetry distributed tracing (optional).
# When ON, links against opentelemetry-cpp and defines XRPL_ENABLE_TELEMETRY
# so that tracing macros in TracingInstrumentation.h are compiled in.
# When OFF (default), all tracing code compiles to no-ops with zero overhead.
# Enable via: conan install -o telemetry=True, or cmake -Dtelemetry=ON.
option(telemetry "Enable OpenTelemetry tracing" OFF)
if(telemetry)
find_package(opentelemetry-cpp CONFIG REQUIRED)
add_compile_definitions(XRPL_ENABLE_TELEMETRY)
message(STATUS "OpenTelemetry tracing enabled")
endif()
# Work around changes to Conan recipe for now.
if(TARGET nudb::core)
set(nudb nudb::core)

View File

@@ -270,14 +270,14 @@ Before running clang-tidy, you must build the project to generate required files
Then run clang-tidy on your local changes:
```
run-clang-tidy -p build -allow-no-checks src tests
run-clang-tidy -p build src include tests
```
This will check all source files in the `src`, `include` and `tests` directories using the compile commands from your `build` directory.
If you wish to automatically fix whatever clang-tidy finds _and_ is capable of fixing, add `-fix` to the above command:
```
run-clang-tidy -p build -quiet -fix -allow-no-checks src tests
run-clang-tidy -p build -fix src include tests
```
## Contracts and instrumentation

View File

@@ -0,0 +1,567 @@
# Distributed Tracing Fundamentals
> **Parent Document**: [OpenTelemetryPlan.md](./OpenTelemetryPlan.md)
> **Next**: [Architecture Analysis](./01-architecture-analysis.md)
---
## What is Distributed Tracing?
Distributed tracing is a method for tracking data objects as they flow through distributed systems. In a network like XRP Ledger, a single transaction touches multiple independent nodes—each with no shared memory or logging. Distributed tracing connects these dots.
**Without tracing:** You see isolated logs on each node with no way to correlate them.
**With tracing:** You see the complete journey of a transaction or an event across all nodes it touched.
---
## Actors and Actions at a Glance
### Actors
| Who (Plain English) | Technical Term |
| ---------------------------------------------- | --------------- |
| A single unit of work being tracked | Span |
| The complete journey of a request | Trace |
| Data that links spans across services | Trace Context |
| Code that creates spans and propagates context | Instrumentation |
| Service that receives and processes traces | Collector |
| Storage and visualization system | Backend (Tempo) |
| Decision logic for which traces to keep | Sampler |
### Actions
| What Happens (Plain English) | Technical Term |
| --------------------------------------- | ----------------------- |
| Start tracking a new operation | Create a Span |
| Connect a child operation to its parent | Set `parent_span_id` |
| Group all related operations together | Share a `trace_id` |
| Pass tracking data between services | Context Propagation |
| Decide whether to record a trace | Sampling (Head or Tail) |
| Send completed traces to storage | Export (OTLP) |
---
## Core Concepts
### 1. Trace
A **trace** represents the entire journey of a request through the system. It has a unique `trace_id` that stays constant across all nodes.
```
Trace ID: abc123
├── Node A: received transaction
├── Node B: relayed transaction
├── Node C: included in consensus
└── Node D: applied to ledger
```
### 2. Span
A **span** represents a single unit of work within a trace. Each span has:
| Attribute | Description | Example |
| ---------------- | -------------------------------- | -------------------------- |
| `trace_id` | Identifies the trace | `event123` |
| `span_id` | Unique identifier | `span456` |
| `parent_span_id` | Parent span (if any) | `p_span123` |
| `name` | Operation name | `rpc.submit` |
| `start_time` | When work began (local time) | `2024-01-15T10:30:00Z` |
| `end_time` | When work completed (local time) | `2024-01-15T10:30:00.050Z` |
| `attributes` | Key-value metadata | `tx.hash=ABC...` |
| `status` | OK, ERROR MSG | `OK` |
### 3. Trace Context
**Trace context** is the data that propagates between services to link spans together. It contains:
- `trace_id` - The trace this span belongs to
- `span_id` - The current span (becomes parent for child spans)
- `trace_flags` - Sampling decisions
---
## How Spans Form a Trace
Spans have parent-child relationships forming a tree structure:
```mermaid
flowchart TB
subgraph trace["Trace: abc123"]
A["tx.submit<br/>span_id: 001<br/>50ms"] --> B["tx.validate<br/>span_id: 002<br/>5ms"]
A --> C["tx.relay<br/>span_id: 003<br/>10ms"]
A --> D["tx.apply<br/>span_id: 004<br/>30ms"]
D --> E["ledger.update<br/>span_id: 005<br/>20ms"]
end
style A fill:#0d47a1,stroke:#082f6a,color:#ffffff
style B fill:#1b5e20,stroke:#0d3d14,color:#ffffff
style C fill:#1b5e20,stroke:#0d3d14,color:#ffffff
style D fill:#1b5e20,stroke:#0d3d14,color:#ffffff
style E fill:#bf360c,stroke:#8c2809,color:#ffffff
```
**Reading the diagram:**
- **tx.submit (blue, root)**: The top-level span representing the entire transaction submission; all other spans are its descendants.
- **tx.validate, tx.relay, tx.apply (green)**: Direct children of tx.submit, representing the three main stages -- validation, relay to peers, and application to the ledger.
- **ledger.update (red)**: A grandchild span nested under tx.apply, representing the actual ledger state mutation triggered by applying the transaction.
- **Arrows (parent to child)**: Each arrow indicates a parent-child span relationship where the parent's completion depends on the child finishing.
The same trace visualized as a **timeline (Gantt chart)**:
```
Time → 0ms 10ms 20ms 30ms 40ms 50ms
├───────────────────────────────────────────┤
tx.submit│▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓│
├─────┤
tx.valid │▓▓▓▓▓│
│ ├──────────┤
tx.relay │ │▓▓▓▓▓▓▓▓▓▓│
│ ├────────────────────────────┤
tx.apply │ │▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓│
│ ├──────────────────┤
ledger │ │▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓│
```
---
## Span Relationships
Spans don't always form simple parent-child trees. Distributed tracing defines several relationship types to capture different causal patterns:
### 1. Parent-Child (ChildOf)
The default relationship. The parent span **depends on** or **contains** the child span. The child runs within the scope of the parent.
```
tx.submit (parent)
├── tx.validate (child) ← parent waits for this
├── tx.relay (child) ← parent waits for this
└── tx.apply (child) ← parent waits for this
```
**When to use:** Synchronous calls, nested operations, any case where the parent's completion depends on the child.
### 2. Follows-From
A causal relationship where the first span **triggers** the second, but does **not wait** for it. The originator fires and moves on.
```
Time →
tx.receive [=======]
↓ triggers (follows-from)
tx.relay [===========] ← runs independently
```
**When to use:** Asynchronous jobs, queued work, fire-and-forget patterns. For example, a node receives a transaction and queues it for relay — the relay span _follows from_ the receive span but the receiver doesn't wait for relaying to complete.
> **OpenTracing** defined `FollowsFrom` as a first-class reference type alongside `ChildOf`.
> **OpenTelemetry** represents this using **Span Links** with descriptive attributes instead (see below).
### 3. Span Links (Cross-Trace and Non-Hierarchical)
Links connect spans that are **causally related but not in a parent-child hierarchy**. Unlike parent-child, links can cross trace boundaries.
```
Trace A Trace B
────── ──────
batch.schedule batch.execute
├─ item.enqueue (span X) ┌──► process.item
├─ item.enqueue (span Y) ───┤ (links to X, Y, Z)
├─ item.enqueue (span Z) └──►
```
**Use cases:**
| Pattern | Description |
| -------------------- | --------------------------------------------------------------------------- |
| **Batch processing** | A batch span links back to all individual spans that contributed to it |
| **Fan-in** | An aggregation span links to the multiple producer spans it merges |
| **Fan-out** | Multiple downstream spans link back to the single span that triggered them |
| **Async handoff** | A deferred job links back to the request that queued it (follows-from) |
| **Cross-trace** | Correlating spans across independent traces (e.g., retries, related events) |
**Link structure:** Each link carries the target span's context plus optional attributes:
```
Link {
trace_id: <target trace>
span_id: <target span>
attributes: { "link.description": "triggered by batch scheduler" }
}
```
### Relationship Summary
```mermaid
flowchart LR
subgraph parent_child["Parent-Child"]
direction TB
P["Parent"] --> C["Child"]
end
subgraph follows_from["Follows-From"]
direction TB
A["Span A"] -.->|triggers| B["Span B"]
end
subgraph links["Span Links"]
direction TB
X["Span X\n(Trace 1)"] -.-|link| Y["Span Y\n(Trace 2)"]
end
parent_child ~~~ follows_from ~~~ links
style P fill:#0d47a1,stroke:#082f6a,color:#ffffff
style C fill:#1b5e20,stroke:#0d3d14,color:#ffffff
style A fill:#0d47a1,stroke:#082f6a,color:#ffffff
style B fill:#bf360c,stroke:#8c2809,color:#ffffff
style X fill:#4a148c,stroke:#38006b,color:#ffffff
style Y fill:#4a148c,stroke:#38006b,color:#ffffff
```
| Relationship | Same Trace? | Dependency? | OTel Mechanism |
| ---------------- | ----------- | -------------------------- | ----------------- |
| **Parent-Child** | Yes | Parent depends on child | `parent_span_id` |
| **Follows-From** | Usually | Causal but no dependency | Link + attributes |
| **Span Link** | Either | Correlation, no dependency | Link + attributes |
---
## Trace ID Generation
A `trace_id` is a 128-bit (16-byte) identifier that groups all spans belonging to one logical operation. How it's generated determines how easily you can find and correlate traces later.
### General Approaches
#### 1. Random (W3C Default)
Generate a random 128-bit ID when a trace starts. Standard approach for most services.
```
trace_id = random_128_bits()
```
| Pros | Cons |
| --------------------------- | --------------------------------------------- |
| Simple, standard | No natural correlation to domain events |
| Guaranteed unique per trace | If propagation is lost, trace is broken |
| Works with all OTel tooling | "Find trace for TX abc" requires index lookup |
#### 2. Deterministic (Derived from Domain Data)
Compute the trace_id from a hash of a natural identifier. Every node independently derives the **same** trace_id for the same event.
```
trace_id = SHA-256(domain_identifier)[0:16] // truncate to 128 bits
```
| Pros | Cons |
| --------------------------------------------------- | ---------------------------------------------------------- |
| Propagation-resilient — same ID computed everywhere | Same event processed twice (retry) shares trace_id |
| Natural search — domain ID maps directly to trace | Non-standard (tooling assumes random) |
| No coordination needed between nodes | 256→128 bit truncation (collision risk negligible at ~2⁶⁴) |
#### 3. Hybrid (Deterministic Prefix + Random Suffix)
First 8 bytes derived from domain data, last 8 bytes random.
```
trace_id = SHA-256(domain_identifier)[0:8] || random_64_bits()
```
| Pros | Cons |
| ------------------------------------------- | ---------------------------------------- |
| Prefix search: "find all traces for TX abc" | Must propagate to maintain full trace_id |
| Unique per processing instance | More complex generation logic |
| Retries get distinct trace_ids | Partial correlation only (prefix match) |
### XRPL Workflow Analysis
XRPL has a unique advantage: its core workflows produce **globally unique 256-bit hashes** that are known on every node. This makes deterministic trace_id generation practical in ways most systems can't achieve.
#### Natural Identifiers by Workflow
| Workflow | Natural Identifier | Size | Known at Start? | Same on All Nodes? |
| ------------------- | --------------------------------- | ---------- | ----------------------------- | -------------------------------- |
| **Transaction** | Transaction hash (`tid_`) | 256-bit | Yes — computed before signing | Yes — hash of canonical tx data |
| **Consensus round** | Previous ledger hash + ledger seq | 256+32 bit | Yes — known when round opens | Yes — all validators agree |
| **Validation** | Ledger hash being validated | 256-bit | Yes — from consensus result | Yes — same closed ledger |
| **Ledger catch-up** | Target ledger hash | 256-bit | Yes — we know what to fetch | Yes — identifies ledger globally |
#### Where These Identifiers Live in Code
```
Transaction: STTx::getTransactionID() → uint256 tid_
TMTransaction::rawTransaction → recompute hash from bytes
Consensus: ConsensusProposal::prevLedger_ → uint256 (previous ledger hash)
ConsensusProposal::position_ → uint256 (TxSet hash)
LedgerHeader::seq → uint32_t (ledger sequence)
Validation: STValidation::getLedgerHash() → uint256
STValidation::getNodeID() → NodeID (160-bit)
Ledger fetch: InboundLedger constructor → uint256 hash, uint32_t seq
TMGetLedger::ledgerHash → bytes (uint256)
```
### Recommended Strategy: Workflow-Scoped Deterministic
Each workflow type derives its trace_id from its natural domain identifier:
```
Transaction trace: trace_id = SHA-256("tx" || tx_hash)[0:16]
Consensus trace: trace_id = SHA-256("cons" || prev_ledger_hash || ledger_seq)[0:16]
Ledger catch-up: trace_id = SHA-256("fetch" || target_ledger_hash)[0:16]
```
The string prefix (`"tx"`, `"cons"`, `"fetch"`) prevents collisions between workflows that might share underlying hashes.
**Why this works for XRPL:**
1. **Propagation-resilient** — Even if a P2P message drops trace context, every node independently computes the same trace_id from the same tx_hash or ledger_hash. Spans still correlate.
2. **Zero-cost search** — "Show me the trace for transaction ABC" becomes a direct lookup: compute `SHA-256("tx" || ABC)[0:16]` and query. No secondary index needed.
3. **Cross-workflow linking via Span Links** — A consensus trace links to individual transaction traces. A validation span links to the consensus trace. This connects the full picture without forcing everything into one giant trace.
### Cross-Workflow Correlation
Each workflow gets its own trace. Span Links tie them together:
```mermaid
flowchart TB
subgraph tx_trace["Transaction Trace"]
direction LR
Tn["trace_id = f(tx_hash)"]:::note --> T1["tx.receive"] --> T2["tx.validate"] --> T3["tx.relay"]
end
subgraph cons_trace["Consensus Trace"]
direction LR
Cn["trace_id = f(prev_ledger, seq)"]:::note --> C1["cons.open"] --> C2["cons.propose"] --> C3["cons.accept"]
end
subgraph val_trace["Validation"]
direction LR
Vn["spans within consensus trace"]:::note --> V1["val.create"] --> V2["val.broadcast"]
end
subgraph fetch_trace["Catch-Up Trace"]
direction LR
Fn["trace_id = f(ledger_hash)"]:::note --> F1["fetch.request"] --> F2["fetch.receive"] --> F3["fetch.apply"]
end
C1 -.-|"span link\n(tx traces)"| T3
C3 --> V1
F1 -.-|"span link\n(target ledger)"| C3
classDef note fill:none,stroke:#888,stroke-dasharray:5 5,color:#333,font-style:italic
style T1 fill:#0d47a1,stroke:#082f6a,color:#ffffff
style T2 fill:#0d47a1,stroke:#082f6a,color:#ffffff
style T3 fill:#0d47a1,stroke:#082f6a,color:#ffffff
style C1 fill:#1b5e20,stroke:#0d3d14,color:#ffffff
style C2 fill:#1b5e20,stroke:#0d3d14,color:#ffffff
style C3 fill:#1b5e20,stroke:#0d3d14,color:#ffffff
style V1 fill:#bf360c,stroke:#8c2809,color:#ffffff
style V2 fill:#bf360c,stroke:#8c2809,color:#ffffff
style F1 fill:#4a148c,stroke:#38006b,color:#ffffff
style F2 fill:#4a148c,stroke:#38006b,color:#ffffff
style F3 fill:#4a148c,stroke:#38006b,color:#ffffff
```
**Reading the diagram:**
- **Transaction Trace (blue)**: An independent trace whose `trace_id` is deterministically derived from the transaction hash. Contains receive, validate, and relay spans.
- **Consensus Trace (green)**: An independent trace whose `trace_id` is derived from the previous ledger hash and sequence number. Covers the open, propose, and accept phases.
- **Validation (red)**: Validation spans live within the consensus trace (not a separate trace). They are created after the accept phase completes.
- **Catch-Up Trace (purple)**: An independent trace for ledger acquisition, derived from the target ledger hash. Used when a node is behind and fetching missing ledgers.
- **Dotted arrows (span links)**: Cross-trace correlations. Consensus links to transaction traces it included; catch-up links to the consensus trace that produced the target ledger.
- **Solid arrow (C3 to V1)**: A parent-child relationship -- validation spans are direct children of the consensus accept span within the same trace.
**How a query flows:**
```
"Why was TX abc slow?"
1. Compute trace_id = SHA-256("tx" || abc)[0:16]
2. Find transaction trace → see it was included in consensus round N
3. Follow span link → consensus trace for round N
4. See which phase was slow (propose? accept?)
5. If a node was catching up, follow link → catch-up trace
```
### Trade-offs to Consider
| Concern | Mitigation |
| ----------------------------- | ----------------------------------------------------------------------------------------------------------------------------- |
| **Retries get same trace_id** | Add `attempt` attribute to root span; spans have unique span_ids and timestamps |
| **256→128 bit truncation** | Birthday-bound collision at ~2⁶⁴ operations — negligible for XRPL's throughput |
| **Non-standard generation** | OTel spec allows any 16-byte non-zero value; tooling works on the hex string |
| **Hash computation cost** | SHA-256 is ~0.3μs per call; XRPL already computes these hashes for other purposes |
| **Late-binding identifiers** | Ledger hash isn't known until after consensus — validation spans use ledger_seq as fallback, then link to the consensus trace |
---
## Distributed Traces Across Nodes
In distributed systems like rippled, traces span **multiple independent nodes**. The trace context must be propagated in network messages:
```mermaid
sequenceDiagram
participant Client
participant NodeA as Node A
participant NodeB as Node B
participant NodeC as Node C
Client->>NodeA: Submit TX<br/>(no trace context)
Note over NodeA: Creates new trace<br/>trace_id: abc123<br/>span: tx.receive
NodeA->>NodeB: Relay TX<br/>(trace_id: abc123, parent: 001)
Note over NodeB: Creates child span<br/>span: tx.relay<br/>parent_span_id: 001
NodeA->>NodeC: Relay TX<br/>(trace_id: abc123, parent: 001)
Note over NodeC: Creates child span<br/>span: tx.relay<br/>parent_span_id: 001
Note over NodeA,NodeC: All spans share trace_id: abc123<br/>enabling correlation across nodes
```
**Reading the diagram:**
- **Client**: The external entity that submits a transaction. It does not carry trace context -- the trace originates at the first node.
- **Node A**: The entry point that creates a new trace (trace_id: abc123) and the root span `tx.receive`. It relays the transaction to peers with trace context attached.
- **Node B and Node C**: Peer nodes that receive the relayed transaction along with the propagated trace context. Each creates a child span under Node A's span, preserving the same `trace_id`.
- **Arrows with trace context**: The relay messages carry `trace_id` and `parent_span_id`, allowing each downstream node to link its spans back to the originating span on Node A.
---
## Context Propagation
For traces to work across nodes, **trace context must be propagated** in messages.
### What's in the Context (~26 bytes)
| Field | Size | Description |
| ------------- | -------- | ------------------------------------------------------- |
| `trace_id` | 16 bytes | Identifies the entire trace (constant across all nodes) |
| `span_id` | 8 bytes | The sender's current span (becomes parent on receiver) |
| `trace_flags` | 1 byte | Sampling decision (bit 0 = sampled; bits 1-7 reserved) |
| `trace_state` | variable | Optional vendor-specific data (typically omitted) |
### How span_id Changes at Each Hop
Only **one** `span_id` travels in the context - the sender's current span. Each node:
1. Extracts the received `span_id` and uses it as the `parent_span_id`
2. Creates a **new** `span_id` for its own span
3. Sends its own `span_id` as the parent when forwarding
```
Node A Node B Node C
────── ────── ──────
Span AAA Span BBB Span CCC
│ │ │
▼ ▼ ▼
Context out: Context out: Context out:
├─ trace_id: abc123 ├─ trace_id: abc123 ├─ trace_id: abc123
├─ span_id: AAA ──────────► ├─ span_id: BBB ──────────► ├─ span_id: CCC ──────►
└─ flags: 01 └─ flags: 01 └─ flags: 01
│ │
parent = AAA parent = BBB
```
The `trace_id` stays constant, but `span_id` **changes at every hop** to maintain the parent-child chain.
### Propagation Formats
There are two patterns:
### HTTP/RPC Headers (W3C Trace Context)
```
traceparent: 00-4bf92f3577b34da6a3ce929d0e0e4736-00f067aa0ba902b7-01
│ │ │ │
│ │ │ └── Flags (sampled)
│ │ └── Parent span ID (16 hex)
│ └── Trace ID (32 hex)
└── Version
```
### Protocol Buffers (rippled P2P messages)
```protobuf
message TMTransaction {
bytes rawTransaction = 1;
// ... existing fields ...
// Trace context extension
bytes trace_parent = 100; // W3C traceparent
bytes trace_state = 101; // W3C tracestate
}
```
---
## Sampling
Not every trace needs to be recorded. **Sampling** reduces overhead:
### Head Sampling (at trace start)
```
Request arrives → Random 10% chance → Record or skip entire trace
```
- ✅ Low overhead
- ❌ May miss interesting traces
### Tail Sampling (after trace completes)
```
Trace completes → Collector evaluates:
- Error? → KEEP
- Slow? → KEEP
- Normal? → Sample 10%
```
- ✅ Never loses important traces
- ❌ Higher memory usage at collector
---
## Key Benefits for rippled
| Challenge | How Tracing Helps |
| ---------------------------------- | ---------------------------------------- |
| "Where is my transaction?" | Follow trace across all nodes it touched |
| "Why was consensus slow?" | See timing breakdown of each phase |
| "Which node is the bottleneck?" | Compare span durations across nodes |
| "What happened during the outage?" | Correlate errors across the network |
---
## Glossary
| Term | Definition |
| -------------------- | ------------------------------------------------------------------- |
| **Trace** | Complete journey of a request, identified by `trace_id` |
| **Span** | Single operation within a trace |
| **Parent-Child** | Span relationship where the parent depends on the child |
| **Follows-From** | Causal relationship where originator doesn't wait for the result |
| **Span Link** | Non-hierarchical connection between spans, possibly across traces |
| **Deterministic ID** | Trace ID derived from domain data (e.g., tx_hash) instead of random |
| **Context** | Data propagated between services (`trace_id`, `span_id`, flags) |
| **Instrumentation** | Code that creates spans and propagates context |
| **Collector** | Service that receives, processes, and exports traces |
| **Backend** | Storage/visualization system (Tempo) |
| **Head Sampling** | Sampling decision at trace start |
| **Tail Sampling** | Sampling decision after trace completes |
---
_Next: [Architecture Analysis](./01-architecture-analysis.md)_ | _Back to: [Overview](./OpenTelemetryPlan.md)_

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# Architecture Analysis
> **Parent Document**: [OpenTelemetryPlan.md](./OpenTelemetryPlan.md)
> **Related**: [Design Decisions](./02-design-decisions.md) | [Implementation Strategy](./03-implementation-strategy.md)
---
## 1.1 Current rippled Architecture Overview
> **WS** = WebSocket | **UNL** = Unique Node List | **TxQ** = Transaction Queue | **StatsD** = Statistics Daemon
The rippled node software consists of several interconnected components that need instrumentation for distributed tracing:
```mermaid
flowchart TB
subgraph rippled["rippled Node"]
subgraph services["Core Services"]
RPC["RPC Server<br/>(HTTP/WS/gRPC)"]
Overlay["Overlay<br/>(P2P Network)"]
Consensus["Consensus<br/>(RCLConsensus)"]
ValidatorList["ValidatorList<br/>(UNL Mgmt)"]
end
JobQueue["JobQueue<br/>(Thread Pool)"]
subgraph processing["Processing Layer"]
NetworkOPs["NetworkOPs<br/>(Tx Processing)"]
LedgerMaster["LedgerMaster<br/>(Ledger Mgmt)"]
NodeStore["NodeStore<br/>(Database)"]
InboundLedgers["InboundLedgers<br/>(Ledger Sync)"]
end
subgraph appservices["Application Services"]
PathFind["PathFinding<br/>(Payment Paths)"]
TxQ["TxQ<br/>(Fee Escalation)"]
LoadMgr["LoadManager<br/>(Fee/Load)"]
end
subgraph observability["Existing Observability"]
PerfLog["PerfLog<br/>(JSON)"]
Insight["Insight<br/>(StatsD)"]
Logging["Logging<br/>(Journal)"]
end
services --> JobQueue
JobQueue --> processing
JobQueue --> appservices
end
style rippled fill:#424242,stroke:#212121,color:#ffffff
style services fill:#1565c0,stroke:#0d47a1,color:#ffffff
style processing fill:#2e7d32,stroke:#1b5e20,color:#ffffff
style appservices fill:#6a1b9a,stroke:#4a148c,color:#ffffff
style observability fill:#e65100,stroke:#bf360c,color:#ffffff
```
**Reading the diagram:**
- **Core Services (blue)**: The entry points into rippled -- RPC Server handles client requests, Overlay manages peer-to-peer networking, Consensus drives agreement, and ValidatorList manages trusted validators.
- **JobQueue (center)**: The asynchronous thread pool that decouples Core Services from the Processing and Application layers. All work flows through it.
- **Processing Layer (green)**: Core business logic -- NetworkOPs processes transactions, LedgerMaster manages ledger state, NodeStore handles persistence, and InboundLedgers synchronizes missing data.
- **Application Services (purple)**: Higher-level features -- PathFinding computes payment routes, TxQ manages fee-based queuing, and LoadManager tracks server load.
- **Existing Observability (orange)**: The current monitoring stack (PerfLog, Insight, Journal logging) that OpenTelemetry will complement, not replace.
- **Arrows (Services to JobQueue to layers)**: Work originates at Core Services, is enqueued onto the JobQueue, and dispatched to Processing or Application layers for execution.
---
## 1.1.1 Actors and Actions
### Actors
| Who (Plain English) | Technical Term |
| ----------------------------------------- | -------------------------- |
| Network node running XRPL software | rippled node |
| External client submitting requests | RPC Client |
| Network neighbor sharing data | Peer (PeerImp) |
| Request handler for client queries | RPC Server (ServerHandler) |
| Command executor for specific RPC methods | RPCHandler |
| Agreement process between nodes | Consensus (RCLConsensus) |
| Transaction processing coordinator | NetworkOPs |
| Background task scheduler | JobQueue |
| Ledger state manager | LedgerMaster |
| Payment route calculator | PathFinding (Pathfinder) |
| Transaction waiting room | TxQ (Transaction Queue) |
| Fee adjustment system | LoadManager |
| Trusted validator list manager | ValidatorList |
| Protocol upgrade tracker | AmendmentTable |
| Ledger state hash tree | SHAMap |
| Persistent key-value storage | NodeStore |
### Actions
| What Happens (Plain English) | Technical Term |
| ---------------------------------------------- | ---------------------- |
| Client sends a request to a node | `rpc.request` |
| Node executes a specific RPC command | `rpc.command.*` |
| Node receives a transaction from a peer | `tx.receive` |
| Node checks if a transaction is valid | `tx.validate` |
| Node forwards a transaction to neighbors | `tx.relay` |
| Nodes agree on which transactions to include | `consensus.round` |
| Consensus progresses through phases | `consensus.phase.*` |
| Node builds a new confirmed ledger | `ledger.build` |
| Node fetches missing ledger data from peers | `ledger.acquire` |
| Node computes payment routes | `pathfind.compute` |
| Node queues a transaction for later processing | `txq.enqueue` |
| Node increases fees due to high load | `fee.escalate` |
| Node fetches the latest trusted validator list | `validator.list.fetch` |
| Node votes on a protocol amendment | `amendment.vote` |
| Node synchronizes state tree data | `shamap.sync` |
---
## 1.2 Key Components for Instrumentation
> **TxQ** = Transaction Queue | **UNL** = Unique Node List
| Component | Location | Purpose | Trace Value |
| ------------------ | ------------------------------------------ | ------------------------ | -------------------------------- |
| **Overlay** | `src/xrpld/overlay/` | P2P communication | Message propagation timing |
| **PeerImp** | `src/xrpld/overlay/detail/PeerImp.cpp` | Individual peer handling | Per-peer latency |
| **RCLConsensus** | `src/xrpld/app/consensus/RCLConsensus.cpp` | Consensus algorithm | Round timing, phase analysis |
| **NetworkOPs** | `src/xrpld/app/misc/NetworkOPs.cpp` | Transaction processing | Tx lifecycle tracking |
| **ServerHandler** | `src/xrpld/rpc/detail/ServerHandler.cpp` | RPC entry point | Request latency |
| **RPCHandler** | `src/xrpld/rpc/detail/RPCHandler.cpp` | Command execution | Per-command timing |
| **JobQueue** | `src/xrpl/core/JobQueue.h` | Async task execution | Queue wait times |
| **PathFinding** | `src/xrpld/app/paths/` | Payment path computation | Path latency, cache hits |
| **TxQ** | `src/xrpld/app/misc/TxQ.cpp` | Transaction queue/fees | Queue depth, eviction rates |
| **LoadManager** | `src/xrpld/app/main/LoadManager.cpp` | Fee escalation/load | Fee levels, load factors |
| **InboundLedgers** | `src/xrpld/app/ledger/InboundLedgers.cpp` | Ledger acquisition | Sync time, peer reliability |
| **ValidatorList** | `src/xrpld/app/misc/ValidatorList.cpp` | UNL management | List freshness, fetch failures |
| **AmendmentTable** | `src/xrpld/app/misc/AmendmentTable.cpp` | Protocol amendments | Voting status, activation events |
| **SHAMap** | `src/xrpld/shamap/` | State hash tree | Sync speed, missing nodes |
---
## 1.3 Transaction Flow Diagram
Transaction flow spans multiple nodes in the network. Each node creates linked spans to form a distributed trace:
```mermaid
sequenceDiagram
participant Client
participant PeerA as Peer A (Receive)
participant PeerB as Peer B (Relay)
participant PeerC as Peer C (Validate)
Client->>PeerA: 1. Submit TX
rect rgb(230, 245, 255)
Note over PeerA: tx.receive SPAN START
PeerA->>PeerA: HashRouter Deduplication
PeerA->>PeerA: tx.validate (child span)
end
PeerA->>PeerB: 2. Relay TX (with trace ctx)
rect rgb(230, 245, 255)
Note over PeerB: tx.receive (linked span)
end
PeerB->>PeerC: 3. Relay TX
rect rgb(230, 245, 255)
Note over PeerC: tx.receive (linked span)
PeerC->>PeerC: tx.process
end
Note over Client,PeerC: DISTRIBUTED TRACE (same trace_id: abc123)
```
**Reading the diagram:**
- **Client**: The external entity that submits a transaction to Peer A. It has no trace context -- the trace starts at the first node.
- **Peer A (Receive)**: The entry node that creates the root span `tx.receive`, runs HashRouter deduplication to avoid processing duplicates, and creates a child `tx.validate` span.
- **Peer A to Peer B arrow**: The relay message carries trace context (trace_id + parent span_id), enabling Peer B to create a linked span under the same trace.
- **Peer B (Relay)**: Receives the transaction and trace context, creates a `tx.receive` span linked to Peer A's trace, then relays onward.
- **Peer C (Validate)**: Final hop in this example. Creates a linked `tx.receive` span and runs `tx.process` to fully process the transaction.
- **Blue rectangles**: Highlight the span boundaries on each node, showing where instrumentation creates and closes spans.
### Trace Structure
```
trace_id: abc123
├── span: tx.receive (Peer A)
│ ├── span: tx.validate
│ └── span: tx.relay
├── span: tx.receive (Peer B) [parent: Peer A]
│ └── span: tx.relay
└── span: tx.receive (Peer C) [parent: Peer B]
└── span: tx.process
```
---
## 1.4 Consensus Round Flow
Consensus rounds are multi-phase operations that benefit significantly from tracing:
```mermaid
flowchart TB
subgraph round["consensus.round (root span)"]
attrs["Attributes:<br/>xrpl.consensus.ledger.seq = 12345678<br/>xrpl.consensus.mode = proposing<br/>xrpl.consensus.proposers = 35"]
subgraph open["consensus.phase.open"]
open_desc["Duration: ~3s<br/>Waiting for transactions"]
end
subgraph establish["consensus.phase.establish"]
est_attrs["proposals_received = 28<br/>disputes_resolved = 3"]
est_children["├── consensus.proposal.receive (×28)<br/>├── consensus.proposal.send (×1)<br/>└── consensus.dispute.resolve (×3)"]
end
subgraph accept["consensus.phase.accept"]
acc_attrs["transactions_applied = 150<br/>ledger.hash = DEF456..."]
acc_children["├── ledger.build<br/>└── ledger.validate"]
end
attrs --> open
open --> establish
establish --> accept
end
style round fill:#f57f17,stroke:#e65100,color:#ffffff
style open fill:#1565c0,stroke:#0d47a1,color:#ffffff
style establish fill:#2e7d32,stroke:#1b5e20,color:#ffffff
style accept fill:#c2185b,stroke:#880e4f,color:#ffffff
```
**Reading the diagram:**
- **consensus.round (orange, root span)**: The top-level span encompassing the entire consensus round, with attributes like ledger sequence, mode, and proposer count.
- **consensus.phase.open (blue)**: The first phase where the node waits (~3s) to collect incoming transactions before proposing.
- **consensus.phase.establish (green)**: The negotiation phase where validators exchange proposals, resolve disputes, and converge on a transaction set. Child spans track each proposal received/sent and each dispute resolved.
- **consensus.phase.accept (pink)**: The final phase where the agreed transaction set is applied, a new ledger is built, and the ledger is validated. Child spans cover `ledger.build` and `ledger.validate`.
- **Arrows (open to establish to accept)**: The sequential flow through the three consensus phases. Each phase must complete before the next begins.
---
## 1.5 RPC Request Flow
> **WS** = WebSocket
RPC requests support W3C Trace Context headers for distributed tracing across services:
```mermaid
flowchart TB
subgraph request["rpc.request (root span)"]
http["HTTP Request — POST /<br/>traceparent:<br/>00-abc123...-def456...-01"]
attrs["Attributes:<br/>http.method = POST<br/>net.peer.ip = 192.168.1.100<br/>xrpl.rpc.command = submit"]
subgraph enqueue["jobqueue.enqueue"]
job_attr["xrpl.job.type = jtCLIENT_RPC"]
end
subgraph command["rpc.command.submit"]
cmd_attrs["xrpl.rpc.version = 2<br/>xrpl.rpc.role = user"]
cmd_children["├── tx.deserialize<br/>├── tx.validate_local<br/>└── tx.submit_to_network"]
end
response["Response: 200 OK<br/>Duration: 45ms"]
http --> attrs
attrs --> enqueue
enqueue --> command
command --> response
end
style request fill:#2e7d32,stroke:#1b5e20,color:#ffffff
style enqueue fill:#1565c0,stroke:#0d47a1,color:#ffffff
style command fill:#e65100,stroke:#bf360c,color:#ffffff
```
**Reading the diagram:**
- **rpc.request (green, root span)**: The outermost span representing the full RPC request lifecycle, from HTTP receipt to response. Carries the W3C `traceparent` header for distributed tracing.
- **HTTP Request node**: Shows the incoming POST request with its `traceparent` header and extracted attributes (method, peer IP, command name).
- **jobqueue.enqueue (blue)**: The span covering the asynchronous handoff from the RPC thread to the JobQueue worker thread. The trace context is preserved across this async boundary.
- **rpc.command.submit (orange)**: The span for the actual command execution, with child spans for deserialization, local validation, and network submission.
- **Response node**: The final output with HTTP status and total duration, marking the end of the root span.
- **Arrows (top to bottom)**: The sequential processing pipeline -- receive request, extract attributes, enqueue job, execute command, return response.
---
## 1.6 Key Trace Points
> **TxQ** = Transaction Queue
The following table identifies priority instrumentation points across the codebase:
| Category | Span Name | File | Method | Priority |
| --------------- | ---------------------- | ---------------------- | ----------------------- | -------- |
| **Transaction** | `tx.receive` | `PeerImp.cpp` | `handleTransaction()` | High |
| **Transaction** | `tx.validate` | `NetworkOPs.cpp` | `processTransaction()` | High |
| **Transaction** | `tx.process` | `NetworkOPs.cpp` | `doTransactionSync()` | High |
| **Transaction** | `tx.relay` | `OverlayImpl.cpp` | `relay()` | Medium |
| **Consensus** | `consensus.round` | `RCLConsensus.cpp` | `startRound()` | High |
| **Consensus** | `consensus.phase.*` | `Consensus.h` | `timerEntry()` | High |
| **Consensus** | `consensus.proposal.*` | `RCLConsensus.cpp` | `peerProposal()` | Medium |
| **RPC** | `rpc.request` | `ServerHandler.cpp` | `onRequest()` | High |
| **RPC** | `rpc.command.*` | `RPCHandler.cpp` | `doCommand()` | High |
| **Peer** | `peer.connect` | `OverlayImpl.cpp` | `onHandoff()` | Low |
| **Peer** | `peer.message.*` | `PeerImp.cpp` | `onMessage()` | Low |
| **Ledger** | `ledger.acquire` | `InboundLedgers.cpp` | `acquire()` | Medium |
| **Ledger** | `ledger.build` | `RCLConsensus.cpp` | `buildLCL()` | High |
| **PathFinding** | `pathfind.request` | `PathRequest.cpp` | `doUpdate()` | High |
| **PathFinding** | `pathfind.compute` | `Pathfinder.cpp` | `findPaths()` | High |
| **TxQ** | `txq.enqueue` | `TxQ.cpp` | `apply()` | High |
| **TxQ** | `txq.apply` | `TxQ.cpp` | `processClosedLedger()` | High |
| **Fee** | `fee.escalate` | `LoadManager.cpp` | `raiseLocalFee()` | Medium |
| **Ledger** | `ledger.replay` | `LedgerReplayer.h` | `replay()` | Medium |
| **Ledger** | `ledger.delta` | `LedgerDeltaAcquire.h` | `processData()` | Medium |
| **Validator** | `validator.list.fetch` | `ValidatorList.cpp` | `verify()` | Medium |
| **Validator** | `validator.manifest` | `Manifest.cpp` | `applyManifest()` | Low |
| **Amendment** | `amendment.vote` | `AmendmentTable.cpp` | `doVoting()` | Low |
| **SHAMap** | `shamap.sync` | `SHAMap.cpp` | `fetchRoot()` | Medium |
---
## 1.7 Instrumentation Priority
> **TxQ** = Transaction Queue
```mermaid
quadrantChart
title Instrumentation Priority Matrix
x-axis Low Complexity --> High Complexity
y-axis Low Value --> High Value
quadrant-1 Implement First
quadrant-2 Plan Carefully
quadrant-3 Quick Wins
quadrant-4 Consider Later
RPC Tracing: [0.2, 0.92]
Transaction Tracing: [0.55, 0.88]
Consensus Tracing: [0.78, 0.82]
PathFinding: [0.38, 0.75]
TxQ and Fees: [0.25, 0.65]
Ledger Sync: [0.62, 0.58]
Peer Message Tracing: [0.35, 0.25]
JobQueue Tracing: [0.2, 0.48]
Validator Mgmt: [0.48, 0.42]
Amendment Tracking: [0.15, 0.32]
SHAMap Operations: [0.72, 0.45]
```
---
## 1.8 Observable Outcomes
> **TxQ** = Transaction Queue | **UNL** = Unique Node List
After implementing OpenTelemetry, operators and developers will gain visibility into the following:
### 1.8.1 What You Will See: Traces
| Trace Type | Description | Example Query in Grafana/Tempo |
| -------------------------- | ------------------------------------------------------------------------------------------- | ------------------------------------------------------ |
| **Transaction Lifecycle** | Full journey from RPC submission through validation, relay, consensus, and ledger inclusion | `{service.name="rippled" && xrpl.tx.hash="ABC123..."}` |
| **Cross-Node Propagation** | Transaction path across multiple rippled nodes with timing | `{xrpl.tx.relay_count > 0}` |
| **Consensus Rounds** | Complete round with all phases (open, establish, accept) | `{span.name=~"consensus.round.*"}` |
| **RPC Request Processing** | Individual command execution with timing breakdown | `{xrpl.rpc.command="account_info"}` |
| **Ledger Acquisition** | Peer-to-peer ledger data requests and responses | `{span.name="ledger.acquire"}` |
| **PathFinding Latency** | Path computation time and cache effectiveness for payment RPCs | `{span.name="pathfind.compute"}` |
| **TxQ Behavior** | Queue depth, eviction patterns, fee escalation during congestion | `{span.name=~"txq.*"}` |
| **Ledger Sync** | Full acquisition timeline including delta and transaction fetches | `{span.name=~"ledger.acquire.*"}` |
| **Validator Health** | UNL fetch success, manifest updates, stale list detection | `{span.name=~"validator.*"}` |
### 1.8.2 What You Will See: Metrics (Derived from Traces)
| Metric | Description | Dashboard Panel |
| ----------------------------- | --------------------------------------- | --------------------------- |
| **RPC Latency (p50/p95/p99)** | Response time distribution per command | Heatmap by command |
| **Transaction Throughput** | Transactions processed per second | Time series graph |
| **Consensus Round Duration** | Time to complete consensus phases | Histogram |
| **Cross-Node Latency** | Time for transaction to reach N nodes | Line chart with percentiles |
| **Error Rate** | Failed transactions/RPC calls by type | Stacked bar chart |
| **PathFinding Latency** | Path computation time per currency pair | Heatmap by currency |
| **TxQ Depth** | Queued transactions over time | Time series with thresholds |
| **Fee Escalation Level** | Current fee multiplier | Gauge with alert thresholds |
| **Ledger Sync Duration** | Time to acquire missing ledgers | Histogram |
### 1.8.3 Concrete Dashboard Examples
**Transaction Trace View (Tempo):**
```
┌────────────────────────────────────────────────────────────────────────────────┐
│ Trace: abc123... (Transaction Submission) Duration: 847ms │
├────────────────────────────────────────────────────────────────────────────────┤
│ ├── rpc.request [ServerHandler] ████░░░░░░ 45ms │
│ │ └── rpc.command.submit [RPCHandler] ████░░░░░░ 42ms │
│ │ └── tx.receive [NetworkOPs] ███░░░░░░░ 35ms │
│ │ ├── tx.validate [TxQ] █░░░░░░░░░ 8ms │
│ │ └── tx.relay [Overlay] ██░░░░░░░░ 15ms │
│ │ ├── tx.receive [Node-B] █████░░░░░ 52ms │
│ │ │ └── tx.relay [Node-B] ██░░░░░░░░ 18ms │
│ │ └── tx.receive [Node-C] ██████░░░░ 65ms │
│ └── consensus.round [RCLConsensus] ████████░░ 720ms │
│ ├── consensus.phase.open ██░░░░░░░░ 180ms │
│ ├── consensus.phase.establish █████░░░░░ 480ms │
│ └── consensus.phase.accept █░░░░░░░░░ 60ms │
└────────────────────────────────────────────────────────────────────────────────┘
```
**RPC Performance Dashboard Panel:**
```
┌─────────────────────────────────────────────────────────────┐
│ RPC Command Latency (Last 1 Hour) │
├─────────────────────────────────────────────────────────────┤
│ Command │ p50 │ p95 │ p99 │ Errors │ Rate │
│──────────────────┼────────┼────────┼────────┼────────┼──────│
│ account_info │ 12ms │ 45ms │ 89ms │ 0.1% │ 150/s│
│ submit │ 35ms │ 120ms │ 250ms │ 2.3% │ 45/s│
│ ledger │ 8ms │ 25ms │ 55ms │ 0.0% │ 80/s│
│ tx │ 15ms │ 50ms │ 100ms │ 0.5% │ 60/s│
│ server_info │ 5ms │ 12ms │ 20ms │ 0.0% │ 200/s│
└─────────────────────────────────────────────────────────────┘
```
**Consensus Health Dashboard Panel:**
```mermaid
---
config:
xyChart:
width: 1200
height: 400
plotReservedSpacePercent: 50
chartOrientation: vertical
themeVariables:
xyChart:
plotColorPalette: "#3498db"
---
xychart-beta
title "Consensus Round Duration (Last 24 Hours)"
x-axis "Time of Day (Hours)" [0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24]
y-axis "Duration (seconds)" 1 --> 5
line [2.1, 2.4, 2.8, 3.2, 3.8, 4.3, 4.5, 5.0, 4.7, 4.0, 3.2, 2.6, 2.0]
```
### 1.8.4 Operator Actionable Insights
| Scenario | What You'll See | Action |
| ------------------------- | ---------------------------------------------------------------------------- | ------------------------------------------------ |
| **Slow RPC** | Span showing which phase is slow (parsing, execution, serialization) | Optimize specific code path |
| **Transaction Stuck** | Trace stops at validation; error attribute shows reason | Fix transaction parameters |
| **Consensus Delay** | Phase.establish taking too long; proposer attribute shows missing validators | Investigate network connectivity |
| **Memory Spike** | Large batch of spans correlating with memory increase | Tune batch_size or sampling |
| **Network Partition** | Traces missing cross-node links for specific peer | Check peer connectivity |
| **Path Computation Slow** | pathfind.compute span shows high latency; cache miss rate in attributes | Warm the RippleLineCache, check order book depth |
| **TxQ Full** | txq.enqueue spans show evictions; fee.escalate spans increasing | Monitor fee levels, alert operators |
| **Ledger Sync Stalled** | ledger.acquire spans timing out; peer reliability attributes show issues | Check peer connectivity, add trusted peers |
| **UNL Stale** | validator.list.fetch spans failing; last_update attribute aging | Verify validator site URLs, check DNS |
### 1.8.5 Developer Debugging Workflow
1. **Find Transaction**: Query by `xrpl.tx.hash` to get full trace
2. **Identify Bottleneck**: Look at span durations to find slowest component
3. **Check Attributes**: Review `xrpl.tx.validity`, `xrpl.rpc.status` for errors
4. **Correlate Logs**: Use `trace_id` to find related PerfLog entries
5. **Compare Nodes**: Filter by `service.instance.id` to compare behavior across nodes
---
_Next: [Design Decisions](./02-design-decisions.md)_ | _Back to: [Overview](./OpenTelemetryPlan.md)_

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# Design Decisions
> **Parent Document**: [OpenTelemetryPlan.md](./OpenTelemetryPlan.md)
> **Related**: [Architecture Analysis](./01-architecture-analysis.md) | [Code Samples](./04-code-samples.md)
---
## 2.1 OpenTelemetry Components
> **OTLP** = OpenTelemetry Protocol
### 2.1.1 SDK Selection
**Primary Choice**: OpenTelemetry C++ SDK (`opentelemetry-cpp`)
| Component | Purpose | Required |
| --------------------------------------- | ---------------------- | ----------- |
| `opentelemetry-cpp::api` | Tracing API headers | Yes |
| `opentelemetry-cpp::sdk` | SDK implementation | Yes |
| `opentelemetry-cpp::ext` | Extensions (exporters) | Yes |
| `opentelemetry-cpp::otlp_grpc_exporter` | OTLP/gRPC export | Recommended |
| `opentelemetry-cpp::otlp_http_exporter` | OTLP/HTTP export | Alternative |
### 2.1.2 Instrumentation Strategy
**Manual Instrumentation** (recommended):
| Approach | Pros | Cons |
| ---------- | ----------------------------------------------------------------- | ------------------------------------------------------- |
| **Manual** | Precise control, optimized placement, rippled-specific attributes | More development effort |
| **Auto** | Less code, automatic coverage | Less control, potential overhead, limited customization |
---
## 2.2 Exporter Configuration
> **OTLP** = OpenTelemetry Protocol
```mermaid
flowchart TB
subgraph nodes["rippled Nodes"]
node1["rippled<br/>Node 1"]
node2["rippled<br/>Node 2"]
node3["rippled<br/>Node 3"]
end
collector["OpenTelemetry<br/>Collector<br/>(sidecar or standalone)"]
subgraph backends["Observability Backends"]
tempo["Tempo"]
elastic["Elastic<br/>APM"]
end
node1 -->|"OTLP/gRPC<br/>:4317"| collector
node2 -->|"OTLP/gRPC<br/>:4317"| collector
node3 -->|"OTLP/gRPC<br/>:4317"| collector
collector --> tempo
collector --> elastic
style nodes fill:#0d47a1,stroke:#082f6a,color:#ffffff
style backends fill:#1b5e20,stroke:#0d3d14,color:#ffffff
style collector fill:#bf360c,stroke:#8c2809,color:#ffffff
```
**Reading the diagram:**
- **rippled Nodes (blue)**: The source of telemetry data. Each rippled node exports spans via OTLP/gRPC on port 4317.
- **OpenTelemetry Collector (red)**: The central aggregation point that receives spans from all nodes. Can run as a sidecar (per-node) or standalone (shared). Handles batching, filtering, and routing.
- **Observability Backends (green)**: The storage and visualization destinations. Tempo is the recommended backend for both development and production, and Elastic APM is an alternative. The Collector routes to one or more backends.
- **Arrows (nodes to collector to backends)**: The data pipeline -- spans flow from nodes to the Collector over gRPC, then the Collector fans out to the configured backends.
### 2.2.1 OTLP/gRPC (Recommended)
```cpp
// Configuration for OTLP over gRPC
namespace otlp = opentelemetry::exporter::otlp;
otlp::OtlpGrpcExporterOptions opts;
opts.endpoint = "localhost:4317";
opts.useTls = true;
opts.sslCaCertPath = "/path/to/ca.crt";
```
### 2.2.2 OTLP/HTTP (Alternative)
```cpp
// Configuration for OTLP over HTTP
namespace otlp = opentelemetry::exporter::otlp;
otlp::OtlpHttpExporterOptions opts;
opts.url = "http://localhost:4318/v1/traces";
opts.content_type = otlp::HttpRequestContentType::kJson; // or kBinary
```
---
## 2.3 Span Naming Conventions
> **TxQ** = Transaction Queue | **UNL** = Unique Node List | **WS** = WebSocket
### 2.3.1 Naming Schema
```
<component>.<operation>[.<sub-operation>]
```
**Examples**:
- `tx.receive` - Transaction received from peer
- `consensus.phase.establish` - Consensus establish phase
- `rpc.command.server_info` - server_info RPC command
### 2.3.2 Complete Span Catalog
```yaml
# Transaction Spans
tx:
receive: "Transaction received from network"
validate: "Transaction signature/format validation"
process: "Full transaction processing"
relay: "Transaction relay to peers"
apply: "Apply transaction to ledger"
# Consensus Spans
consensus:
round: "Complete consensus round"
phase:
open: "Open phase - collecting transactions"
establish: "Establish phase - reaching agreement"
accept: "Accept phase - applying consensus"
proposal:
receive: "Receive peer proposal"
send: "Send our proposal"
validation:
receive: "Receive peer validation"
send: "Send our validation"
# RPC Spans
rpc:
request: "HTTP/WebSocket request handling"
command:
"*": "Specific RPC command (dynamic)"
# Peer Spans
peer:
connect: "Peer connection establishment"
disconnect: "Peer disconnection"
message:
send: "Send protocol message"
receive: "Receive protocol message"
# Ledger Spans
ledger:
acquire: "Ledger acquisition from network"
build: "Build new ledger"
validate: "Ledger validation"
close: "Close ledger"
replay: "Ledger replay executed"
delta: "Delta-based ledger acquired"
# PathFinding Spans
pathfind:
request: "Path request initiated"
compute: "Path computation executed"
# TxQ Spans
txq:
enqueue: "Transaction queued"
apply: "Queued transaction applied"
# Fee/Load Spans
fee:
escalate: "Fee escalation triggered"
# Validator Spans
validator:
list:
fetch: "UNL list fetched"
manifest: "Manifest update processed"
# Amendment Spans
amendment:
vote: "Amendment voting executed"
# SHAMap Spans
shamap:
sync: "State tree synchronization"
# Job Spans
job:
enqueue: "Job added to queue"
execute: "Job execution"
```
---
## 2.4 Attribute Schema
> **TxQ** = Transaction Queue | **UNL** = Unique Node List | **OTLP** = OpenTelemetry Protocol
### 2.4.1 Resource Attributes (Set Once at Startup)
```cpp
// Standard OpenTelemetry semantic conventions
resource::SemanticConventions::SERVICE_NAME = "rippled"
resource::SemanticConventions::SERVICE_VERSION = BuildInfo::getVersionString()
resource::SemanticConventions::SERVICE_INSTANCE_ID = <node_public_key_base58>
// Custom rippled attributes
"xrpl.network.id" = <network_id> // e.g., 0 for mainnet
"xrpl.network.type" = "mainnet" | "testnet" | "devnet" | "standalone"
"xrpl.node.type" = "validator" | "stock" | "reporting"
"xrpl.node.cluster" = <cluster_name> // If clustered
```
### 2.4.2 Span Attributes by Category
#### Transaction Attributes
```cpp
"xrpl.tx.hash" = string // Transaction hash (hex)
"xrpl.tx.type" = string // "Payment", "OfferCreate", etc.
"xrpl.tx.account" = string // Source account (redacted in prod)
"xrpl.tx.sequence" = int64 // Account sequence number
"xrpl.tx.fee" = int64 // Fee in drops
"xrpl.tx.result" = string // "tesSUCCESS", "tecPATH_DRY", etc.
"xrpl.tx.ledger_index" = int64 // Ledger containing transaction
```
#### Consensus Attributes
```cpp
"xrpl.consensus.round" = int64 // Round number
"xrpl.consensus.phase" = string // "open", "establish", "accept"
"xrpl.consensus.mode" = string // "proposing", "observing", etc.
"xrpl.consensus.proposers" = int64 // Number of proposers
"xrpl.consensus.ledger.prev" = string // Previous ledger hash
"xrpl.consensus.ledger.seq" = int64 // Ledger sequence
"xrpl.consensus.tx_count" = int64 // Transactions in consensus set
"xrpl.consensus.duration_ms" = float64 // Round duration
// Phase 4a: Establish-phase gap fill & cross-node correlation
"xrpl.consensus.round_id" = int64 // Consensus round number
"xrpl.consensus.ledger_id" = string // previousLedger.id() — shared across nodes
"xrpl.consensus.trace_strategy" = string // "deterministic" or "attribute"
"xrpl.consensus.converge_percent" = int64 // Convergence % (0-100+)
"xrpl.consensus.establish_count" = int64 // Number of establish iterations
"xrpl.consensus.disputes_count" = int64 // Active disputed transactions
"xrpl.consensus.proposers_agreed" = int64 // Peers agreeing with our position
"xrpl.consensus.proposers_total" = int64 // Total peer positions
"xrpl.consensus.agree_count" = int64 // Peers that agree (haveConsensus)
"xrpl.consensus.disagree_count" = int64 // Peers that disagree
"xrpl.consensus.threshold_percent" = int64 // Current threshold (50/65/70/95)
"xrpl.consensus.result" = string // "yes", "no", "moved_on"
"xrpl.consensus.mode.old" = string // Previous consensus mode
"xrpl.consensus.mode.new" = string // New consensus mode
```
#### RPC Attributes
```cpp
"xrpl.rpc.command" = string // Command name
"xrpl.rpc.version" = int64 // API version
"xrpl.rpc.role" = string // "admin" or "user"
"xrpl.rpc.params" = string // Sanitized parameters (optional)
```
#### Peer & Message Attributes
```cpp
"xrpl.peer.id" = string // Peer public key (base58)
"xrpl.peer.address" = string // IP:port
"xrpl.peer.latency_ms" = float64 // Measured latency
"xrpl.peer.cluster" = string // Cluster name if clustered
"xrpl.message.type" = string // Protocol message type name
"xrpl.message.size_bytes" = int64 // Message size
"xrpl.message.compressed" = bool // Whether compressed
```
#### Ledger & Job Attributes
```cpp
"xrpl.ledger.hash" = string // Ledger hash
"xrpl.ledger.index" = int64 // Ledger sequence/index
"xrpl.ledger.close_time" = int64 // Close time (epoch)
"xrpl.ledger.tx_count" = int64 // Transaction count
"xrpl.job.type" = string // Job type name
"xrpl.job.queue_ms" = float64 // Time spent in queue
"xrpl.job.worker" = int64 // Worker thread ID
```
#### PathFinding Attributes
```cpp
"xrpl.pathfind.source_currency" = string // Source currency code
"xrpl.pathfind.dest_currency" = string // Destination currency code
"xrpl.pathfind.path_count" = int64 // Number of paths found
"xrpl.pathfind.cache_hit" = bool // RippleLineCache hit
```
#### TxQ Attributes
```cpp
"xrpl.txq.queue_depth" = int64 // Current queue depth
"xrpl.txq.fee_level" = int64 // Fee level of transaction
"xrpl.txq.eviction_reason" = string // Why transaction was evicted
```
#### Fee Attributes
```cpp
"xrpl.fee.load_factor" = int64 // Current load factor
"xrpl.fee.escalation_level" = int64 // Fee escalation multiplier
```
#### Validator Attributes
```cpp
"xrpl.validator.list_size" = int64 // UNL size
"xrpl.validator.list_age_sec" = int64 // Seconds since last update
```
#### Amendment Attributes
```cpp
"xrpl.amendment.name" = string // Amendment name
"xrpl.amendment.status" = string // "enabled", "vetoed", "supported"
```
#### SHAMap Attributes
```cpp
"xrpl.shamap.type" = string // "transaction", "state", "account_state"
"xrpl.shamap.missing_nodes" = int64 // Number of missing nodes during sync
"xrpl.shamap.duration_ms" = float64 // Sync duration
```
### 2.4.3 Data Collection Summary
The following table summarizes what data is collected by category:
| Category | Attributes Collected | Purpose |
| --------------- | ---------------------------------------------------------------------- | ---------------------------- |
| **Transaction** | `tx.hash`, `tx.type`, `tx.result`, `tx.fee`, `ledger_index` | Trace transaction lifecycle |
| **Consensus** | `round`, `phase`, `mode`, `proposers` (public keys), `duration_ms` | Analyze consensus timing |
| **RPC** | `command`, `version`, `status`, `duration_ms` | Monitor RPC performance |
| **Peer** | `peer.id` (public key), `latency_ms`, `message.type`, `message.size` | Network topology analysis |
| **Ledger** | `ledger.hash`, `ledger.index`, `close_time`, `tx_count` | Ledger progression tracking |
| **Job** | `job.type`, `queue_ms`, `worker` | JobQueue performance |
| **PathFinding** | `pathfind.source_currency`, `dest_currency`, `path_count`, `cache_hit` | Payment path analysis |
| **TxQ** | `txq.queue_depth`, `fee_level`, `eviction_reason` | Queue depth and fee tracking |
| **Fee** | `fee.load_factor`, `escalation_level` | Fee escalation monitoring |
| **Validator** | `validator.list_size`, `list_age_sec` | UNL health monitoring |
| **Amendment** | `amendment.name`, `status` | Protocol upgrade tracking |
| **SHAMap** | `shamap.type`, `missing_nodes`, `duration_ms` | State tree sync performance |
### 2.4.4 Privacy & Sensitive Data Policy
> **PII** = Personally Identifiable Information
OpenTelemetry instrumentation is designed to collect **operational metadata only**, never sensitive content.
#### Data NOT Collected
The following data is explicitly **excluded** from telemetry collection:
| Excluded Data | Reason |
| ----------------------- | ----------------------------------------- |
| **Private Keys** | Never exposed; not relevant to tracing |
| **Account Balances** | Financial data; privacy sensitive |
| **Transaction Amounts** | Financial data; privacy sensitive |
| **Raw TX Payloads** | May contain sensitive memo/data fields |
| **Personal Data** | No PII collected |
| **IP Addresses** | Configurable; excluded by default in prod |
#### Privacy Protection Mechanisms
| Mechanism | Description |
| ----------------------------- | ------------------------------------------------------------------------- |
| **Account Hashing** | `xrpl.tx.account` is hashed at collector level before storage |
| **Configurable Redaction** | Sensitive fields can be excluded via `[telemetry]` config section |
| **Sampling** | Only 10% of traces recorded by default, reducing data exposure |
| **Local Control** | Node operators have full control over what gets exported |
| **No Raw Payloads** | Transaction content is never recorded, only metadata (hash, type, result) |
| **Collector-Level Filtering** | Additional redaction/hashing can be configured at OTel Collector |
#### Collector-Level Data Protection
The OpenTelemetry Collector can be configured to hash or redact sensitive attributes before export:
```yaml
processors:
attributes:
actions:
# Hash account addresses before storage
- key: xrpl.tx.account
action: hash
# Remove IP addresses entirely
- key: xrpl.peer.address
action: delete
# Redact specific fields
- key: xrpl.rpc.params
action: delete
```
#### Configuration Options for Privacy
In `rippled.cfg`, operators can control data collection granularity:
```ini
[telemetry]
enabled=1
# Disable collection of specific components
trace_transactions=1
trace_consensus=1
trace_rpc=1
trace_peer=0 # Disable peer tracing (high volume, includes addresses)
# Redact specific attributes
redact_account=1 # Hash account addresses before export
redact_peer_address=1 # Remove peer IP addresses
```
> **Note**: The `redact_account` configuration in `rippled.cfg` controls SDK-level redaction before export, while collector-level filtering (see [Collector-Level Data Protection](#collector-level-data-protection) above) provides an additional defense-in-depth layer. Both can operate independently.
> **Key Principle**: Telemetry collects **operational metadata** (timing, counts, hashes) — never **sensitive content** (keys, balances, amounts, raw payloads).
---
## 2.5 Context Propagation Design
> **WS** = WebSocket
### 2.5.1 Propagation Boundaries
```mermaid
flowchart TB
subgraph http["HTTP/WebSocket (RPC)"]
w3c["W3C Trace Context Headers:<br/>traceparent:<br/>00-trace_id-span_id-flags<br/>tracestate: rippled=..."]
end
subgraph protobuf["Protocol Buffers (P2P)"]
proto["message TraceContext {<br/> bytes trace_id = 1; // 16 bytes<br/> bytes span_id = 2; // 8 bytes<br/> uint32 trace_flags = 3;<br/> string trace_state = 4;<br/>}"]
end
subgraph jobqueue["JobQueue (Internal Async)"]
job["Context captured at job creation,<br/>restored at execution<br/><br/>class Job {<br/> otel::context::Context<br/> traceContext_;<br/>};"]
end
style http fill:#0d47a1,stroke:#082f6a,color:#ffffff
style protobuf fill:#1b5e20,stroke:#0d3d14,color:#ffffff
style jobqueue fill:#bf360c,stroke:#8c2809,color:#ffffff
```
**Reading the diagram:**
- **HTTP/WebSocket - RPC (blue)**: For client-facing RPC requests, trace context is propagated using the W3C `traceparent` header. This is the standard approach and works with any OTel-compatible client.
- **Protocol Buffers - P2P (green)**: For peer-to-peer messages between rippled nodes, trace context is embedded as a protobuf `TraceContext` message carrying trace_id, span_id, flags, and optional trace_state.
- **JobQueue - Internal Async (red)**: For asynchronous work within a single node, the OTel context is captured when a job is created and restored when the job executes on a worker thread. This bridges the async gap so spans remain linked.
---
## 2.6 Integration with Existing Observability
> **OTLP** = OpenTelemetry Protocol | **WS** = WebSocket
### 2.6.1 Existing Frameworks Comparison
rippled already has two observability mechanisms. OpenTelemetry complements (not replaces) them:
| Aspect | PerfLog | Beast Insight (StatsD) | OpenTelemetry |
| --------------------- | ----------------------------- | ---------------------------- | ------------------------- |
| **Type** | Logging | Metrics | Distributed Tracing |
| **Data** | JSON log entries | Counters, gauges, histograms | Spans with context |
| **Scope** | Single node | Single node | **Cross-node** |
| **Output** | `perf.log` file | StatsD server | OTLP Collector |
| **Question answered** | "What happened on this node?" | "How many? How fast?" | "What was the journey?" |
| **Correlation** | By timestamp | By metric name | By `trace_id` |
| **Overhead** | Low (file I/O) | Low (UDP packets) | Low-Medium (configurable) |
### 2.6.2 What Each Framework Does Best
#### PerfLog
- **Purpose**: Detailed local event logging for RPC and job execution
- **Strengths**:
- Rich JSON output with timing data
- Already integrated in RPC handlers
- File-based, no external dependencies
- **Limitations**:
- Single-node only (no cross-node correlation)
- No parent-child relationships between events
- Manual log parsing required
```json
// Example PerfLog entry
{
"time": "2024-01-15T10:30:00.123Z",
"method": "submit",
"duration_us": 1523,
"result": "tesSUCCESS"
}
```
#### Beast Insight (StatsD)
- **Purpose**: Real-time metrics for monitoring dashboards
- **Strengths**:
- Aggregated metrics (counters, gauges, histograms)
- Low overhead (UDP, fire-and-forget)
- Good for alerting thresholds
- **Limitations**:
- No request-level detail
- No causal relationships
- Single-node perspective
```cpp
// Example StatsD usage in rippled
insight.increment("rpc.submit.count");
insight.gauge("ledger.age", age);
insight.timing("consensus.round", duration);
```
#### OpenTelemetry (NEW)
- **Purpose**: Distributed request tracing across nodes
- **Strengths**:
- **Cross-node correlation** via `trace_id`
- Parent-child span relationships
- Rich attributes per span
- Industry standard (CNCF)
- **Limitations**:
- Requires collector infrastructure
- Higher complexity than logging
```cpp
// Example OpenTelemetry span
auto span = telemetry.startSpan("tx.relay");
span->SetAttribute("tx.hash", hash);
span->SetAttribute("peer.id", peerId);
// Span automatically linked to parent via context
```
### 2.6.3 When to Use Each
| Scenario | PerfLog | StatsD | OpenTelemetry |
| --------------------------------------- | ---------- | ------ | ------------- |
| "How many TXs per second?" | ❌ | ✅ | ✅ |
| "What's the p99 RPC latency?" | ❌ | ✅ | ✅ |
| "Why was this specific TX slow?" | ⚠️ partial | ❌ | ✅ |
| "Which node delayed consensus?" | ❌ | ❌ | ✅ |
| "What happened on node X at time T?" | ✅ | ❌ | ✅ |
| "Show me the TX journey across 5 nodes" | ❌ | ❌ | ✅ |
### 2.6.4 Coexistence Strategy
```mermaid
flowchart TB
subgraph rippled["rippled Process"]
perflog["PerfLog<br/>(JSON to file)"]
insight["Beast Insight<br/>(StatsD)"]
otel["OpenTelemetry<br/>(Tracing)"]
end
perflog --> perffile["perf.log"]
insight --> statsd["StatsD Server"]
otel --> collector["OTLP Collector"]
perffile --> grafana["Grafana<br/>(Unified UI)"]
statsd --> grafana
collector --> grafana
style rippled fill:#212121,stroke:#0a0a0a,color:#ffffff
style grafana fill:#bf360c,stroke:#8c2809,color:#ffffff
```
**Reading the diagram:**
- **rippled Process (dark gray)**: The single rippled node running all three observability frameworks side by side. Each framework operates independently with no interference.
- **PerfLog to perf.log**: PerfLog writes JSON-formatted event logs to a local file. Grafana can ingest these via Loki or a file-based datasource.
- **Beast Insight to StatsD Server**: Insight sends aggregated metrics (counters, gauges) over UDP to a StatsD server. Grafana reads from StatsD-compatible backends like Graphite or Prometheus (via StatsD exporter).
- **OpenTelemetry to OTLP Collector**: OTel exports spans over OTLP/gRPC to a Collector, which then forwards to a trace backend (Tempo).
- **Grafana (red, unified UI)**: All three data streams converge in Grafana, enabling operators to correlate logs, metrics, and traces in a single dashboard.
### 2.6.5 Correlation with PerfLog
Trace IDs can be correlated with existing PerfLog entries for comprehensive debugging:
```cpp
// In RPCHandler.cpp - correlate trace with PerfLog
Status doCommand(RPC::JsonContext& context, Json::Value& result)
{
// Start OpenTelemetry span
auto span = context.app.getTelemetry().startSpan(
"rpc.command." + context.method);
// Get trace ID for correlation
auto traceId = span->GetContext().trace_id().IsValid()
? toHex(span->GetContext().trace_id())
: "";
// Use existing PerfLog with trace correlation
auto const curId = context.app.getPerfLog().currentId();
context.app.getPerfLog().rpcStart(context.method, curId);
// Future: Add trace ID to PerfLog entry
// context.app.getPerfLog().setTraceId(curId, traceId);
try {
auto ret = handler(context, result);
context.app.getPerfLog().rpcFinish(context.method, curId);
span->SetStatus(opentelemetry::trace::StatusCode::kOk);
return ret;
} catch (std::exception const& e) {
context.app.getPerfLog().rpcError(context.method, curId);
span->RecordException(e);
span->SetStatus(opentelemetry::trace::StatusCode::kError, e.what());
throw;
}
}
```
---
_Previous: [Architecture Analysis](./01-architecture-analysis.md)_ | _Next: [Implementation Strategy](./03-implementation-strategy.md)_ | _Back to: [Overview](./OpenTelemetryPlan.md)_

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# Implementation Strategy
> **Parent Document**: [OpenTelemetryPlan.md](./OpenTelemetryPlan.md)
> **Related**: [Code Samples](./04-code-samples.md) | [Configuration Reference](./05-configuration-reference.md)
---
## 3.1 Directory Structure
The telemetry implementation follows rippled's existing code organization pattern:
```
include/xrpl/
├── telemetry/
│ ├── Telemetry.h # Main telemetry interface
│ ├── TelemetryConfig.h # Configuration structures
│ ├── TraceContext.h # Context propagation utilities
│ ├── SpanGuard.h # RAII span management
│ └── SpanAttributes.h # Attribute helper functions
src/libxrpl/
├── telemetry/
│ ├── Telemetry.cpp # Implementation
│ ├── TelemetryConfig.cpp # Config parsing
│ ├── TraceContext.cpp # Context serialization
│ └── NullTelemetry.cpp # No-op implementation
src/xrpld/
├── telemetry/
│ ├── TracingInstrumentation.h # Instrumentation macros
│ └── TracingInstrumentation.cpp
```
---
## 3.2 Implementation Approach
<div align="center">
```mermaid
%%{init: {'flowchart': {'nodeSpacing': 20, 'rankSpacing': 30}}}%%
flowchart TB
subgraph phase1["Phase 1: Core"]
direction LR
sdk["SDK Integration"] ~~~ interface["Telemetry Interface"] ~~~ config["Configuration"]
end
subgraph phase2["Phase 2: RPC"]
direction LR
http["HTTP Context"] ~~~ rpc["RPC Handlers"]
end
subgraph phase3["Phase 3: P2P"]
direction LR
proto["Protobuf Context"] ~~~ tx["Transaction Relay"]
end
subgraph phase4["Phase 4: Consensus"]
direction LR
consensus["Consensus Rounds"] ~~~ proposals["Proposals"]
end
phase1 --> phase2 --> phase3 --> phase4
style phase1 fill:#1565c0,stroke:#0d47a1,color:#ffffff
style phase2 fill:#2e7d32,stroke:#1b5e20,color:#ffffff
style phase3 fill:#e65100,stroke:#bf360c,color:#ffffff
style phase4 fill:#c2185b,stroke:#880e4f,color:#ffffff
```
</div>
### Key Principles
1. **Minimal Intrusion**: Instrumentation should not alter existing control flow
2. **Zero-Cost When Disabled**: Use compile-time flags and no-op implementations
3. **Backward Compatibility**: Protocol Buffer extensions use high field numbers
4. **Graceful Degradation**: Tracing failures must not affect node operation
---
## 3.3 Performance Overhead Summary
> **OTLP** = OpenTelemetry Protocol
| Metric | Overhead | Notes |
| ------------- | ---------- | ------------------------------------------------ |
| CPU | 1-3% | Of per-transaction CPU cost (~200μs baseline) |
| Memory | ~10 MB | SDK statics + batch buffer + worker thread stack |
| Network | 10-50 KB/s | Compressed OTLP export to collector |
| Latency (p99) | <2% | With proper sampling configuration |
---
## 3.4 Detailed CPU Overhead Analysis
### 3.4.1 Per-Operation Costs
> **Note on hardware assumptions**: The costs below are based on the official OTel C++ SDK CI benchmarks
> (969 runs on GitHub Actions 2-core shared runners). On production server hardware (3+ GHz Xeon),
> expect costs at the **lower end** of each range (~30-50% improvement over CI hardware).
| Operation | Time (ns) | Frequency | Impact |
| --------------------- | --------- | ---------------------- | ---------- |
| Span creation | 500-1000 | Every traced operation | Low |
| Span end | 100-200 | Every traced operation | Low |
| SetAttribute (string) | 80-120 | 3-5 per span | Low |
| SetAttribute (int) | 40-60 | 2-3 per span | Negligible |
| AddEvent | 100-200 | 0-2 per span | Low |
| Context injection | 150-250 | Per outgoing message | Low |
| Context extraction | 100-180 | Per incoming message | Low |
| GetCurrent context | 10-20 | Thread-local access | Negligible |
**Source**: Span creation based on OTel C++ SDK `BM_SpanCreation` benchmark (AlwaysOnSampler +
SimpleSpanProcessor + InMemoryExporter), median ~1,000 ns on CI hardware. AddEvent includes
timestamp read + string copy + vector push + mutex acquisition. Context injection/extraction
confirmed by `BM_SpanCreationWithScope` benchmark delta (~160 ns).
### 3.4.2 Transaction Processing Overhead
<div align="center">
```mermaid
%%{init: {'pie': {'textPosition': 0.75}}}%%
pie showData
"tx.receive (1400ns)" : 1400
"tx.validate (1200ns)" : 1200
"tx.relay (1200ns)" : 1200
"Context inject (200ns)" : 200
```
**Transaction Tracing Overhead (~4.0μs total)**
</div>
**Overhead percentage**: 4.0 μs / 200 μs (avg tx processing) = **~2.0%**
> **Breakdown**: Each span (tx.receive, tx.validate, tx.relay) costs ~1,000 ns for creation plus
> ~200-400 ns for 3-5 attribute sets. Context injection is ~200 ns (confirmed by benchmarks).
> On production hardware, expect ~2.6 μs total (~1.3% overhead) due to faster span creation (~500-600 ns).
### 3.4.3 Consensus Round Overhead
| Operation | Count | Cost (ns) | Total |
| ---------------------- | ----- | --------- | ---------- |
| consensus.round span | 1 | ~1200 | ~1.2 μs |
| consensus.phase spans | 3 | ~1100 | ~3.3 μs |
| proposal.receive spans | ~20 | ~1100 | ~22 μs |
| proposal.send spans | ~3 | ~1100 | ~3.3 μs |
| Context operations | ~30 | ~200 | ~6 μs |
| **TOTAL** | | | **~36 μs** |
> **Why higher**: Each span costs ~1,000 ns creation + ~100-200 ns for 1-2 attributes, totaling ~1,100-1,200 ns.
> Context operations remain ~200 ns (confirmed by benchmarks). On production hardware, expect ~24 μs total.
**Overhead percentage**: 36 μs / 3s (typical round) = **~0.001%** (negligible)
### 3.4.4 RPC Request Overhead
| Operation | Cost (ns) |
| ---------------- | ------------ |
| rpc.request span | ~1200 |
| rpc.command span | ~1100 |
| Context extract | ~250 |
| Context inject | ~200 |
| **TOTAL** | **~2.75 μs** |
> **Why higher**: Each span costs ~1,000 ns creation + ~100-200 ns for attributes (command name,
> version, role). Context extract/inject costs are confirmed by OTel C++ benchmarks.
- Fast RPC (1ms): 2.75 μs / 1ms = **~0.275%**
- Slow RPC (100ms): 2.75 μs / 100ms = **~0.003%**
---
## 3.5 Memory Overhead Analysis
> **OTLP** = OpenTelemetry Protocol
### 3.5.1 Static Memory
| Component | Size | Allocated |
| ------------------------------------ | ----------- | ---------- |
| TracerProvider singleton | ~64 KB | At startup |
| BatchSpanProcessor (circular buffer) | ~16 KB | At startup |
| BatchSpanProcessor (worker thread) | ~8 MB | At startup |
| OTLP exporter (gRPC channel init) | ~256 KB | At startup |
| Propagator registry | ~8 KB | At startup |
| **Total static** | **~8.3 MB** | |
> **Why higher than earlier estimate**: The BatchSpanProcessor's circular buffer itself is only ~16 KB
> (2049 x 8-byte `AtomicUniquePtr` entries), but it spawns a dedicated worker thread whose default
> stack size on Linux is ~8 MB. The OTLP gRPC exporter allocates memory for channel stubs and TLS
> initialization. The worker thread stack dominates the static footprint.
### 3.5.2 Dynamic Memory
| Component | Size per unit | Max units | Peak |
| -------------------- | -------------- | ---------- | --------------- |
| Active span | ~500-800 bytes | 1000 | ~500-800 KB |
| Queued span (export) | ~500 bytes | 2048 | ~1 MB |
| Attribute storage | ~80 bytes | 5 per span | Included |
| Context storage | ~64 bytes | Per thread | ~6.4 KB |
| **Total dynamic** | | | **~1.5-1.8 MB** |
> **Why active spans are larger**: An active `Span` object includes the wrapper (~88 bytes: shared_ptr,
> mutex, unique_ptr to Recordable) plus `SpanData` (~250 bytes: SpanContext, timestamps, name, status,
> empty containers) plus attribute storage (~200-500 bytes for 3-5 string attributes in a `std::map`).
> Source: `sdk/src/trace/span.h` and `sdk/include/opentelemetry/sdk/trace/span_data.h`.
> Queued spans release the wrapper, keeping only `SpanData` + attributes (~500 bytes).
### 3.5.3 Memory Growth Characteristics
```mermaid
---
config:
xyChart:
width: 700
height: 400
---
xychart-beta
title "Memory Usage vs Span Rate (bounded by queue limit)"
x-axis "Spans/second" [0, 200, 400, 600, 800, 1000]
y-axis "Memory (MB)" 0 --> 12
line [8.5, 9.2, 9.6, 9.9, 10.0, 10.0]
```
**Notes**:
- Memory increases with span rate but **plateaus at queue capacity** (default 2048 spans)
- Batch export prevents unbounded growth
- At queue limit, oldest spans are dropped (not blocked)
- Maximum memory is bounded: ~8.3 MB static (dominated by worker thread stack) + 2048 queued spans x ~500 bytes (~1 MB) + active spans (~0.8 MB) ≈ **~10 MB ceiling**
- The worker thread stack (~8 MB) is virtual memory; actual RSS depends on stack usage (typically much less)
### 3.5.4 Performance Data Sources
The overhead estimates in Sections 3.3-3.5 are derived from the following sources:
| Source | What it covers | URL |
| ------------------------------------------------ | ----------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------ |
| OTel C++ SDK CI benchmarks (969 runs) | Span creation, context activation, sampler overhead | [Benchmark Dashboard](https://open-telemetry.github.io/opentelemetry-cpp/benchmarks/) |
| `api/test/trace/span_benchmark.cc` | API-level span creation (~22 ns no-op) | [Source](https://github.com/open-telemetry/opentelemetry-cpp/blob/main/api/test/trace/span_benchmark.cc) |
| `sdk/test/trace/sampler_benchmark.cc` | SDK span creation with samplers (~1,000 ns AlwaysOn) | [Source](https://github.com/open-telemetry/opentelemetry-cpp/blob/main/sdk/test/trace/sampler_benchmark.cc) |
| `sdk/include/.../span_data.h` | SpanData memory layout (~250 bytes base) | [Source](https://github.com/open-telemetry/opentelemetry-cpp/blob/main/sdk/include/opentelemetry/sdk/trace/span_data.h) |
| `sdk/src/trace/span.h` | Span wrapper memory layout (~88 bytes) | [Source](https://github.com/open-telemetry/opentelemetry-cpp/blob/main/sdk/src/trace/span.h) |
| `sdk/include/.../batch_span_processor_options.h` | Default queue size (2048), batch size (512) | [Source](https://github.com/open-telemetry/opentelemetry-cpp/blob/main/sdk/include/opentelemetry/sdk/trace/batch_span_processor_options.h) |
| `sdk/include/.../circular_buffer.h` | CircularBuffer implementation (AtomicUniquePtr array) | [Source](https://github.com/open-telemetry/opentelemetry-cpp/blob/main/sdk/include/opentelemetry/sdk/common/circular_buffer.h) |
| OTLP proto definition | Serialized span size estimation | [Proto](https://github.com/open-telemetry/opentelemetry-proto/blob/main/opentelemetry/proto/trace/v1/trace.proto) |
---
## 3.6 Network Overhead Analysis
### 3.6.1 Export Bandwidth
> **Bytes per span**: Estimates use ~500 bytes/span (conservative upper bound). OTLP protobuf analysis
> shows a typical span with 3-5 string attributes serializes to ~200-300 bytes raw; with gzip
> compression (~60-70% of raw) and batching (amortized headers), ~350 bytes/span is more realistic.
> The table uses the conservative estimate for capacity planning.
| Sampling Rate | Spans/sec | Bandwidth | Notes |
| ------------- | --------- | --------- | ---------------- |
| 100% | ~500 | ~250 KB/s | Development only |
| 10% | ~50 | ~25 KB/s | Staging |
| 1% | ~5 | ~2.5 KB/s | Production |
| Error-only | ~1 | ~0.5 KB/s | Minimal overhead |
### 3.6.2 Trace Context Propagation
| Message Type | Context Size | Messages/sec | Overhead |
| ---------------------- | ------------ | ------------ | ----------- |
| TMTransaction | 25 bytes | ~100 | ~2.5 KB/s |
| TMProposeSet | 25 bytes | ~10 | ~250 B/s |
| TMValidation | 25 bytes | ~50 | ~1.25 KB/s |
| **Total P2P overhead** | | | **~4 KB/s** |
---
## 3.7 Optimization Strategies
### 3.7.1 Sampling Strategies
#### Tail Sampling
```mermaid
flowchart TD
trace["New Trace"]
trace --> errors{"Is Error?"}
errors -->|Yes| sample["SAMPLE"]
errors -->|No| consensus{"Is Consensus?"}
consensus -->|Yes| sample
consensus -->|No| slow{"Is Slow?"}
slow -->|Yes| sample
slow -->|No| prob{"Random < 10%?"}
prob -->|Yes| sample
prob -->|No| drop["DROP"]
style sample fill:#4caf50,stroke:#388e3c,color:#fff
style drop fill:#f44336,stroke:#c62828,color:#fff
```
### 3.7.2 Batch Tuning Recommendations
| Environment | Batch Size | Batch Delay | Max Queue |
| ------------------ | ---------- | ----------- | --------- |
| Low-latency | 128 | 1000ms | 512 |
| High-throughput | 1024 | 10000ms | 8192 |
| Memory-constrained | 256 | 2000ms | 512 |
### 3.7.3 Conditional Instrumentation
```cpp
// Compile-time feature flag
#ifndef XRPL_ENABLE_TELEMETRY
// Zero-cost when disabled
#define XRPL_TRACE_SPAN(t, n) ((void)0)
#endif
// Runtime component filtering
if (telemetry.shouldTracePeer())
{
XRPL_TRACE_SPAN(telemetry, "peer.message.receive");
// ... instrumentation
}
// No overhead when component tracing disabled
```
---
## 3.8 Links to Detailed Documentation
- **[Code Samples](./04-code-samples.md)**: Complete implementation code for all components
- **[Configuration Reference](./05-configuration-reference.md)**: Configuration options and collector setup
- **[Implementation Phases](./06-implementation-phases.md)**: Detailed timeline and milestones
---
## 3.9 Code Intrusiveness Assessment
> **TxQ** = Transaction Queue
This section provides a detailed assessment of how intrusive the OpenTelemetry integration is to the existing rippled codebase.
### 3.9.1 Files Modified Summary
| Component | Files Modified | Lines Added | Lines Changed | Architectural Impact |
| --------------------- | -------------- | ----------- | ------------- | -------------------- |
| **Core Telemetry** | 5 new files | ~800 | 0 | None (new module) |
| **Application Init** | 2 files | ~30 | ~5 | Minimal |
| **RPC Layer** | 3 files | ~80 | ~20 | Minimal |
| **Transaction Relay** | 4 files | ~120 | ~40 | Low |
| **Consensus** | 3 files | ~100 | ~30 | Low-Medium |
| **Protocol Buffers** | 1 file | ~25 | 0 | Low |
| **CMake/Build** | 3 files | ~50 | ~10 | Minimal |
| **PathFinding** | 2 | ~80 | ~5 | Minimal |
| **TxQ/Fee** | 2 | ~60 | ~5 | Minimal |
| **Validator/Amend** | 3 | ~40 | ~5 | Minimal |
| **Total** | **~28 files** | **~1,490** | **~120** | **Low** |
### 3.9.2 Detailed File Impact
```mermaid
pie title Code Changes by Component
"New Telemetry Module" : 800
"Transaction Relay" : 160
"Consensus" : 130
"RPC Layer" : 100
"PathFinding" : 80
"TxQ/Fee" : 60
"Validator/Amendment" : 40
"Application Init" : 35
"Protocol Buffers" : 25
"Build System" : 60
```
#### New Files (No Impact on Existing Code)
| File | Lines | Purpose |
| ---------------------------------------------- | ----- | -------------------- |
| `include/xrpl/telemetry/Telemetry.h` | ~160 | Main interface |
| `include/xrpl/telemetry/SpanGuard.h` | ~120 | RAII wrapper |
| `include/xrpl/telemetry/TraceContext.h` | ~80 | Context propagation |
| `src/xrpld/telemetry/TracingInstrumentation.h` | ~60 | Macros |
| `src/libxrpl/telemetry/Telemetry.cpp` | ~200 | Implementation |
| `src/libxrpl/telemetry/TelemetryConfig.cpp` | ~60 | Config parsing |
| `src/libxrpl/telemetry/NullTelemetry.cpp` | ~40 | No-op implementation |
#### Modified Files (Existing Rippled Code)
| File | Lines Added | Lines Changed | Risk Level |
| ------------------------------------------------- | ----------- | ------------- | ---------- |
| `src/xrpld/app/main/Application.cpp` | ~15 | ~3 | Low |
| `include/xrpl/app/main/Application.h` | ~5 | ~2 | Low |
| `src/xrpld/rpc/detail/ServerHandler.cpp` | ~40 | ~10 | Low |
| `src/xrpld/rpc/handlers/*.cpp` | ~30 | ~8 | Low |
| `src/xrpld/overlay/detail/PeerImp.cpp` | ~60 | ~15 | Medium |
| `src/xrpld/overlay/detail/OverlayImpl.cpp` | ~30 | ~10 | Medium |
| `src/xrpld/app/consensus/RCLConsensus.cpp` | ~50 | ~15 | Medium |
| `src/xrpld/app/consensus/RCLConsensusAdaptor.cpp` | ~40 | ~12 | Medium |
| `src/xrpld/core/JobQueue.cpp` | ~20 | ~5 | Low |
| `src/xrpld/app/paths/PathRequest.cpp` | ~40 | ~3 | Low |
| `src/xrpld/app/paths/Pathfinder.cpp` | ~40 | ~2 | Low |
| `src/xrpld/app/misc/TxQ.cpp` | ~40 | ~3 | Low |
| `src/xrpld/app/main/LoadManager.cpp` | ~20 | ~2 | Low |
| `src/xrpld/app/misc/ValidatorList.cpp` | ~20 | ~2 | Low |
| `src/xrpld/app/misc/AmendmentTable.cpp` | ~10 | ~2 | Low |
| `src/xrpld/app/misc/Manifest.cpp` | ~10 | ~1 | Low |
| `src/xrpld/shamap/SHAMap.cpp` | ~20 | ~3 | Low |
| `src/xrpld/overlay/detail/ripple.proto` | ~25 | 0 | Low |
| `CMakeLists.txt` | ~40 | ~8 | Low |
| `cmake/FindOpenTelemetry.cmake` | ~50 | 0 | None (new) |
### 3.9.3 Risk Assessment by Component
<div align="center">
**Do First** ↖ ↗ **Plan Carefully**
```mermaid
quadrantChart
title Code Intrusiveness Risk Matrix
x-axis Low Risk --> High Risk
y-axis Low Value --> High Value
RPC Tracing: [0.2, 0.55]
Transaction Relay: [0.55, 0.85]
Consensus Tracing: [0.75, 0.92]
Peer Message Tracing: [0.85, 0.35]
JobQueue Context: [0.3, 0.42]
Ledger Acquisition: [0.48, 0.65]
PathFinding: [0.38, 0.72]
TxQ and Fees: [0.25, 0.62]
Validator Mgmt: [0.15, 0.35]
```
**Optional** ↙ ↘ **Avoid**
</div>
#### Risk Level Definitions
| Risk Level | Definition | Mitigation |
| ---------- | ---------------------------------------------------------------- | ---------------------------------- |
| **Low** | Additive changes only; no modification to existing logic | Standard code review |
| **Medium** | Minor modifications to existing functions; clear boundaries | Comprehensive unit tests |
| **High** | Changes to core logic or data structures; potential side effects | Integration tests + staged rollout |
### 3.9.4 Architectural Impact Assessment
| Aspect | Impact | Justification |
| -------------------- | ------- | -------------------------------------------------------------------------------- |
| **Data Flow** | Minimal | Read-only instrumentation; no modification to consensus or transaction data flow |
| **Threading Model** | Minimal | Context propagation uses thread-local storage (standard OTel pattern) |
| **Memory Model** | Low | Bounded queues prevent unbounded growth; RAII ensures cleanup |
| **Network Protocol** | Low | Optional fields in protobuf (high field numbers); backward compatible |
| **Configuration** | None | New config section; existing configs unaffected |
| **Build System** | Low | Optional CMake flag; builds work without OpenTelemetry |
| **Dependencies** | Low | OpenTelemetry SDK is optional; null implementation when disabled |
### 3.9.5 Backward Compatibility
| Compatibility | Status | Notes |
| --------------- | ------- | ----------------------------------------------------- |
| **Config File** | ✅ Full | New `[telemetry]` section is optional |
| **Protocol** | ✅ Full | Optional protobuf fields with high field numbers |
| **Build** | ✅ Full | `XRPL_ENABLE_TELEMETRY=OFF` produces identical binary |
| **Runtime** | ✅ Full | `enabled=0` produces zero overhead |
| **API** | ✅ Full | No changes to public RPC or P2P APIs |
### 3.9.6 Rollback Strategy
If issues are discovered after deployment:
1. **Immediate**: Set `enabled=0` in config and restart (zero code change)
2. **Quick**: Rebuild with `XRPL_ENABLE_TELEMETRY=OFF`
3. **Complete**: Revert telemetry commits (clean separation makes this easy)
### 3.9.7 Code Change Examples
**Minimal RPC Instrumentation (Low Intrusiveness):**
```cpp
// Before
void ServerHandler::onRequest(...) {
auto result = processRequest(req);
send(result);
}
// After (only ~10 lines added)
void ServerHandler::onRequest(...) {
XRPL_TRACE_RPC(app_.getTelemetry(), "rpc.request"); // +1 line
XRPL_TRACE_SET_ATTR("xrpl.rpc.command", command); // +1 line
auto result = processRequest(req);
XRPL_TRACE_SET_ATTR("xrpl.rpc.status", status); // +1 line
send(result);
}
```
**Consensus Instrumentation (Medium Intrusiveness):**
```cpp
// Before
void RCLConsensusAdaptor::startRound(...) {
// ... existing logic
}
// After (context storage required)
void RCLConsensusAdaptor::startRound(...) {
XRPL_TRACE_CONSENSUS(app_.getTelemetry(), "consensus.round");
XRPL_TRACE_SET_ATTR("xrpl.consensus.ledger.seq", seq);
// Store context for child spans in phase transitions
currentRoundContext_ = _xrpl_guard_->context(); // New member variable
// ... existing logic unchanged
}
```
---
_Previous: [Design Decisions](./02-design-decisions.md)_ | _Next: [Code Samples](./04-code-samples.md)_ | _Back to: [Overview](./OpenTelemetryPlan.md)_

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# Configuration Reference
> **Parent Document**: [OpenTelemetryPlan.md](./OpenTelemetryPlan.md)
> **Related**: [Code Samples](./04-code-samples.md) | [Implementation Phases](./06-implementation-phases.md)
---
## 5.1 rippled Configuration
> **OTLP** = OpenTelemetry Protocol | **TxQ** = Transaction Queue
### 5.1.1 Configuration File Section
Add to `cfg/xrpld-example.cfg`:
```ini
# ═══════════════════════════════════════════════════════════════════════════════
# TELEMETRY (OpenTelemetry Distributed Tracing)
# ═══════════════════════════════════════════════════════════════════════════════
#
# Enables distributed tracing for transaction flow, consensus, and RPC calls.
# Traces are exported to an OpenTelemetry Collector using OTLP protocol.
#
# [telemetry]
#
# # Enable/disable telemetry (default: 0 = disabled)
# enabled=1
#
# # Exporter type: "otlp_grpc" (default), "otlp_http", or "none"
# exporter=otlp_grpc
#
# # OTLP endpoint (default: localhost:4317 for gRPC, localhost:4318 for HTTP)
# endpoint=localhost:4317
#
# # Use TLS for exporter connection (default: 0)
# use_tls=0
#
# # Path to CA certificate for TLS (optional)
# # tls_ca_cert=/path/to/ca.crt
#
# # Sampling ratio: 0.0-1.0 (default: 1.0 = 100% sampling)
# # Use lower values in production to reduce overhead
# # Default: 1.0 (all traces). For production deployments with high
# # throughput, 0.1 (10%) is recommended to reduce overhead.
# # See Section 7.4.2 for sampling strategy details.
# sampling_ratio=0.1
#
# # Batch processor settings
# batch_size=512 # Spans per batch (default: 512)
# batch_delay_ms=5000 # Max delay before sending batch (default: 5000)
# max_queue_size=2048 # Max queued spans (default: 2048)
#
# # Component-specific tracing (default: all enabled except peer)
# trace_transactions=1 # Transaction relay and processing
# trace_consensus=1 # Consensus rounds and proposals
# trace_rpc=1 # RPC request handling
# trace_peer=0 # Peer messages (high volume, disabled by default)
# trace_ledger=1 # Ledger acquisition and building
# trace_pathfind=1 # Path computation (can be expensive)
# trace_txq=1 # Transaction queue and fee escalation
# trace_validator=0 # Validator list and manifest updates (low volume)
# trace_amendment=0 # Amendment voting (very low volume)
#
# # Service identification (automatically detected if not specified)
# # service_name=rippled
# # service_instance_id=<node_public_key>
[telemetry]
enabled=0
```
### 5.1.2 Configuration Options Summary
| Option | Type | Default | Description |
| --------------------- | ------ | ---------------- | ----------------------------------------- |
| `enabled` | bool | `false` | Enable/disable telemetry |
| `exporter` | string | `"otlp_grpc"` | Exporter type: otlp_grpc, otlp_http, none |
| `endpoint` | string | `localhost:4317` | OTLP collector endpoint |
| `use_tls` | bool | `false` | Enable TLS for exporter connection |
| `tls_ca_cert` | string | `""` | Path to CA certificate file |
| `sampling_ratio` | float | `1.0` | Sampling ratio (0.0-1.0) |
| `batch_size` | uint | `512` | Spans per export batch |
| `batch_delay_ms` | uint | `5000` | Max delay before sending batch (ms) |
| `max_queue_size` | uint | `2048` | Maximum queued spans |
| `trace_transactions` | bool | `true` | Enable transaction tracing |
| `trace_consensus` | bool | `true` | Enable consensus tracing |
| `trace_rpc` | bool | `true` | Enable RPC tracing |
| `trace_peer` | bool | `false` | Enable peer message tracing (high volume) |
| `trace_ledger` | bool | `true` | Enable ledger tracing |
| `trace_pathfind` | bool | `true` | Enable path computation tracing |
| `trace_txq` | bool | `true` | Enable transaction queue tracing |
| `trace_validator` | bool | `false` | Enable validator list/manifest tracing |
| `trace_amendment` | bool | `false` | Enable amendment voting tracing |
| `service_name` | string | `"rippled"` | Service name for traces |
| `service_instance_id` | string | `<node_pubkey>` | Instance identifier |
---
## 5.2 Configuration Parser
> **TxQ** = Transaction Queue
```cpp
// src/libxrpl/telemetry/TelemetryConfig.cpp
#include <xrpl/telemetry/Telemetry.h>
#include <xrpl/basics/Log.h>
namespace xrpl {
namespace telemetry {
Telemetry::Setup
setup_Telemetry(
Section const& section,
std::string const& nodePublicKey,
std::string const& version)
{
Telemetry::Setup setup;
// Basic settings
setup.enabled = section.value_or("enabled", false);
setup.serviceName = section.value_or("service_name", "rippled");
setup.serviceVersion = version;
setup.serviceInstanceId = section.value_or(
"service_instance_id", nodePublicKey);
// Exporter settings
setup.exporterType = section.value_or("exporter", "otlp_grpc");
if (setup.exporterType == "otlp_grpc")
setup.exporterEndpoint = section.value_or("endpoint", "localhost:4317");
else if (setup.exporterType == "otlp_http")
setup.exporterEndpoint = section.value_or("endpoint", "localhost:4318");
setup.useTls = section.value_or("use_tls", false);
setup.tlsCertPath = section.value_or("tls_ca_cert", "");
// Sampling
setup.samplingRatio = section.value_or("sampling_ratio", 1.0);
if (setup.samplingRatio < 0.0 || setup.samplingRatio > 1.0)
{
Throw<std::runtime_error>(
"telemetry.sampling_ratio must be between 0.0 and 1.0");
}
// Batch processor
setup.batchSize = section.value_or("batch_size", 512u);
setup.batchDelay = std::chrono::milliseconds{
section.value_or("batch_delay_ms", 5000u)};
setup.maxQueueSize = section.value_or("max_queue_size", 2048u);
// Component filtering
setup.traceTransactions = section.value_or("trace_transactions", true);
setup.traceConsensus = section.value_or("trace_consensus", true);
setup.traceRpc = section.value_or("trace_rpc", true);
setup.tracePeer = section.value_or("trace_peer", false);
setup.traceLedger = section.value_or("trace_ledger", true);
setup.tracePathfind = section.value_or("trace_pathfind", true);
setup.traceTxQ = section.value_or("trace_txq", true);
setup.traceValidator = section.value_or("trace_validator", false);
setup.traceAmendment = section.value_or("trace_amendment", false);
return setup;
}
} // namespace telemetry
} // namespace xrpl
```
---
## 5.3 Application Integration
### 5.3.1 ApplicationImp Changes
```cpp
// src/xrpld/app/main/Application.cpp (modified)
#include <xrpl/telemetry/Telemetry.h>
class ApplicationImp : public Application
{
// ... existing members ...
// Telemetry (must be constructed early, destroyed late)
std::unique_ptr<telemetry::Telemetry> telemetry_;
public:
ApplicationImp(...)
{
// Initialize telemetry early (before other components)
auto telemetrySection = config_->section("telemetry");
auto telemetrySetup = telemetry::setup_Telemetry(
telemetrySection,
toBase58(TokenType::NodePublic, nodeIdentity_.publicKey()),
BuildInfo::getVersionString());
// Set network attributes
telemetrySetup.networkId = config_->NETWORK_ID;
telemetrySetup.networkType = [&]() {
if (config_->NETWORK_ID == 0) return "mainnet";
if (config_->NETWORK_ID == 1) return "testnet";
if (config_->NETWORK_ID == 2) return "devnet";
return "custom";
}();
telemetry_ = telemetry::make_Telemetry(
telemetrySetup,
logs_->journal("Telemetry"));
// ... rest of initialization ...
}
void start() override
{
// Start telemetry first
if (telemetry_)
telemetry_->start();
// ... existing start code ...
}
void stop() override
{
// ... existing stop code ...
// Stop telemetry last (to capture shutdown spans)
if (telemetry_)
telemetry_->stop();
}
telemetry::Telemetry& getTelemetry() override
{
assert(telemetry_);
return *telemetry_;
}
};
```
### 5.3.2 Application Interface Addition
```cpp
// include/xrpl/app/main/Application.h (modified)
namespace telemetry { class Telemetry; }
class Application
{
public:
// ... existing virtual methods ...
/** Get the telemetry system for distributed tracing */
virtual telemetry::Telemetry& getTelemetry() = 0;
};
```
---
## 5.4 CMake Integration
> **OTLP** = OpenTelemetry Protocol
### 5.4.1 Find OpenTelemetry Module
```cmake
# cmake/FindOpenTelemetry.cmake
# Find OpenTelemetry C++ SDK
#
# This module defines:
# OpenTelemetry_FOUND - System has OpenTelemetry
# OpenTelemetry::api - API library target
# OpenTelemetry::sdk - SDK library target
# OpenTelemetry::otlp_grpc_exporter - OTLP gRPC exporter target
# OpenTelemetry::otlp_http_exporter - OTLP HTTP exporter target
find_package(opentelemetry-cpp CONFIG QUIET)
if(opentelemetry-cpp_FOUND)
set(OpenTelemetry_FOUND TRUE)
# Create imported targets if not already created by config
if(NOT TARGET OpenTelemetry::api)
add_library(OpenTelemetry::api ALIAS opentelemetry-cpp::api)
endif()
if(NOT TARGET OpenTelemetry::sdk)
add_library(OpenTelemetry::sdk ALIAS opentelemetry-cpp::sdk)
endif()
if(NOT TARGET OpenTelemetry::otlp_grpc_exporter)
add_library(OpenTelemetry::otlp_grpc_exporter ALIAS
opentelemetry-cpp::otlp_grpc_exporter)
endif()
else()
# Try pkg-config fallback
find_package(PkgConfig QUIET)
if(PKG_CONFIG_FOUND)
pkg_check_modules(OTEL opentelemetry-cpp QUIET)
if(OTEL_FOUND)
set(OpenTelemetry_FOUND TRUE)
# Create imported targets from pkg-config
add_library(OpenTelemetry::api INTERFACE IMPORTED)
target_include_directories(OpenTelemetry::api INTERFACE
${OTEL_INCLUDE_DIRS})
endif()
endif()
endif()
include(FindPackageHandleStandardArgs)
find_package_handle_standard_args(OpenTelemetry
REQUIRED_VARS OpenTelemetry_FOUND)
```
### 5.4.2 CMakeLists.txt Changes
```cmake
# CMakeLists.txt (additions)
# ═══════════════════════════════════════════════════════════════════════════════
# TELEMETRY OPTIONS
# ═══════════════════════════════════════════════════════════════════════════════
option(XRPL_ENABLE_TELEMETRY
"Enable OpenTelemetry distributed tracing support" OFF)
if(XRPL_ENABLE_TELEMETRY)
find_package(OpenTelemetry REQUIRED)
# Define compile-time flag
add_compile_definitions(XRPL_ENABLE_TELEMETRY)
message(STATUS "OpenTelemetry tracing: ENABLED")
else()
message(STATUS "OpenTelemetry tracing: DISABLED")
endif()
# ═══════════════════════════════════════════════════════════════════════════════
# TELEMETRY LIBRARY
# ═══════════════════════════════════════════════════════════════════════════════
if(XRPL_ENABLE_TELEMETRY)
add_library(xrpl_telemetry
src/libxrpl/telemetry/Telemetry.cpp
src/libxrpl/telemetry/TelemetryConfig.cpp
src/libxrpl/telemetry/TraceContext.cpp
)
target_include_directories(xrpl_telemetry
PUBLIC
${CMAKE_CURRENT_SOURCE_DIR}/include
)
target_link_libraries(xrpl_telemetry
PUBLIC
OpenTelemetry::api
OpenTelemetry::sdk
OpenTelemetry::otlp_grpc_exporter
PRIVATE
xrpl_basics
)
# Add to main library dependencies
target_link_libraries(xrpld PRIVATE xrpl_telemetry)
else()
# Create null implementation library
add_library(xrpl_telemetry
src/libxrpl/telemetry/NullTelemetry.cpp
)
target_include_directories(xrpl_telemetry
PUBLIC ${CMAKE_CURRENT_SOURCE_DIR}/include
)
endif()
```
---
## 5.5 OpenTelemetry Collector Configuration
> **OTLP** = OpenTelemetry Protocol | **APM** = Application Performance Monitoring
### 5.5.1 Development Configuration
```yaml
# otel-collector-dev.yaml
# Minimal configuration for local development
receivers:
otlp:
protocols:
grpc:
endpoint: 0.0.0.0:4317
http:
endpoint: 0.0.0.0:4318
processors:
batch:
timeout: 1s
send_batch_size: 100
exporters:
# Console output for debugging
logging:
verbosity: detailed
sampling_initial: 5
sampling_thereafter: 200
# Tempo for trace visualization
otlp/tempo:
endpoint: tempo:4317
tls:
insecure: true
# Grafana Tempo for trace storage
otlp/tempo:
endpoint: tempo:4317
tls:
insecure: true
service:
pipelines:
traces:
receivers: [otlp]
processors: [batch]
exporters: [logging, jaeger, otlp/tempo]
```
### 5.5.2 Production Configuration
```yaml
# otel-collector-prod.yaml
# Production configuration with filtering, sampling, and multiple backends
receivers:
otlp:
protocols:
grpc:
endpoint: 0.0.0.0:4317
tls:
cert_file: /etc/otel/server.crt
key_file: /etc/otel/server.key
ca_file: /etc/otel/ca.crt
processors:
# Memory limiter to prevent OOM
memory_limiter:
check_interval: 1s
limit_mib: 1000
spike_limit_mib: 200
# Batch processing for efficiency
batch:
timeout: 5s
send_batch_size: 512
send_batch_max_size: 1024
# Tail-based sampling (keep errors and slow traces)
tail_sampling:
decision_wait: 10s
num_traces: 100000
expected_new_traces_per_sec: 1000
policies:
# Always keep error traces
- name: errors
type: status_code
status_code:
status_codes: [ERROR]
# Keep slow consensus rounds (>5s)
- name: slow-consensus
type: latency
latency:
threshold_ms: 5000
# Keep slow RPC requests (>1s)
- name: slow-rpc
type: and
and:
and_sub_policy:
- name: rpc-spans
type: string_attribute
string_attribute:
key: xrpl.rpc.command
values: [".*"]
enabled_regex_matching: true
- name: latency
type: latency
latency:
threshold_ms: 1000
# Probabilistic sampling for the rest
- name: probabilistic
type: probabilistic
probabilistic:
sampling_percentage: 10
# Attribute processing
attributes:
actions:
# Hash sensitive data
- key: xrpl.tx.account
action: hash
# Add deployment info
- key: deployment.environment
value: production
action: upsert
exporters:
# Grafana Tempo for long-term storage
otlp/tempo:
endpoint: tempo.monitoring:4317
tls:
insecure: false
ca_file: /etc/otel/tempo-ca.crt
# Elastic APM for correlation with logs
otlp/elastic:
endpoint: apm.elastic:8200
headers:
Authorization: "Bearer ${ELASTIC_APM_TOKEN}"
extensions:
health_check:
endpoint: 0.0.0.0:13133
zpages:
endpoint: 0.0.0.0:55679
service:
extensions: [health_check, zpages]
pipelines:
traces:
receivers: [otlp]
processors: [memory_limiter, tail_sampling, attributes, batch]
exporters: [otlp/tempo, otlp/elastic]
```
---
## 5.6 Docker Compose Development Environment
> **OTLP** = OpenTelemetry Protocol
```yaml
# docker-compose-telemetry.yaml
version: "3.8"
services:
# OpenTelemetry Collector
otel-collector:
image: otel/opentelemetry-collector-contrib:0.92.0
container_name: otel-collector
command: ["--config=/etc/otel-collector-config.yaml"]
volumes:
- ./otel-collector-dev.yaml:/etc/otel-collector-config.yaml:ro
ports:
- "4317:4317" # OTLP gRPC
- "4318:4318" # OTLP HTTP
- "13133:13133" # Health check
depends_on:
- tempo
# Tempo for trace visualization
tempo:
image: grafana/tempo:2.6.1
container_name: tempo
ports:
- "3200:3200" # Tempo HTTP API
- "4317" # OTLP gRPC (internal)
# Grafana Tempo for trace storage (recommended for production)
tempo:
image: grafana/tempo:2.7.2
container_name: tempo
command: ["-config.file=/etc/tempo.yaml"]
volumes:
- ./tempo.yaml:/etc/tempo.yaml:ro
- tempo-data:/var/tempo
ports:
- "3200:3200" # HTTP API
# Grafana for dashboards
grafana:
image: grafana/grafana:10.2.3
container_name: grafana
environment:
- GF_AUTH_ANONYMOUS_ENABLED=true
- GF_AUTH_ANONYMOUS_ORG_ROLE=Admin
volumes:
- ./grafana/provisioning:/etc/grafana/provisioning:ro
- ./grafana/dashboards:/var/lib/grafana/dashboards:ro
ports:
- "3000:3000"
depends_on:
- jaeger
- tempo
# Prometheus for metrics (optional, for correlation)
prometheus:
image: prom/prometheus:v2.48.1
container_name: prometheus
volumes:
- ./prometheus.yaml:/etc/prometheus/prometheus.yml:ro
ports:
- "9090:9090"
networks:
default:
name: rippled-telemetry
```
---
## 5.7 Configuration Architecture
> **OTLP** = OpenTelemetry Protocol
```mermaid
flowchart TB
subgraph config["Configuration Sources"]
cfgFile["xrpld.cfg<br/>[telemetry] section"]
cmake["CMake<br/>XRPL_ENABLE_TELEMETRY"]
end
subgraph init["Initialization"]
parse["setup_Telemetry()"]
factory["make_Telemetry()"]
end
subgraph runtime["Runtime Components"]
tracer["TracerProvider"]
exporter["OTLP Exporter"]
processor["BatchProcessor"]
end
subgraph collector["Collector Pipeline"]
recv["Receivers"]
proc["Processors"]
exp["Exporters"]
end
cfgFile --> parse
cmake -->|"compile flag"| parse
parse --> factory
factory --> tracer
tracer --> processor
processor --> exporter
exporter -->|"OTLP"| recv
recv --> proc
proc --> exp
style config fill:#e3f2fd,stroke:#1976d2
style runtime fill:#e8f5e9,stroke:#388e3c
style collector fill:#fff3e0,stroke:#ff9800
```
**Reading the diagram:**
- **Configuration Sources**: `xrpld.cfg` provides runtime settings (endpoint, sampling) while the CMake flag controls whether telemetry is compiled in at all.
- **Initialization**: `setup_Telemetry()` parses config values, then `make_Telemetry()` constructs the provider, processor, and exporter objects.
- **Runtime Components**: The `TracerProvider` creates spans, the `BatchProcessor` buffers them, and the `OTLP Exporter` serializes and sends them over the wire.
- **OTLP arrow to Collector**: Trace data leaves the rippled process via OTLP (gRPC or HTTP) and enters the external Collector pipeline.
- **Collector Pipeline**: `Receivers` ingest OTLP data, `Processors` apply sampling/filtering/enrichment, and `Exporters` forward traces to storage backends (Tempo, etc.).
---
## 5.8 Grafana Integration
> **APM** = Application Performance Monitoring
Step-by-step instructions for integrating rippled traces with Grafana.
### 5.8.1 Data Source Configuration
#### Tempo (Recommended)
```yaml
# grafana/provisioning/datasources/tempo.yaml
apiVersion: 1
datasources:
- name: Tempo
type: tempo
access: proxy
url: http://tempo:3200
jsonData:
httpMethod: GET
tracesToLogs:
datasourceUid: loki
tags: ["service.name", "xrpl.tx.hash"]
mappedTags: [{ key: "trace_id", value: "traceID" }]
mapTagNamesEnabled: true
filterByTraceID: true
serviceMap:
datasourceUid: prometheus
nodeGraph:
enabled: true
search:
hide: false
lokiSearch:
datasourceUid: loki
```
#### Elastic APM
```yaml
# grafana/provisioning/datasources/elastic-apm.yaml
apiVersion: 1
datasources:
- name: Elasticsearch-APM
type: elasticsearch
access: proxy
url: http://elasticsearch:9200
database: "apm-*"
jsonData:
esVersion: "8.0.0"
timeField: "@timestamp"
logMessageField: message
logLevelField: log.level
```
### 5.8.2 Dashboard Provisioning
```yaml
# grafana/provisioning/dashboards/dashboards.yaml
apiVersion: 1
providers:
- name: "rippled-dashboards"
orgId: 1
folder: "rippled"
folderUid: "rippled"
type: file
disableDeletion: false
updateIntervalSeconds: 30
options:
path: /var/lib/grafana/dashboards/rippled
```
### 5.8.3 Example Dashboard: RPC Performance
```json
{
"title": "rippled RPC Performance",
"uid": "rippled-rpc-performance",
"panels": [
{
"title": "RPC Latency by Command",
"type": "heatmap",
"datasource": "Tempo",
"targets": [
{
"queryType": "traceql",
"query": "{resource.service.name=\"rippled\" && span.xrpl.rpc.command != \"\"} | histogram_over_time(duration) by (span.xrpl.rpc.command)"
}
],
"gridPos": { "h": 8, "w": 12, "x": 0, "y": 0 }
},
{
"title": "RPC Error Rate",
"type": "timeseries",
"datasource": "Tempo",
"targets": [
{
"queryType": "traceql",
"query": "{resource.service.name=\"rippled\" && status.code=error} | rate() by (span.xrpl.rpc.command)"
}
],
"gridPos": { "h": 8, "w": 12, "x": 12, "y": 0 }
},
{
"title": "Top 10 Slowest RPC Commands",
"type": "table",
"datasource": "Tempo",
"targets": [
{
"queryType": "traceql",
"query": "{resource.service.name=\"rippled\" && span.xrpl.rpc.command != \"\"} | avg(duration) by (span.xrpl.rpc.command) | topk(10)"
}
],
"gridPos": { "h": 8, "w": 24, "x": 0, "y": 8 }
},
{
"title": "Recent Traces",
"type": "table",
"datasource": "Tempo",
"targets": [
{
"queryType": "traceql",
"query": "{resource.service.name=\"rippled\"}"
}
],
"gridPos": { "h": 8, "w": 24, "x": 0, "y": 16 }
}
]
}
```
### 5.8.4 Example Dashboard: Transaction Tracing
```json
{
"title": "rippled Transaction Tracing",
"uid": "rippled-tx-tracing",
"panels": [
{
"title": "Transaction Throughput",
"type": "stat",
"datasource": "Tempo",
"targets": [
{
"queryType": "traceql",
"query": "{resource.service.name=\"rippled\" && name=\"tx.receive\"} | rate()"
}
],
"gridPos": { "h": 4, "w": 6, "x": 0, "y": 0 }
},
{
"title": "Cross-Node Relay Count",
"type": "timeseries",
"datasource": "Tempo",
"targets": [
{
"queryType": "traceql",
"query": "{resource.service.name=\"rippled\" && name=\"tx.relay\"} | avg(span.xrpl.tx.relay_count)"
}
],
"gridPos": { "h": 8, "w": 12, "x": 0, "y": 4 }
},
{
"title": "Transaction Validation Errors",
"type": "table",
"datasource": "Tempo",
"targets": [
{
"queryType": "traceql",
"query": "{resource.service.name=\"rippled\" && name=\"tx.validate\" && status.code=error}"
}
],
"gridPos": { "h": 8, "w": 12, "x": 12, "y": 4 }
}
]
}
```
### 5.8.5 TraceQL Query Examples
Common queries for rippled traces:
```
# Find all traces for a specific transaction hash
{resource.service.name="rippled" && span.xrpl.tx.hash="ABC123..."}
# Find slow RPC commands (>100ms)
{resource.service.name="rippled" && name=~"rpc.command.*"} | duration > 100ms
# Find consensus rounds taking >5 seconds
{resource.service.name="rippled" && name="consensus.round"} | duration > 5s
# Find failed transactions with error details
{resource.service.name="rippled" && name="tx.validate" && status.code=error}
# Find transactions relayed to many peers
{resource.service.name="rippled" && name="tx.relay"} | span.xrpl.tx.relay_count > 10
# Compare latency across nodes
{resource.service.name="rippled" && name="rpc.command.account_info"} | avg(duration) by (resource.service.instance.id)
```
### 5.8.6 Correlation with PerfLog
To correlate OpenTelemetry traces with existing PerfLog data:
**Step 1: Configure Loki to ingest PerfLog**
```yaml
# promtail-config.yaml
scrape_configs:
- job_name: rippled-perflog
static_configs:
- targets:
- localhost
labels:
job: rippled
__path__: /var/log/rippled/perf*.log
pipeline_stages:
- json:
expressions:
trace_id: trace_id
ledger_seq: ledger_seq
tx_hash: tx_hash
- labels:
trace_id:
ledger_seq:
tx_hash:
```
**Step 2: Add trace_id to PerfLog entries**
Modify PerfLog to include trace_id when available:
```cpp
// In PerfLog output, add trace_id from current span context
void logPerf(Json::Value& entry) {
auto span = opentelemetry::trace::GetSpan(
opentelemetry::context::RuntimeContext::GetCurrent());
if (span && span->GetContext().IsValid()) {
char traceIdHex[33];
span->GetContext().trace_id().ToLowerBase16(traceIdHex);
entry["trace_id"] = std::string(traceIdHex, 32);
}
// ... existing logging
}
```
**Step 3: Configure Grafana trace-to-logs link**
In Tempo data source configuration, set up the derived field:
```yaml
jsonData:
tracesToLogs:
datasourceUid: loki
tags: ["trace_id", "xrpl.tx.hash"]
filterByTraceID: true
filterBySpanID: false
```
### 5.8.7 Correlation with Insight/StatsD Metrics
To correlate traces with existing Beast Insight metrics:
**Step 1: Export Insight metrics to Prometheus**
```yaml
# prometheus.yaml
scrape_configs:
- job_name: "rippled-statsd"
static_configs:
- targets: ["statsd-exporter:9102"]
```
**Step 2: Add exemplars to metrics**
OpenTelemetry SDK automatically adds exemplars (trace IDs) to metrics when using the Prometheus exporter. This links metrics spikes to specific traces.
**Step 3: Configure Grafana metric-to-trace link**
```yaml
# In Prometheus data source
jsonData:
exemplarTraceIdDestinations:
- name: trace_id
datasourceUid: tempo
```
**Step 4: Dashboard panel with exemplars**
```json
{
"title": "RPC Latency with Trace Links",
"type": "timeseries",
"datasource": "Prometheus",
"targets": [
{
"expr": "histogram_quantile(0.99, rate(rippled_rpc_duration_seconds_bucket[5m]))",
"exemplar": true
}
]
}
```
This allows clicking on metric data points to jump directly to the related trace.
---
_Previous: [Code Samples](./04-code-samples.md)_ | _Next: [Implementation Phases](./06-implementation-phases.md)_ | _Back to: [Overview](./OpenTelemetryPlan.md)_

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@@ -0,0 +1,649 @@
# Implementation Phases
> **Parent Document**: [OpenTelemetryPlan.md](./OpenTelemetryPlan.md)
> **Related**: [Configuration Reference](./05-configuration-reference.md) | [Observability Backends](./07-observability-backends.md)
---
## 6.1 Phase Overview
> **TxQ** = Transaction Queue
```mermaid
gantt
title OpenTelemetry Implementation Timeline
dateFormat YYYY-MM-DD
axisFormat Week %W
section Phase 1
Core Infrastructure :p1, 2024-01-01, 2w
SDK Integration :p1a, 2024-01-01, 4d
Telemetry Interface :p1b, after p1a, 3d
Configuration & CMake :p1c, after p1b, 3d
Unit Tests :p1d, after p1c, 2d
Buffer & Integration :p1e, after p1d, 2d
section Phase 2
RPC Tracing :p2, after p1, 2w
HTTP Context Extraction :p2a, after p1, 2d
RPC Handler Instrumentation :p2b, after p2a, 4d
PathFinding Instrumentation :p2f, after p2b, 2d
TxQ Instrumentation :p2g, after p2f, 2d
WebSocket Support :p2c, after p2g, 2d
Integration Tests :p2d, after p2c, 2d
Buffer & Review :p2e, after p2d, 4d
section Phase 3
Transaction Tracing :p3, after p2, 2w
Protocol Buffer Extension :p3a, after p2, 2d
PeerImp Instrumentation :p3b, after p3a, 3d
Fee Escalation Instrumentation :p3f, after p3b, 2d
Relay Context Propagation :p3c, after p3f, 3d
Multi-node Tests :p3d, after p3c, 2d
Buffer & Review :p3e, after p3d, 4d
section Phase 4
Consensus Tracing :p4, after p3, 2w
Consensus Round Spans :p4a, after p3, 3d
Proposal Handling :p4b, after p4a, 3d
Validator List & Manifest Tracing :p4f, after p4b, 2d
Amendment Voting Tracing :p4g, after p4f, 2d
SHAMap Sync Tracing :p4h, after p4g, 2d
Validation Tests :p4c, after p4h, 4d
Buffer & Review :p4e, after p4c, 4d
section Phase 5
Documentation & Deploy :p5, after p4, 1w
```
---
## 6.2 Phase 1: Core Infrastructure (Weeks 1-2)
**Objective**: Establish foundational telemetry infrastructure
### Tasks
| Task | Description |
| ---- | ----------------------------------------------------- |
| 1.1 | Add OpenTelemetry C++ SDK to Conan/CMake |
| 1.2 | Implement `Telemetry` interface and factory |
| 1.3 | Implement `SpanGuard` RAII wrapper |
| 1.4 | Implement configuration parser |
| 1.5 | Integrate into `ApplicationImp` |
| 1.6 | Add conditional compilation (`XRPL_ENABLE_TELEMETRY`) |
| 1.7 | Create `NullTelemetry` no-op implementation |
| 1.8 | Unit tests for core infrastructure |
### Exit Criteria
- [ ] OpenTelemetry SDK compiles and links
- [ ] Telemetry can be enabled/disabled via config
- [ ] Basic span creation works
- [ ] No performance regression when disabled
- [ ] Unit tests passing
---
## 6.3 Phase 2: RPC Tracing (Weeks 3-4)
> **TxQ** = Transaction Queue
**Objective**: Complete tracing for all RPC operations
### Tasks
| Task | Description |
| ---- | -------------------------------------------------------------------------- |
| 2.1 | Implement W3C Trace Context HTTP header extraction |
| 2.2 | Instrument `ServerHandler::onRequest()` |
| 2.3 | Instrument `RPCHandler::doCommand()` |
| 2.4 | Add RPC-specific attributes |
| 2.5 | Instrument WebSocket handler |
| 2.6 | PathFinding instrumentation (`pathfind.request`, `pathfind.compute` spans) |
| 2.7 | TxQ instrumentation (`txq.enqueue`, `txq.apply` spans) |
| 2.8 | Integration tests for RPC tracing |
| 2.9 | Performance benchmarks |
| 2.10 | Documentation |
### Exit Criteria
- [ ] All RPC commands traced
- [ ] Trace context propagates from HTTP headers
- [ ] WebSocket and HTTP both instrumented
- [ ] <1ms overhead per RPC call
- [ ] Integration tests passing
---
## 6.4 Phase 3: Transaction Tracing (Weeks 5-6)
**Objective**: Trace transaction lifecycle across network
### Tasks
| Task | Description |
| ---- | ---------------------------------------------------- |
| 3.1 | Define `TraceContext` Protocol Buffer message |
| 3.2 | Implement protobuf context serialization |
| 3.3 | Instrument `PeerImp::handleTransaction()` |
| 3.4 | Instrument `NetworkOPs::submitTransaction()` |
| 3.5 | Instrument HashRouter integration |
| 3.6 | Fee escalation instrumentation (`fee.escalate` span) |
| 3.7 | Implement relay context propagation |
| 3.8 | Integration tests (multi-node) |
| 3.9 | Performance benchmarks |
### Exit Criteria
- [ ] Transaction traces span across nodes
- [ ] Trace context in Protocol Buffer messages
- [ ] HashRouter deduplication visible in traces
- [ ] Multi-node integration tests passing
- [ ] <5% overhead on transaction throughput
---
## 6.5 Phase 4: Consensus Tracing (Weeks 7-8)
**Objective**: Full observability into consensus rounds
### Tasks
| Task | Description |
| ---- | ---------------------------------------------- |
| 4.1 | Instrument `RCLConsensusAdaptor::startRound()` |
| 4.2 | Instrument phase transitions |
| 4.3 | Instrument proposal handling |
| 4.4 | Instrument validation handling |
| 4.5 | Add consensus-specific attributes |
| 4.6 | Correlate with transaction traces |
| 4.7 | Validator list and manifest tracing |
| 4.8 | Amendment voting tracing |
| 4.9 | SHAMap sync tracing |
| 4.10 | Multi-validator integration tests |
| 4.11 | Performance validation |
### Spans Produced
| Span Name | Location | Attributes |
| --------------------------- | ---------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `consensus.proposal.send` | `RCLConsensus.cpp:177` | `xrpl.consensus.round` |
| `consensus.ledger_close` | `RCLConsensus.cpp:282` | `xrpl.consensus.ledger.seq`, `xrpl.consensus.mode` |
| `consensus.accept` | `RCLConsensus.cpp:395` | `xrpl.consensus.proposers`, `xrpl.consensus.round_time_ms` |
| `consensus.accept.apply` | `RCLConsensus.cpp:521` | `xrpl.consensus.close_time`, `close_time_correct`, `close_resolution_ms`, `state`, `proposing`, `round_time_ms`, `ledger.seq`, `parent_close_time`, `close_time_self`, `close_time_vote_bins`, `resolution_direction` |
| `consensus.validation.send` | `RCLConsensus.cpp:753` | `xrpl.consensus.proposing` |
### Exit Criteria
- [x] Complete consensus round traces
- [x] Phase transitions visible
- [x] Proposals and validations traced
- [x] Close time agreement tracked (per `avCT_CONSENSUS_PCT`)
- [x] No impact on consensus timing
- [ ] Multi-validator test network validated
### Implementation Status — Phase 4a Complete
Phase 4a (establish-phase gap fill & cross-node correlation) adds:
- **Deterministic trace ID** derived from `previousLedger.id()` so all validators
in the same round share the same `trace_id` (switchable via
`consensus_trace_strategy` config: `"deterministic"` or `"attribute"`).
See [Configuration Reference](./05-configuration-reference.md) for full
configuration options. The `consensus_trace_strategy` option will be
documented in the configuration reference as part of Phase 4a implementation.
- **Round lifecycle spans**: `consensus.round` with round-to-round span links.
- **Establish phase**: `consensus.establish`, `consensus.update_positions` (with
`dispute.resolve` events), `consensus.check` (with threshold tracking).
- **Mode changes**: `consensus.mode_change` spans.
- **Validation**: `consensus.validation.send` with span link to round span
(thread-safe cross-thread access via `roundSpanContext_` snapshot).
- **Separation of concerns**: telemetry extracted to private helpers
(`startRoundTracing`, `createValidationSpan`, `startEstablishTracing`,
`updateEstablishTracing`, `endEstablishTracing`).
See [Phase4_taskList.md](./Phase4_taskList.md) for the full spec and implementation notes.
---
## 6.5a Phase 4a: Establish-Phase Gap Fill & Cross-Node Correlation
**Objective**: Fill tracing gaps in the establish phase and establish cross-node
correlation using deterministic trace IDs derived from `previousLedger.id()`.
**Approach**: Direct instrumentation in `Consensus.h`. Long-lived spans use
direct SpanGuard members; short-lived scoped spans use `XRPL_TRACE_*` macros.
### Tasks
| Task | Description | Effort | Risk |
| ---- | ------------------------------------------------ | ------ | ------ |
| 4a.0 | Prerequisites: extend SpanGuard & Telemetry APIs | 1d | Medium |
| 4a.1 | Adaptor `getTelemetry()` method | 0.5d | Low |
| 4a.2 | Switchable round span with deterministic traceID | 2d | High |
| 4a.3 | Span members in `Consensus.h` | 0.5d | Medium |
| 4a.4 | Instrument `phaseEstablish()` | 1d | Medium |
| 4a.5 | Instrument `updateOurPositions()` | 1d | Medium |
| 4a.6 | Instrument `haveConsensus()` (thresholds) | 1d | Medium |
| 4a.7 | Instrument mode changes | 0.5d | Low |
| 4a.8 | Reparent existing spans under round | 0.5d | Low |
| 4a.9 | Build verification and testing | 1d | Low |
**Total Effort**: 9 days
### Spans Produced
| Span Name | Location | Key Attributes |
| ---------------------------- | ------------------ | ---------------------------------------------------------------- |
| `consensus.round` | `RCLConsensus.cpp` | `round_id`, `ledger_id`, `ledger.seq`, `mode`; link prev round |
| `consensus.establish` | `Consensus.h` | `converge_percent`, `establish_count`, `proposers` |
| `consensus.update_positions` | `Consensus.h` | `disputes_count`, `converge_percent`, `proposers_agreed/total` |
| `consensus.check` | `Consensus.h` | `agree/disagree_count`, `threshold_percent`, `result` |
| `consensus.mode_change` | `RCLConsensus.cpp` | `mode.old`, `mode.new` |
### Exit Criteria
- [ ] Establish phase internals fully traced (disputes, convergence, thresholds)
- [ ] Cross-node correlation works via deterministic trace_id
- [ ] Strategy switchable via config (`deterministic` / `attribute`)
- [ ] Consecutive rounds linked via follows-from spans
- [ ] Build passes with telemetry ON and OFF
- [ ] No impact on consensus timing
See [Phase4_taskList.md](./Phase4_taskList.md) for full task details.
---
## 6.5b Phase 4b: Cross-Node Propagation (Future)
**Objective**: Wire `TraceContextPropagator` for P2P messages (proposals,
validations) to enable true distributed tracing between nodes.
**Status**: Design documented, NOT implemented. Protobuf fields (field 1001)
and `TraceContextPropagator` class exist. Wiring deferred until Phase 4a is
validated in a multi-node environment.
**Prerequisites**: Phase 4a complete and validated.
See [Phase4_taskList.md § Phase 4b](./Phase4_taskList.md) for full design.
---
## 6.6 Phase 5: Documentation & Deployment (Week 9)
**Objective**: Production readiness
### Tasks
| Task | Description |
| ---- | ----------------------------- |
| 5.1 | Operator runbook |
| 5.2 | Grafana dashboards |
| 5.3 | Alert definitions |
| 5.4 | Collector deployment examples |
| 5.5 | Developer documentation |
| 5.6 | Training materials |
| 5.7 | Final integration testing |
---
## 6.7 Risk Assessment
```mermaid
quadrantChart
title Risk Assessment Matrix
x-axis Low Impact --> High Impact
y-axis Low Likelihood --> High Likelihood
quadrant-1 Mitigate Immediately
quadrant-2 Plan Mitigation
quadrant-3 Accept Risk
quadrant-4 Monitor Closely
SDK Compat: [0.2, 0.18]
Protocol Chg: [0.75, 0.72]
Perf Overhead: [0.58, 0.42]
Context Prop: [0.4, 0.55]
Memory Leaks: [0.85, 0.25]
```
### Risk Details
| Risk | Likelihood | Impact | Mitigation |
| ------------------------------------ | ---------- | ------ | --------------------------------------- |
| Protocol changes break compatibility | Medium | High | Use high field numbers, optional fields |
| Performance overhead unacceptable | Medium | Medium | Sampling, conditional compilation |
| Context propagation complexity | Medium | Medium | Phased rollout, extensive testing |
| SDK compatibility issues | Low | Medium | Pin SDK version, fallback to no-op |
| Memory leaks in long-running nodes | Low | High | Memory profiling, bounded queues |
---
## 6.8 Success Metrics
| Metric | Target | Measurement |
| ------------------------ | -------------------------------------------------------------- | --------------------- |
| Trace coverage | >95% of transaction code paths (independent of sampling ratio) | Sampling verification |
| CPU overhead | <3% | Benchmark tests |
| Memory overhead | <10 MB | Memory profiling |
| Latency impact (p99) | <2% | Performance tests |
| Trace completeness | >99% spans with required attrs | Validation script |
| Cross-node trace linkage | >90% of multi-hop transactions | Integration tests |
---
## 6.9 Quick Wins and Crawl-Walk-Run Strategy
> **TxQ** = Transaction Queue
This section outlines a prioritized approach to maximize ROI with minimal initial investment.
### 6.9.1 Crawl-Walk-Run Overview
<div align="center">
```mermaid
flowchart TB
subgraph crawl["🐢 CRAWL (Week 1-2)"]
direction LR
c1[Core SDK Setup] ~~~ c2[RPC Tracing Only] ~~~ c3[PathFinding + TxQ Tracing] ~~~ c4[Single Node]
end
subgraph walk["🚶 WALK (Week 3-5)"]
direction LR
w1[Transaction Tracing] ~~~ w2[Fee Escalation Tracing] ~~~ w3[Cross-Node Context] ~~~ w4[Basic Dashboards]
end
subgraph run["🏃 RUN (Week 6-9)"]
direction LR
r1[Consensus Tracing] ~~~ r2[Validator, Amendment,<br/>SHAMap Tracing] ~~~ r3[Full Correlation] ~~~ r4[Production Deploy]
end
crawl --> walk --> run
style crawl fill:#1b5e20,stroke:#0d3d14,color:#fff
style walk fill:#bf360c,stroke:#8c2809,color:#fff
style run fill:#0d47a1,stroke:#082f6a,color:#fff
style c1 fill:#1b5e20,stroke:#0d3d14,color:#fff
style c2 fill:#1b5e20,stroke:#0d3d14,color:#fff
style c3 fill:#1b5e20,stroke:#0d3d14,color:#fff
style c4 fill:#1b5e20,stroke:#0d3d14,color:#fff
style w1 fill:#ffe0b2,stroke:#ffcc80,color:#1e293b
style w2 fill:#ffe0b2,stroke:#ffcc80,color:#1e293b
style w3 fill:#ffe0b2,stroke:#ffcc80,color:#1e293b
style w4 fill:#ffe0b2,stroke:#ffcc80,color:#1e293b
style r1 fill:#0d47a1,stroke:#082f6a,color:#fff
style r2 fill:#0d47a1,stroke:#082f6a,color:#fff
style r3 fill:#0d47a1,stroke:#082f6a,color:#fff
style r4 fill:#0d47a1,stroke:#082f6a,color:#fff
```
</div>
**Reading the diagram:**
- **CRAWL (Weeks 1-2)**: Minimal investment -- set up the SDK, instrument RPC and PathFinding/TxQ handlers, and verify on a single node. Delivers immediate latency visibility.
- **WALK (Weeks 3-5)**: Expand to transaction lifecycle tracing, fee escalation, cross-node context propagation, and basic Grafana dashboards. This is where distributed tracing starts working.
- **RUN (Weeks 6-9)**: Full consensus instrumentation, validator/amendment/SHAMap tracing, end-to-end correlation, and production deployment with sampling and alerting.
- **Arrows (crawl → walk → run)**: Each phase builds on the prior one; you cannot skip ahead because later phases depend on infrastructure established earlier.
### 6.9.2 Quick Wins (Immediate Value)
| Quick Win | Value | When to Deploy |
| ------------------------------ | ------ | -------------- |
| **RPC Command Tracing** | High | Week 2 |
| **RPC Latency Histograms** | High | Week 2 |
| **Error Rate Dashboard** | Medium | Week 2 |
| **Transaction Submit Tracing** | High | Week 3 |
| **Consensus Round Duration** | Medium | Week 6 |
### 6.9.3 CRAWL Phase (Weeks 1-2)
**Goal**: Get basic tracing working with minimal code changes.
**What You Get**:
- RPC request/response traces for all commands
- Latency breakdown per RPC command
- PathFinding and TxQ tracing (directly impacts RPC latency)
- Error visibility with stack traces
- Basic Grafana dashboard
**Code Changes**: ~15 lines in `ServerHandler.cpp`, ~40 lines in new telemetry module
**Why Start Here**:
- RPC is the lowest-risk, highest-visibility component
- PathFinding and TxQ are RPC-adjacent and directly affect latency
- Immediate value for debugging client issues
- No cross-node complexity
- Single file modification to existing code
### 6.9.4 WALK Phase (Weeks 3-5)
**Goal**: Add transaction lifecycle tracing across nodes.
**What You Get**:
- End-to-end transaction traces from submit to relay
- Fee escalation tracing within the transaction pipeline
- Cross-node correlation (see transaction path)
- HashRouter deduplication visibility
- Relay latency metrics
**Code Changes**: ~120 lines across 4 files, plus protobuf extension
**Why Do This Second**:
- Builds on RPC tracing (transactions submitted via RPC)
- Fee escalation is integral to the transaction processing pipeline
- Moderate complexity (requires context propagation)
- High value for debugging transaction issues
### 6.9.5 RUN Phase (Weeks 6-9)
**Goal**: Full observability including consensus.
**What You Get**:
- Complete consensus round visibility
- Phase transition timing
- Validator proposal tracking
- Validator list and manifest tracing
- Amendment voting tracing
- SHAMap sync tracing
- Full end-to-end traces (client → RPC → TX → consensus → ledger)
**Code Changes**: ~100 lines across 3 consensus files, plus validator/amendment/SHAMap modules
**Why Do This Last**:
- Highest complexity (consensus is critical path)
- Validator, amendment, and SHAMap components are lower priority
- Requires thorough testing
- Lower relative value (consensus issues are rarer)
### 6.9.6 ROI Prioritization Matrix
```mermaid
quadrantChart
title Implementation ROI Matrix
x-axis Low Effort --> High Effort
y-axis Low Value --> High Value
quadrant-1 Quick Wins - Do First
quadrant-2 Major Projects - Plan Carefully
quadrant-3 Nice to Have - Optional
quadrant-4 Time Sinks - Avoid
RPC Tracing: [0.15, 0.92]
TX Submit Trace: [0.3, 0.78]
TX Relay Trace: [0.5, 0.88]
Consensus Trace: [0.72, 0.72]
Peer Msg Trace: [0.85, 0.3]
Ledger Acquire: [0.55, 0.52]
```
---
## 6.10 Definition of Done
> **TxQ** = Transaction Queue | **HA** = High Availability
Clear, measurable criteria for each phase.
### 6.10.1 Phase 1: Core Infrastructure
| Criterion | Measurement | Target |
| --------------- | ---------------------------------------------------------- | ---------------------------- |
| SDK Integration | `cmake --build` succeeds with `-DXRPL_ENABLE_TELEMETRY=ON` | ✅ Compiles |
| Runtime Toggle | `enabled=0` produces zero overhead | <0.1% CPU difference |
| Span Creation | Unit test creates and exports span | Span appears in Tempo |
| Configuration | All config options parsed correctly | Config validation tests pass |
| Documentation | Developer guide exists | PR approved |
**Definition of Done**: All criteria met, PR merged, no regressions in CI.
### 6.10.2 Phase 2: RPC Tracing
| Criterion | Measurement | Target |
| ------------------ | ---------------------------------- | -------------------------- |
| Coverage | All RPC commands instrumented | 100% of commands |
| Context Extraction | traceparent header propagates | Integration test passes |
| Attributes | Command, status, duration recorded | Validation script confirms |
| Performance | RPC latency overhead | <1ms p99 |
| Dashboard | Grafana dashboard deployed | Screenshot in docs |
**Definition of Done**: RPC traces visible in Tempo for all commands, dashboard shows latency distribution.
### 6.10.3 Phase 3: Transaction Tracing
| Criterion | Measurement | Target |
| ---------------- | ------------------------------- | ---------------------------------- |
| Local Trace | Submit validate TxQ traced | Single-node test passes |
| Cross-Node | Context propagates via protobuf | Multi-node test passes |
| Relay Visibility | relay_count attribute correct | Spot check 100 txs |
| HashRouter | Deduplication visible in trace | Duplicate txs show suppressed=true |
| Performance | TX throughput overhead | <5% degradation |
**Definition of Done**: Transaction traces span 3+ nodes in test network, performance within bounds.
### 6.10.4 Phase 4: Consensus Tracing
| Criterion | Measurement | Target |
| -------------------- | ----------------------------- | ------------------------- |
| Round Tracing | startRound creates root span | Unit test passes |
| Phase Visibility | All phases have child spans | Integration test confirms |
| Proposer Attribution | Proposer ID in attributes | Spot check 50 rounds |
| Timing Accuracy | Phase durations match PerfLog | <5% variance |
| No Consensus Impact | Round timing unchanged | Performance test passes |
**Definition of Done**: Consensus rounds fully traceable, no impact on consensus timing.
### 6.10.5 Phase 5: Production Deployment
| Criterion | Measurement | Target |
| ------------ | ---------------------------- | -------------------------- |
| Collector HA | Multiple collectors deployed | No single point of failure |
| Sampling | Tail sampling configured | 10% base + errors + slow |
| Retention | Data retained per policy | 7 days hot, 30 days warm |
| Alerting | Alerts configured | Error spike, high latency |
| Runbook | Operator documentation | Approved by ops team |
| Training | Team trained | Session completed |
**Definition of Done**: Telemetry running in production, operators trained, alerts active.
### 6.10.6 Success Metrics Summary
| Phase | Primary Metric | Secondary Metric | Deadline |
| ------- | ---------------------- | --------------------------- | ------------- |
| Phase 1 | SDK compiles and runs | Zero overhead when disabled | End of Week 2 |
| Phase 2 | 100% RPC coverage | <1ms latency overhead | End of Week 4 |
| Phase 3 | Cross-node traces work | <5% throughput impact | End of Week 6 |
| Phase 4 | Consensus fully traced | No consensus timing impact | End of Week 8 |
| Phase 5 | Production deployment | Operators trained | End of Week 9 |
---
## 6.12 Recommended Implementation Order
Based on ROI analysis, implement in this exact order:
```mermaid
flowchart TB
subgraph week1["Week 1"]
t1[1. OpenTelemetry SDK<br/>Conan/CMake integration]
t2[2. Telemetry interface<br/>SpanGuard, config]
end
subgraph week2["Week 2"]
t3[3. RPC ServerHandler<br/>instrumentation]
t4[4. Basic Tempo setup<br/>for testing]
end
subgraph week3["Week 3"]
t5[5. Transaction submit<br/>tracing]
t6[6. Grafana dashboard<br/>v1]
end
subgraph week4["Week 4"]
t7[7. Protobuf context<br/>extension]
t8[8. PeerImp tx.relay<br/>instrumentation]
end
subgraph week5["Week 5"]
t9[9. Multi-node<br/>integration tests]
t10[10. Performance<br/>benchmarks]
end
subgraph week6_8["Weeks 6-8"]
t11[11. Consensus<br/>instrumentation]
t12[12. Full integration<br/>testing]
end
subgraph week9["Week 9"]
t13[13. Production<br/>deployment]
t14[14. Documentation<br/>& training]
end
t1 --> t2 --> t3 --> t4
t4 --> t5 --> t6
t6 --> t7 --> t8
t8 --> t9 --> t10
t10 --> t11 --> t12
t12 --> t13 --> t14
style week1 fill:#1b5e20,stroke:#0d3d14,color:#fff
style week2 fill:#1b5e20,stroke:#0d3d14,color:#fff
style week3 fill:#bf360c,stroke:#8c2809,color:#fff
style week4 fill:#bf360c,stroke:#8c2809,color:#fff
style week5 fill:#bf360c,stroke:#8c2809,color:#fff
style week6_8 fill:#0d47a1,stroke:#082f6a,color:#fff
style week9 fill:#4a148c,stroke:#2e0d57,color:#fff
style t1 fill:#1b5e20,stroke:#0d3d14,color:#fff
style t2 fill:#1b5e20,stroke:#0d3d14,color:#fff
style t3 fill:#1b5e20,stroke:#0d3d14,color:#fff
style t4 fill:#1b5e20,stroke:#0d3d14,color:#fff
style t5 fill:#ffe0b2,stroke:#ffcc80,color:#1e293b
style t6 fill:#ffe0b2,stroke:#ffcc80,color:#1e293b
style t7 fill:#ffe0b2,stroke:#ffcc80,color:#1e293b
style t8 fill:#ffe0b2,stroke:#ffcc80,color:#1e293b
style t9 fill:#ffe0b2,stroke:#ffcc80,color:#1e293b
style t10 fill:#ffe0b2,stroke:#ffcc80,color:#1e293b
style t11 fill:#0d47a1,stroke:#082f6a,color:#fff
style t12 fill:#0d47a1,stroke:#082f6a,color:#fff
style t13 fill:#4a148c,stroke:#2e0d57,color:#fff
style t14 fill:#4a148c,stroke:#2e0d57,color:#fff
```
**Reading the diagram:**
- **Week 1 (tasks 1-2)**: Foundation work -- integrate the OpenTelemetry SDK via Conan/CMake and build the `Telemetry` interface with `SpanGuard` and config parsing.
- **Week 2 (tasks 3-4)**: First observable output -- instrument `ServerHandler` for RPC tracing and stand up Tempo so developers can see traces immediately.
- **Weeks 3-5 (tasks 5-10)**: Transaction lifecycle -- add submit tracing, build the first Grafana dashboard, extend protobuf for cross-node context, instrument `PeerImp` relay, then validate with multi-node integration tests and performance benchmarks.
- **Weeks 6-8 (tasks 11-12)**: Consensus deep-dive -- instrument consensus rounds and phases, then run full integration testing across all instrumented paths.
- **Week 9 (tasks 13-14)**: Go-live -- deploy to production with sampling/alerting configured, and deliver documentation and operator training.
- **Arrow chain (t1 ... t14)**: Strict sequential dependency; each task's output is a prerequisite for the next.
---
_Previous: [Configuration Reference](./05-configuration-reference.md)_ | _Next: [Observability Backends](./07-observability-backends.md)_ | _Back to: [Overview](./OpenTelemetryPlan.md)_

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# Observability Backend Recommendations
> **Parent Document**: [OpenTelemetryPlan.md](./OpenTelemetryPlan.md)
> **Related**: [Implementation Phases](./06-implementation-phases.md) | [Appendix](./08-appendix.md)
---
## 7.1 Development/Testing Backends
> **OTLP** = OpenTelemetry Protocol
| Backend | Pros | Cons | Use Case |
| ---------- | ----------------------------------- | ---------------------- | ------------------- |
| **Tempo** | Cost-effective, Grafana integration | Requires Grafana stack | Local dev, CI, Prod |
| **Zipkin** | Simple, lightweight | Basic features | Quick prototyping |
### Quick Start with Tempo
```bash
# Start Tempo with OTLP support
docker run -d --name tempo \
-p 3200:3200 \
-p 4317:4317 \
-p 4318:4318 \
grafana/tempo:2.6.1
```
---
## 7.2 Production Backends
> **APM** = Application Performance Monitoring
| Backend | Pros | Cons | Use Case |
| ----------------- | ----------------------------------------- | ---------------------- | --------------------------- |
| **Grafana Tempo** | Cost-effective, Grafana integration | Requires Grafana stack | Most production deployments |
| **Elastic APM** | Full observability stack, log correlation | Resource intensive | Existing Elastic users |
| **Honeycomb** | Excellent query, high cardinality | SaaS cost | Deep debugging needs |
| **Datadog APM** | Full platform, easy setup | SaaS cost | Enterprise with budget |
### Backend Selection Flowchart
```mermaid
flowchart TD
start[Select Backend] --> budget{Budget<br/>Constraints?}
budget -->|Yes| oss[Open Source]
budget -->|No| saas{Prefer<br/>SaaS?}
oss --> existing{Existing<br/>Stack?}
existing -->|Grafana| tempo[Grafana Tempo]
existing -->|Elastic| elastic[Elastic APM]
existing -->|None| tempo
saas -->|Yes| enterprise{Enterprise<br/>Support?}
saas -->|No| oss
enterprise -->|Yes| datadog[Datadog APM]
enterprise -->|No| honeycomb[Honeycomb]
tempo --> final[Configure Collector]
elastic --> final
honeycomb --> final
datadog --> final
style start fill:#0f172a,stroke:#020617,color:#fff
style budget fill:#334155,stroke:#1e293b,color:#fff
style oss fill:#1e293b,stroke:#0f172a,color:#fff
style existing fill:#334155,stroke:#1e293b,color:#fff
style saas fill:#334155,stroke:#1e293b,color:#fff
style enterprise fill:#334155,stroke:#1e293b,color:#fff
style final fill:#0f172a,stroke:#020617,color:#fff
style tempo fill:#1b5e20,stroke:#0d3d14,color:#fff
style elastic fill:#bf360c,stroke:#8c2809,color:#fff
style honeycomb fill:#0d47a1,stroke:#082f6a,color:#fff
style datadog fill:#4a148c,stroke:#2e0d57,color:#fff
```
**Reading the diagram:**
- **Budget Constraints? (Yes)**: Leads to open-source options. If you already run Grafana or Elastic, pick the matching backend; otherwise default to Grafana Tempo.
- **Budget Constraints? (No) → Prefer SaaS?**: If you want a managed service, choose between Datadog (enterprise support) and Honeycomb (developer-focused). If not, fall back to open-source.
- **Terminal nodes (Tempo / Elastic / Honeycomb / Datadog)**: Each represents a concrete backend choice, all of which feed into the same final step.
- **Configure Collector**: Regardless of backend, you always finish by configuring the OTel Collector to export to your chosen destination.
---
## 7.3 Recommended Production Architecture
> **OTLP** = OpenTelemetry Protocol | **APM** = Application Performance Monitoring | **HA** = High Availability
```mermaid
flowchart TB
subgraph validators["Validator Nodes"]
v1[rippled<br/>Validator 1]
v2[rippled<br/>Validator 2]
end
subgraph stock["Stock Nodes"]
s1[rippled<br/>Stock 1]
s2[rippled<br/>Stock 2]
end
subgraph collector["OTel Collector Cluster"]
c1[Collector<br/>DC1]
c2[Collector<br/>DC2]
end
subgraph backends["Storage Backends"]
tempo[(Grafana<br/>Tempo)]
elastic[(Elastic<br/>APM)]
archive[(S3/GCS<br/>Archive)]
end
subgraph ui["Visualization"]
grafana[Grafana<br/>Dashboards]
end
v1 -->|OTLP| c1
v2 -->|OTLP| c1
s1 -->|OTLP| c2
s2 -->|OTLP| c2
c1 --> tempo
c1 --> elastic
c2 --> tempo
c2 --> archive
tempo --> grafana
elastic --> grafana
%% Note: simplified single-collector-per-DC topology shown for clarity
style validators fill:#b71c1c,stroke:#7f1d1d,color:#ffffff
style stock fill:#0d47a1,stroke:#082f6a,color:#ffffff
style collector fill:#bf360c,stroke:#8c2809,color:#ffffff
style backends fill:#1b5e20,stroke:#0d3d14,color:#ffffff
style ui fill:#4a148c,stroke:#2e0d57,color:#ffffff
```
**Reading the diagram:**
- **Validator / Stock Nodes**: All rippled nodes emit trace data via OTLP. Validators and stock nodes are grouped separately because they may reside in different network zones.
- **Collector Cluster (DC1, DC2)**: Regional collectors receive OTLP from nodes in their datacenter, apply processing (sampling, enrichment), and fan out to multiple backends.
- **Storage Backends**: Tempo and Elastic provide queryable trace storage; S3/GCS Archive provides long-term cold storage for compliance or post-incident analysis.
- **Grafana Dashboards**: The single visualization layer that queries both Tempo and Elastic, giving operators a unified view of all traces.
- **Data flow direction**: Nodes → Collectors → Storage → Grafana. Each arrow represents a network hop; minimizing collector-to-backend hops reduces latency.
> **Note**: Production deployments should use multiple collector instances behind a load balancer for high availability. The diagram shows a simplified single-collector topology for clarity.
---
## 7.4 Architecture Considerations
### 7.4.1 Collector Placement
| Strategy | Description | Pros | Cons |
| ------------- | -------------------- | ------------------------ | ----------------------- |
| **Sidecar** | Collector per node | Isolation, simple config | Resource overhead |
| **DaemonSet** | Collector per host | Shared resources | Complexity |
| **Gateway** | Central collector(s) | Centralized processing | Single point of failure |
**Recommendation**: Use **Gateway** pattern with regional collectors for rippled networks:
- One collector cluster per datacenter/region
- Tail-based sampling at collector level
- Multiple export destinations for redundancy
### 7.4.2 Sampling Strategy
```mermaid
flowchart LR
subgraph head["Head Sampling (Node)"]
hs[Node-level head sampling<br/>configurable, default: 100%<br/>recommended production: 10%]
end
subgraph tail["Tail Sampling (Collector)"]
ts1[Keep all errors]
ts2[Keep slow >5s]
ts3[Keep 10% rest]
end
head --> tail
ts1 --> final[Final Traces]
ts2 --> final
ts3 --> final
style head fill:#0d47a1,stroke:#082f6a,color:#fff
style tail fill:#1b5e20,stroke:#0d3d14,color:#fff
style hs fill:#0d47a1,stroke:#082f6a,color:#fff
style ts1 fill:#1b5e20,stroke:#0d3d14,color:#fff
style ts2 fill:#1b5e20,stroke:#0d3d14,color:#fff
style ts3 fill:#1b5e20,stroke:#0d3d14,color:#fff
style final fill:#bf360c,stroke:#8c2809,color:#fff
```
**Reading the diagram:**
- **Head Sampling (Node)**: The first filter -- each rippled node decides whether to sample a trace at creation time (default 100%, recommended 10% in production). This controls the volume leaving the node.
- **Tail Sampling (Collector)**: The second filter -- the collector inspects completed traces and applies rules: keep all errors, keep anything slower than 5 seconds, and keep 10% of the remainder.
- **Arrow head → tail**: All head-sampled traces flow to the collector, where tail sampling further reduces volume while preserving the most valuable data.
- **Final Traces**: The output after both sampling stages; this is what gets stored and queried. The two-stage approach balances cost with debuggability.
### 7.4.3 Data Retention
| Environment | Hot Storage | Warm Storage | Cold Archive |
| ----------- | ----------- | ------------ | ------------ |
| Development | 24 hours | N/A | N/A |
| Staging | 7 days | N/A | N/A |
| Production | 7 days | 30 days | many years |
---
## 7.5 Integration Checklist
- [ ] Choose primary backend (Tempo recommended for cost/features)
- [ ] Deploy collector cluster with high availability
- [ ] Configure tail-based sampling for error/latency traces
- [ ] Set up Grafana dashboards for trace visualization
- [ ] Configure alerts for trace anomalies
- [ ] Establish data retention policies
- [ ] Test trace correlation with logs and metrics
---
## 7.6 Grafana Dashboard Examples
Pre-built dashboards for rippled observability.
### 7.6.1 Consensus Health Dashboard
```json
{
"title": "rippled Consensus Health",
"uid": "rippled-consensus-health",
"tags": ["rippled", "consensus", "tracing"],
"panels": [
{
"title": "Consensus Round Duration",
"type": "timeseries",
"datasource": "Tempo",
"targets": [
{
"queryType": "traceql",
"query": "{resource.service.name=\"rippled\" && name=\"consensus.round\"} | avg(duration) by (resource.service.instance.id)"
}
],
"fieldConfig": {
"defaults": {
"unit": "ms",
"thresholds": {
"steps": [
{ "color": "green", "value": null },
{ "color": "yellow", "value": 4000 },
{ "color": "red", "value": 5000 }
]
}
}
},
"gridPos": { "h": 8, "w": 12, "x": 0, "y": 0 }
},
{
"title": "Phase Duration Breakdown",
"type": "barchart",
"datasource": "Tempo",
"targets": [
{
"queryType": "traceql",
"query": "{resource.service.name=\"rippled\" && name=~\"consensus.phase.*\"} | avg(duration) by (name)"
}
],
"gridPos": { "h": 8, "w": 12, "x": 12, "y": 0 }
},
{
"title": "Proposers per Round",
"type": "stat",
"datasource": "Tempo",
"targets": [
{
"queryType": "traceql",
"query": "{resource.service.name=\"rippled\" && name=\"consensus.round\"} | avg(span.xrpl.consensus.proposers)"
}
],
"gridPos": { "h": 4, "w": 6, "x": 0, "y": 8 }
},
{
"title": "Recent Slow Rounds (>5s)",
"type": "table",
"datasource": "Tempo",
"targets": [
{
"queryType": "traceql",
"query": "{resource.service.name=\"rippled\" && name=\"consensus.round\"} | duration > 5s"
}
],
"gridPos": { "h": 8, "w": 24, "x": 0, "y": 12 }
}
]
}
```
### 7.6.2 Node Overview Dashboard
```json
{
"title": "rippled Node Overview",
"uid": "rippled-node-overview",
"panels": [
{
"title": "Active Nodes",
"type": "stat",
"datasource": "Tempo",
"targets": [
{
"queryType": "traceql",
"query": "{resource.service.name=\"rippled\"} | count_over_time() by (resource.service.instance.id) | count()"
}
],
"gridPos": { "h": 4, "w": 4, "x": 0, "y": 0 }
},
{
"title": "Total Transactions (1h)",
"type": "stat",
"datasource": "Tempo",
"targets": [
{
"queryType": "traceql",
"query": "{resource.service.name=\"rippled\" && name=\"tx.receive\"} | count()"
}
],
"gridPos": { "h": 4, "w": 4, "x": 4, "y": 0 }
},
{
"title": "Error Rate",
"type": "gauge",
"datasource": "Tempo",
"targets": [
{
"queryType": "traceql",
"query": "{resource.service.name=\"rippled\" && status.code=error} | rate() / {resource.service.name=\"rippled\"} | rate() * 100"
}
],
"fieldConfig": {
"defaults": {
"unit": "percent",
"max": 10,
"thresholds": {
"steps": [
{ "color": "green", "value": null },
{ "color": "yellow", "value": 1 },
{ "color": "red", "value": 5 }
]
}
}
},
"gridPos": { "h": 4, "w": 4, "x": 8, "y": 0 }
},
{
"title": "Service Map",
"type": "nodeGraph",
"datasource": "Tempo",
"gridPos": { "h": 12, "w": 12, "x": 12, "y": 0 }
}
]
}
```
### 7.6.3 Alert Rules
```yaml
# grafana/provisioning/alerting/rippled-alerts.yaml
apiVersion: 1
groups:
- name: rippled-tracing-alerts
folder: rippled
interval: 1m
rules:
- uid: consensus-slow
title: Consensus Round Slow
condition: A
data:
- refId: A
datasourceUid: tempo
model:
queryType: traceql
query: '{resource.service.name="rippled" && name="consensus.round"} | avg(duration) > 5s'
# Note: Verify TraceQL aggregate queries are supported by your
# Tempo version. Aggregate alerting (e.g., avg(duration)) requires
# Tempo 2.3+ with TraceQL metrics enabled.
for: 5m
annotations:
summary: Consensus rounds taking >5 seconds
description: "Consensus duration: {{ $value }}ms"
labels:
severity: warning
- uid: rpc-error-spike
title: RPC Error Rate Spike
condition: B
data:
- refId: B
datasourceUid: tempo
model:
queryType: traceql
query: '{resource.service.name="rippled" && name=~"rpc.command.*" && status.code=error} | rate() > 0.05'
# Note: Verify TraceQL aggregate queries are supported by your
# Tempo version. Aggregate alerting (e.g., rate()) requires
# Tempo 2.3+ with TraceQL metrics enabled.
for: 2m
annotations:
summary: RPC error rate >5%
labels:
severity: critical
- uid: tx-throughput-drop
title: Transaction Throughput Drop
condition: C
data:
- refId: C
datasourceUid: tempo
model:
queryType: traceql
query: '{resource.service.name="rippled" && name="tx.receive"} | rate() < 10'
for: 10m
annotations:
summary: Transaction throughput below threshold
labels:
severity: warning
```
---
## 7.7 PerfLog and Insight Correlation
> **OTLP** = OpenTelemetry Protocol
How to correlate OpenTelemetry traces with existing rippled observability.
### 7.7.1 Correlation Architecture
```mermaid
flowchart TB
subgraph rippled["rippled Node"]
otel[OpenTelemetry<br/>Spans]
perflog[PerfLog<br/>JSON Logs]
insight[Beast Insight<br/>StatsD Metrics]
end
subgraph collectors["Data Collection"]
otelc[OTel Collector]
promtail[Promtail/Fluentd]
statsd[StatsD Exporter]
end
subgraph storage["Storage"]
tempo[(Tempo)]
loki[(Loki)]
prom[(Prometheus)]
end
subgraph grafana["Grafana"]
traces[Trace View]
logs[Log View]
metrics[Metrics View]
corr[Correlation<br/>Panel]
end
otel -->|OTLP| otelc --> tempo
perflog -->|JSON| promtail --> loki
insight -->|StatsD| statsd --> prom
tempo --> traces
loki --> logs
prom --> metrics
traces --> corr
logs --> corr
metrics --> corr
style rippled fill:#0d47a1,stroke:#082f6a,color:#fff
style collectors fill:#bf360c,stroke:#8c2809,color:#fff
style storage fill:#1b5e20,stroke:#0d3d14,color:#fff
style grafana fill:#4a148c,stroke:#2e0d57,color:#fff
style otel fill:#0d47a1,stroke:#082f6a,color:#fff
style perflog fill:#0d47a1,stroke:#082f6a,color:#fff
style insight fill:#0d47a1,stroke:#082f6a,color:#fff
style otelc fill:#bf360c,stroke:#8c2809,color:#fff
style promtail fill:#bf360c,stroke:#8c2809,color:#fff
style statsd fill:#bf360c,stroke:#8c2809,color:#fff
style tempo fill:#1b5e20,stroke:#0d3d14,color:#fff
style loki fill:#1b5e20,stroke:#0d3d14,color:#fff
style prom fill:#1b5e20,stroke:#0d3d14,color:#fff
style traces fill:#4a148c,stroke:#2e0d57,color:#fff
style logs fill:#4a148c,stroke:#2e0d57,color:#fff
style metrics fill:#4a148c,stroke:#2e0d57,color:#fff
style corr fill:#4a148c,stroke:#2e0d57,color:#fff
```
**Reading the diagram:**
- **rippled Node (three sources)**: A single node emits three independent data streams -- OpenTelemetry spans, PerfLog JSON logs, and Beast Insight StatsD metrics.
- **Data Collection layer**: Each stream has its own collector -- OTel Collector for spans, Promtail/Fluentd for logs, and a StatsD exporter for metrics. They operate independently.
- **Storage layer (Tempo, Loki, Prometheus)**: Each data type lands in a purpose-built store optimized for its query patterns (trace search, log grep, metric aggregation).
- **Grafana Correlation Panel**: The key integration point -- Grafana queries all three stores and links them via shared fields (`trace_id`, `xrpl.tx.hash`, `ledger_seq`), enabling a single-pane debugging experience.
### 7.7.2 Correlation Fields
| Source | Field | Link To | Purpose |
| ----------- | --------------------------- | ------------- | -------------------------- |
| **Trace** | `trace_id` | Logs | Find log entries for trace |
| **Trace** | `xrpl.tx.hash` | Logs, Metrics | Find TX-related data |
| **Trace** | `xrpl.consensus.ledger.seq` | Logs | Find ledger-related logs |
| **PerfLog** | `trace_id` (new) | Traces | Jump to trace from log |
| **PerfLog** | `ledger_seq` | Traces | Find consensus trace |
| **Insight** | `exemplar.trace_id` | Traces | Jump from metric spike |
### 7.7.3 Example: Debugging a Slow Transaction
**Step 1: Find the trace**
```
# In Grafana Explore with Tempo
{resource.service.name="rippled" && span.xrpl.tx.hash="ABC123..."}
```
**Step 2: Get the trace_id from the trace view**
```
Trace ID: 4bf92f3577b34da6a3ce929d0e0e4736
```
**Step 3: Find related PerfLog entries**
```
# In Grafana Explore with Loki
{job="rippled"} |= "4bf92f3577b34da6a3ce929d0e0e4736"
```
**Step 4: Check Insight metrics for the time window**
```
# In Grafana with Prometheus
rate(rippled_tx_applied_total[1m])
@ timestamp_from_trace
```
### 7.7.4 Unified Dashboard Example
```json
{
"title": "rippled Unified Observability",
"uid": "rippled-unified",
"panels": [
{
"title": "Transaction Latency (Traces)",
"type": "timeseries",
"datasource": "Tempo",
"targets": [
{
"queryType": "traceql",
"query": "{resource.service.name=\"rippled\" && name=\"tx.receive\"} | histogram_over_time(duration)"
}
],
"gridPos": { "h": 6, "w": 8, "x": 0, "y": 0 }
},
{
"title": "Transaction Rate (Metrics)",
"type": "timeseries",
"datasource": "Prometheus",
"targets": [
{
"expr": "rate(rippled_tx_received_total[5m])",
"legendFormat": "{{ instance }}"
}
],
"fieldConfig": {
"defaults": {
"links": [
{
"title": "View traces",
"url": "/explore?left={\"datasource\":\"Tempo\",\"query\":\"{resource.service.name=\\\"rippled\\\" && name=\\\"tx.receive\\\"}\"}"
}
]
}
},
"gridPos": { "h": 6, "w": 8, "x": 8, "y": 0 }
},
{
"title": "Recent Logs",
"type": "logs",
"datasource": "Loki",
"targets": [
{
"expr": "{job=\"rippled\"} | json"
}
],
"gridPos": { "h": 6, "w": 8, "x": 16, "y": 0 }
},
{
"title": "Trace Search",
"type": "table",
"datasource": "Tempo",
"targets": [
{
"queryType": "traceql",
"query": "{resource.service.name=\"rippled\"}"
}
],
"fieldConfig": {
"overrides": [
{
"matcher": { "id": "byName", "options": "traceID" },
"properties": [
{
"id": "links",
"value": [
{
"title": "View trace",
"url": "/explore?left={\"datasource\":\"Tempo\",\"query\":\"${__value.raw}\"}"
},
{
"title": "View logs",
"url": "/explore?left={\"datasource\":\"Loki\",\"query\":\"{job=\\\"rippled\\\"} |= \\\"${__value.raw}\\\"\"}"
}
]
}
]
}
]
},
"gridPos": { "h": 12, "w": 24, "x": 0, "y": 6 }
}
]
}
```
---
_Previous: [Implementation Phases](./06-implementation-phases.md)_ | _Next: [Appendix](./08-appendix.md)_ | _Back to: [Overview](./OpenTelemetryPlan.md)_

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# Appendix
> **Parent Document**: [OpenTelemetryPlan.md](./OpenTelemetryPlan.md)
> **Related**: [Observability Backends](./07-observability-backends.md)
---
## 8.1 Glossary
> **OTLP** = OpenTelemetry Protocol | **TxQ** = Transaction Queue
| Term | Definition |
| --------------------- | ---------------------------------------------------------- |
| **Span** | A unit of work with start/end time, name, and attributes |
| **Trace** | A collection of spans representing a complete request flow |
| **Trace ID** | 128-bit unique identifier for a trace |
| **Span ID** | 64-bit unique identifier for a span within a trace |
| **Context** | Carrier for trace/span IDs across boundaries |
| **Propagator** | Component that injects/extracts context |
| **Sampler** | Decides which traces to record |
| **Exporter** | Sends spans to backend |
| **Collector** | Receives, processes, and forwards telemetry |
| **OTLP** | OpenTelemetry Protocol (wire format) |
| **W3C Trace Context** | Standard HTTP headers for trace propagation |
| **Baggage** | Key-value pairs propagated across service boundaries |
| **Resource** | Entity producing telemetry (service, host, etc.) |
| **Instrumentation** | Code that creates telemetry data |
### rippled-Specific Terms
| Term | Definition |
| ----------------- | ------------------------------------------------------------- |
| **Overlay** | P2P network layer managing peer connections |
| **Consensus** | XRP Ledger consensus algorithm (RCL) |
| **Proposal** | Validator's suggested transaction set for a ledger |
| **Validation** | Validator's signature on a closed ledger |
| **HashRouter** | Component for transaction deduplication |
| **JobQueue** | Thread pool for asynchronous task execution |
| **PerfLog** | Existing performance logging system in rippled |
| **Beast Insight** | Existing metrics framework in rippled |
| **PathFinding** | Payment path computation engine for cross-currency payments |
| **TxQ** | Transaction queue managing fee-based prioritization |
| **LoadManager** | Dynamic fee escalation based on network load |
| **SHAMap** | SHA-256 hash-based map (Merkle trie variant) for ledger state |
---
## 8.2 Span Hierarchy Visualization
> **TxQ** = Transaction Queue
```mermaid
flowchart TB
subgraph trace["Trace: Transaction Lifecycle"]
rpc["rpc.request<br/>(entry point)"]
validate["tx.validate"]
relay["tx.relay<br/>(parent span)"]
subgraph peers["Peer Spans"]
p1["peer.send<br/>Peer A"]
p2["peer.send<br/>Peer B"]
p3["peer.send<br/>Peer C"]
end
subgraph pathfinding["PathFinding Spans"]
pathfind["pathfind.request"]
pathcomp["pathfind.compute"]
end
consensus["consensus.round"]
apply["tx.apply"]
subgraph txqueue["TxQ Spans"]
txq["txq.enqueue"]
txqApply["txq.apply"]
end
feeCalc["fee.escalate"]
end
subgraph validators["Validator Spans"]
valFetch["validator.list.fetch"]
valManifest["validator.manifest"]
end
rpc --> validate
rpc --> pathfind
pathfind --> pathcomp
validate --> relay
relay --> p1
relay --> p2
relay --> p3
p1 -.->|"context propagation"| consensus
consensus --> apply
apply --> txq
txq --> txqApply
txq --> feeCalc
style trace fill:#0f172a,stroke:#020617,color:#fff
style peers fill:#1e3a8a,stroke:#172554,color:#fff
style pathfinding fill:#134e4a,stroke:#0f766e,color:#fff
style txqueue fill:#064e3b,stroke:#047857,color:#fff
style validators fill:#4c1d95,stroke:#6d28d9,color:#fff
style rpc fill:#1d4ed8,stroke:#1e40af,color:#fff
style validate fill:#047857,stroke:#064e3b,color:#fff
style relay fill:#047857,stroke:#064e3b,color:#fff
style p1 fill:#0e7490,stroke:#155e75,color:#fff
style p2 fill:#0e7490,stroke:#155e75,color:#fff
style p3 fill:#0e7490,stroke:#155e75,color:#fff
style consensus fill:#fef3c7,stroke:#fde68a,color:#1e293b
style apply fill:#047857,stroke:#064e3b,color:#fff
style pathfind fill:#0e7490,stroke:#155e75,color:#fff
style pathcomp fill:#0e7490,stroke:#155e75,color:#fff
style txq fill:#047857,stroke:#064e3b,color:#fff
style txqApply fill:#047857,stroke:#064e3b,color:#fff
style feeCalc fill:#047857,stroke:#064e3b,color:#fff
style valFetch fill:#6d28d9,stroke:#4c1d95,color:#fff
style valManifest fill:#6d28d9,stroke:#4c1d95,color:#fff
```
**Reading the diagram:**
- **rpc.request (blue, top)**: The entry point — every traced transaction starts as an RPC call; this root span is the parent of all downstream work.
- **tx.validate and pathfind.request (green/teal, first fork)**: The RPC request fans out into transaction validation and, for cross-currency payments, a PathFinding branch (`pathfind.request` -> `pathfind.compute`).
- **tx.relay -> Peer Spans (teal, middle)**: After validation, the transaction is relayed to peers A, B, and C in parallel; each `peer.send` is a sibling child span showing fan-out across the network.
- **context propagation (dashed arrow)**: The dotted line from `peer.send Peer A` to `consensus.round` represents the trace context crossing a node boundary — the receiving validator picks up the same `trace_id` and continues the trace.
- **consensus.round -> tx.apply -> TxQ Spans (green, lower)**: Once consensus accepts the transaction, it is applied to the ledger; the TxQ spans (`txq.enqueue`, `txq.apply`, `fee.escalate`) capture queue depth and fee escalation behavior.
- **Validator Spans (purple, detached)**: `validator.list.fetch` and `validator.manifest` are independent workflows for UNL management — they run on their own traces and are linked to consensus via Span Links, not parent-child relationships.
---
## 8.3 References
> **OTLP** = OpenTelemetry Protocol
### OpenTelemetry Resources
1. [OpenTelemetry C++ SDK](https://github.com/open-telemetry/opentelemetry-cpp)
2. [OpenTelemetry Specification](https://opentelemetry.io/docs/specs/otel/)
3. [OpenTelemetry Collector](https://opentelemetry.io/docs/collector/)
4. [OTLP Protocol Specification](https://opentelemetry.io/docs/specs/otlp/)
### Standards
5. [W3C Trace Context](https://www.w3.org/TR/trace-context/)
6. [W3C Baggage](https://www.w3.org/TR/baggage/)
7. [Protocol Buffers](https://protobuf.dev/)
### rippled Resources
8. [rippled Source Code](https://github.com/XRPLF/rippled)
9. [XRP Ledger Documentation](https://xrpl.org/docs/)
10. [rippled Overlay README](https://github.com/XRPLF/rippled/blob/develop/src/xrpld/overlay/README.md)
11. [rippled RPC README](https://github.com/XRPLF/rippled/blob/develop/src/xrpld/rpc/README.md)
12. [rippled Consensus README](https://github.com/XRPLF/rippled/blob/develop/src/xrpld/app/consensus/README.md)
---
## 8.4 Version History
| Version | Date | Author | Changes |
| ------- | ---------- | ------ | -------------------------------------------------------------- |
| 1.0 | 2026-02-12 | - | Initial implementation plan |
| 1.1 | 2026-02-13 | - | Refactored into modular documents |
| 1.2 | 2026-03-24 | - | Review fixes: accuracy corrections, cross-document consistency |
---
## 8.5 Document Index
### Plan Documents
| Document | Description |
| ---------------------------------------------------------------- | -------------------------------------------- |
| [OpenTelemetryPlan.md](./OpenTelemetryPlan.md) | Master overview and executive summary |
| [00-tracing-fundamentals.md](./00-tracing-fundamentals.md) | Distributed tracing concepts and OTel primer |
| [01-architecture-analysis.md](./01-architecture-analysis.md) | rippled architecture and trace points |
| [02-design-decisions.md](./02-design-decisions.md) | SDK selection, exporters, span conventions |
| [03-implementation-strategy.md](./03-implementation-strategy.md) | Directory structure, performance analysis |
| [04-code-samples.md](./04-code-samples.md) | C++ code examples for all components |
| [05-configuration-reference.md](./05-configuration-reference.md) | rippled config, CMake, Collector configs |
| [06-implementation-phases.md](./06-implementation-phases.md) | Timeline, tasks, risks, success metrics |
| [07-observability-backends.md](./07-observability-backends.md) | Backend selection and architecture |
| [08-appendix.md](./08-appendix.md) | Glossary, references, version history |
| [presentation.md](./presentation.md) | Slide deck for OTel plan overview |
### Task Lists
| Document | Description |
| -------------------------------------------------------------------------- | --------------------------------------------------- |
| [POC_taskList.md](./POC_taskList.md) | Proof-of-concept telemetry integration |
| [Phase2_taskList.md](./Phase2_taskList.md) | RPC layer trace instrumentation |
| [Phase3_taskList.md](./Phase3_taskList.md) | Peer overlay & consensus tracing |
| [Phase4_taskList.md](./Phase4_taskList.md) | Transaction lifecycle tracing |
| [Phase5_taskList.md](./Phase5_taskList.md) | Ledger processing & advanced tracing |
| [Phase5_IntegrationTest_taskList.md](./Phase5_IntegrationTest_taskList.md) | Observability stack integration tests |
| [presentation.md](./presentation.md) | Presentation slides for OpenTelemetry plan overview |
---
_Previous: [Observability Backends](./07-observability-backends.md)_ | _Back to: [Overview](./OpenTelemetryPlan.md)_

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# [OpenTelemetry](00-tracing-fundamentals.md) Distributed Tracing Implementation Plan for rippled (xrpld)
## Executive Summary
> **OTLP** = OpenTelemetry Protocol
This document provides a comprehensive implementation plan for integrating OpenTelemetry distributed tracing into the rippled XRP Ledger node software. The plan addresses the unique challenges of a decentralized peer-to-peer system where trace context must propagate across network boundaries between independent nodes.
### Key Benefits
- **End-to-end transaction visibility**: Track transactions from submission through consensus to ledger inclusion
- **Consensus round analysis**: Understand timing and behavior of consensus phases across validators
- **RPC performance insights**: Identify slow handlers and optimize response times
- **Network topology understanding**: Visualize message propagation patterns between peers
- **Incident debugging**: Correlate events across distributed nodes during issues
### Estimated Performance Overhead
| Metric | Overhead | Notes |
| ------------- | ---------- | ----------------------------------- |
| CPU | 1-3% | Span creation and attribute setting |
| Memory | 2-5 MB | Batch buffer for pending spans |
| Network | 10-50 KB/s | Compressed OTLP export to collector |
| Latency (p99) | <2% | With proper sampling configuration |
---
## Document Structure
This implementation plan is organized into modular documents for easier navigation:
<div align="center">
```mermaid
flowchart TB
overview["📋 OpenTelemetryPlan.md<br/>(This Document)"]
subgraph fundamentals["Fundamentals"]
fund["00-tracing-fundamentals.md"]
end
subgraph analysis["Analysis & Design"]
arch["01-architecture-analysis.md"]
design["02-design-decisions.md"]
end
subgraph impl["Implementation"]
strategy["03-implementation-strategy.md"]
code["04-code-samples.md"]
config["05-configuration-reference.md"]
end
subgraph deploy["Deployment & Planning"]
phases["06-implementation-phases.md"]
backends["07-observability-backends.md"]
appendix["08-appendix.md"]
poc["POC_taskList.md"]
end
overview --> fundamentals
overview --> analysis
overview --> impl
overview --> deploy
fund --> arch
arch --> design
design --> strategy
strategy --> code
code --> config
config --> phases
phases --> backends
backends --> appendix
phases --> poc
style overview fill:#1b5e20,stroke:#0d3d14,color:#fff,stroke-width:2px
style fundamentals fill:#00695c,stroke:#004d40,color:#fff
style fund fill:#00695c,stroke:#004d40,color:#fff
style analysis fill:#0d47a1,stroke:#082f6a,color:#fff
style impl fill:#bf360c,stroke:#8c2809,color:#fff
style deploy fill:#4a148c,stroke:#2e0d57,color:#fff
style arch fill:#0d47a1,stroke:#082f6a,color:#fff
style design fill:#0d47a1,stroke:#082f6a,color:#fff
style strategy fill:#bf360c,stroke:#8c2809,color:#fff
style code fill:#bf360c,stroke:#8c2809,color:#fff
style config fill:#bf360c,stroke:#8c2809,color:#fff
style phases fill:#4a148c,stroke:#2e0d57,color:#fff
style backends fill:#4a148c,stroke:#2e0d57,color:#fff
style appendix fill:#4a148c,stroke:#2e0d57,color:#fff
style poc fill:#4a148c,stroke:#2e0d57,color:#fff
```
</div>
---
## Table of Contents
| Section | Document | Description |
| ------- | ---------------------------------------------------------- | ---------------------------------------------------------------------- |
| **0** | [Tracing Fundamentals](./00-tracing-fundamentals.md) | Distributed tracing concepts, span relationships, context propagation |
| **1** | [Architecture Analysis](./01-architecture-analysis.md) | rippled component analysis, trace points, instrumentation priorities |
| **2** | [Design Decisions](./02-design-decisions.md) | SDK selection, exporters, span naming, attributes, context propagation |
| **3** | [Implementation Strategy](./03-implementation-strategy.md) | Directory structure, key principles, performance optimization |
| **4** | [Code Samples](./04-code-samples.md) | C++ implementation examples for core infrastructure and key modules |
| **5** | [Configuration Reference](./05-configuration-reference.md) | rippled config, CMake integration, Collector configurations |
| **6** | [Implementation Phases](./06-implementation-phases.md) | 5-phase timeline, tasks, risks, success metrics |
| **7** | [Observability Backends](./07-observability-backends.md) | Backend selection guide and production architecture |
| **8** | [Appendix](./08-appendix.md) | Glossary, references, version history |
| **POC** | [POC Task List](./POC_taskList.md) | Proof of concept tasks for RPC tracing end-to-end demo |
---
## 0. Tracing Fundamentals
This document introduces distributed tracing concepts for readers unfamiliar with the domain. It covers what traces and spans are, how parent-child and follows-from relationships model causality, how context propagates across service boundaries, and how sampling controls data volume. It also maps these concepts to rippled-specific scenarios like transaction relay and consensus.
➡️ **[Read Tracing Fundamentals](./00-tracing-fundamentals.md)**
---
## 1. Architecture Analysis
> **WS** = WebSocket | **TxQ** = Transaction Queue
The rippled node consists of several key components that require instrumentation for comprehensive distributed tracing. The main areas include the RPC server (HTTP/WebSocket), Overlay P2P network, Consensus mechanism (RCLConsensus), JobQueue for async task execution, PathFinding, Transaction Queue (TxQ), fee escalation (LoadManager), ledger acquisition, validator management, and existing observability infrastructure (PerfLog, Insight/StatsD, Journal logging).
Key trace points span across transaction submission via RPC, peer-to-peer message propagation, consensus round execution, ledger building, path computation, transaction queue behavior, fee escalation, and validator health. The implementation prioritizes high-value, low-risk components first: RPC handlers provide immediate value with minimal risk, while consensus tracing requires careful implementation to avoid timing impacts.
➡️ **[Read full Architecture Analysis](./01-architecture-analysis.md)**
---
## 2. Design Decisions
> **OTLP** = OpenTelemetry Protocol | **CNCF** = Cloud Native Computing Foundation
The OpenTelemetry C++ SDK is selected for its CNCF backing, active development, and native performance characteristics. Traces are exported via OTLP/gRPC (primary) or OTLP/HTTP (fallback) to an OpenTelemetry Collector, which provides flexible routing and sampling.
Span naming follows a hierarchical `<component>.<operation>` convention (e.g., `rpc.submit`, `tx.relay`, `consensus.round`). Context propagation uses W3C Trace Context headers for HTTP and embedded Protocol Buffer fields for P2P messages. The implementation coexists with existing PerfLog and Insight observability systems through correlation IDs.
**Data Collection & Privacy**: Telemetry collects only operational metadata (timing, counts, hashes) — never sensitive content (private keys, balances, amounts, raw payloads). Privacy protection includes account hashing, configurable redaction, sampling, and collector-level filtering. Node operators retain full control over telemetry configuration.
➡️ **[Read full Design Decisions](./02-design-decisions.md)**
---
## 3. Implementation Strategy
The telemetry code is organized under `include/xrpl/telemetry/` for headers and `src/libxrpl/telemetry/` for implementation. Key principles include RAII-based span management via `SpanGuard`, conditional compilation with `XRPL_ENABLE_TELEMETRY`, and minimal runtime overhead through batch processing and efficient sampling.
Performance optimization strategies include probabilistic head sampling (10% default), tail-based sampling at the collector for errors and slow traces, batch export to reduce network overhead, and conditional instrumentation that compiles to no-ops when disabled.
➡️ **[Read full Implementation Strategy](./03-implementation-strategy.md)**
---
## 4. Code Samples
C++ implementation examples are provided for the core telemetry infrastructure and key modules:
- `Telemetry.h` - Core interface for tracer access and span creation
- `SpanGuard.h` - RAII wrapper for automatic span lifecycle management
- `TracingInstrumentation.h` - Macros for conditional instrumentation
- Protocol Buffer extensions for trace context propagation
- Module-specific instrumentation (RPC, Consensus, P2P, JobQueue)
- Remaining modules (PathFinding, TxQ, Validator, etc.) follow the same patterns
➡️ **[View all Code Samples](./04-code-samples.md)**
---
## 5. Configuration Reference
> **OTLP** = OpenTelemetry Protocol | **APM** = Application Performance Monitoring
Configuration is handled through the `[telemetry]` section in `xrpld.cfg` with options for enabling/disabling, exporter selection, endpoint configuration, sampling ratios, and component-level filtering. CMake integration includes a `XRPL_ENABLE_TELEMETRY` option for compile-time control.
OpenTelemetry Collector configurations are provided for development and production (with tail-based sampling, Tempo, and Elastic APM). Docker Compose examples enable quick local development environment setup.
➡️ **[View full Configuration Reference](./05-configuration-reference.md)**
---
## 6. Implementation Phases
The implementation spans 9 weeks across 5 phases:
| Phase | Duration | Focus | Key Deliverables |
| ----- | --------- | ------------------- | --------------------------------------------------- |
| 1 | Weeks 1-2 | Core Infrastructure | SDK integration, Telemetry interface, Configuration |
| 2 | Weeks 3-4 | RPC Tracing | HTTP context extraction, Handler instrumentation |
| 3 | Weeks 5-6 | Transaction Tracing | Protocol Buffer context, Relay propagation |
| 4 | Weeks 7-8 | Consensus Tracing | Round spans, Proposal/validation tracing |
| 5 | Week 9 | Documentation | Runbook, Dashboards, Training |
**Total Effort**: 47 person-days (2 developers working in parallel)
➡️ **[View full Implementation Phases](./06-implementation-phases.md)**
---
## 7. Observability Backends
> **APM** = Application Performance Monitoring | **GCS** = Google Cloud Storage
Grafana Tempo is recommended for all environments due to its cost-effectiveness and Grafana integration, while Elastic APM is ideal for organizations with existing Elastic infrastructure.
The recommended production architecture uses a gateway collector pattern with regional collectors performing tail-based sampling, routing traces to multiple backends (Tempo for primary storage, Elastic for log correlation, S3/GCS for long-term archive).
➡️ **[View Observability Backend Recommendations](./07-observability-backends.md)**
---
## 8. Appendix
The appendix contains a glossary of OpenTelemetry and rippled-specific terms, references to external documentation and specifications, version history for this implementation plan, and a complete document index.
➡️ **[View Appendix](./08-appendix.md)**
---
## POC Task List
A step-by-step task list for building a minimal end-to-end proof of concept that demonstrates distributed tracing in rippled. The POC scope is limited to RPC tracing — showing request traces flowing from rippled through an OpenTelemetry Collector into Tempo, viewable in Grafana.
➡️ **[View POC Task List](./POC_taskList.md)**
---
_This document provides a comprehensive implementation plan for integrating OpenTelemetry distributed tracing into the rippled XRP Ledger node software. For detailed information on any section, follow the links to the corresponding sub-documents._

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# OpenTelemetry POC Task List
> **Goal**: Build a minimal end-to-end proof of concept that demonstrates distributed tracing in rippled. A successful POC will show RPC request traces flowing from rippled through an OTel Collector into Tempo, viewable in Grafana.
>
> **Scope**: RPC tracing only (highest value, lowest risk per the [CRAWL phase](./06-implementation-phases.md#6102-quick-wins-immediate-value) in the implementation phases). No cross-node P2P context propagation or consensus tracing in the POC.
### Related Plan Documents
| Document | Relevance to POC |
| ---------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------- |
| [00-tracing-fundamentals.md](./00-tracing-fundamentals.md) | Core concepts: traces, spans, context propagation, sampling |
| [01-architecture-analysis.md](./01-architecture-analysis.md) | RPC request flow (§1.5), key trace points (§1.6), instrumentation priority (§1.7) |
| [02-design-decisions.md](./02-design-decisions.md) | SDK selection (§2.1), exporter config (§2.2), span naming (§2.3), attribute schema (§2.4), coexistence with PerfLog/Insight (§2.6) |
| [03-implementation-strategy.md](./03-implementation-strategy.md) | Directory structure (§3.1), key principles (§3.2), performance overhead (§3.3-3.6), conditional compilation (§3.7.3), code intrusiveness (§3.9) |
| [04-code-samples.md](./04-code-samples.md) | Telemetry interface (§4.1), SpanGuard (§4.2), macros (§4.3), RPC instrumentation (§4.5.3) |
| [05-configuration-reference.md](./05-configuration-reference.md) | rippled config (§5.1), config parser (§5.2), Application integration (§5.3), CMake (§5.4), Collector config (§5.5), Docker Compose (§5.6), Grafana (§5.8) |
| [06-implementation-phases.md](./06-implementation-phases.md) | Phase 1 core tasks (§6.2), Phase 2 RPC tasks (§6.3), quick wins (§6.10), definition of done (§6.11) |
| [07-observability-backends.md](./07-observability-backends.md) | Tempo dev setup (§7.1), Grafana dashboards (§7.6), alert rules (§7.6.3) |
---
## Task 0: Docker Observability Stack Setup
> **OTLP** = OpenTelemetry Protocol
**Objective**: Stand up the backend infrastructure to receive, store, and display traces.
**What to do**:
- Create `docker/telemetry/docker-compose.yml` in the repo with three services:
1. **OpenTelemetry Collector** (`otel/opentelemetry-collector-contrib:0.92.0`)
- Expose ports `4317` (OTLP gRPC) and `4318` (OTLP HTTP)
- Expose port `13133` (health check)
- Mount a config file `docker/telemetry/otel-collector-config.yaml`
2. **Tempo** (`grafana/tempo:2.6.1`)
- Expose port `3200` (HTTP API) and `4317` (OTLP gRPC, internal)
3. **Grafana** (`grafana/grafana:latest`) — optional but useful
- Expose port `3000`
- Enable anonymous admin access for local dev (`GF_AUTH_ANONYMOUS_ENABLED=true`, `GF_AUTH_ANONYMOUS_ORG_ROLE=Admin`)
- Provision Tempo as a data source via `docker/telemetry/grafana/provisioning/datasources/tempo.yaml`
- Create `docker/telemetry/otel-collector-config.yaml`:
```yaml
receivers:
otlp:
protocols:
grpc:
endpoint: 0.0.0.0:4317
http:
endpoint: 0.0.0.0:4318
processors:
batch:
timeout: 1s
send_batch_size: 100
exporters:
logging:
verbosity: detailed
otlp/tempo:
endpoint: tempo:4317
tls:
insecure: true
service:
pipelines:
traces:
receivers: [otlp]
processors: [batch]
exporters: [logging, otlp/tempo]
```
- Create Grafana Tempo datasource provisioning file at `docker/telemetry/grafana/provisioning/datasources/tempo.yaml`:
```yaml
apiVersion: 1
datasources:
- name: Tempo
type: tempo
access: proxy
url: http://tempo:3200
```
**Verification**: Run `docker compose -f docker/telemetry/docker-compose.yml up -d`, then:
- `curl http://localhost:13133` returns healthy (Collector)
- `http://localhost:3000` opens Grafana (Tempo datasource available, no traces yet)
**Reference**:
- [05-configuration-reference.md §5.5](./05-configuration-reference.md) — Collector config (dev YAML with Tempo exporter)
- [05-configuration-reference.md §5.6](./05-configuration-reference.md) — Docker Compose development environment
- [07-observability-backends.md §7.1](./07-observability-backends.md) — Tempo quick start and backend selection
- [05-configuration-reference.md §5.8](./05-configuration-reference.md) — Grafana datasource provisioning and dashboards
---
## Task 1: Add OpenTelemetry C++ SDK Dependency
**Objective**: Make `opentelemetry-cpp` available to the build system.
**What to do**:
- Edit `conanfile.py` to add `opentelemetry-cpp` as an **optional** dependency. The gRPC otel plugin flag (`"grpc/*:otel_plugin": False`) in the existing conanfile may need to remain false — we pull the OTel SDK separately.
- Add a Conan option: `with_telemetry = [True, False]` defaulting to `False`
- When `with_telemetry` is `True`, add `opentelemetry-cpp` to `self.requires()`
- Required OTel Conan components: `opentelemetry-cpp` (which bundles api, sdk, and exporters). If the package isn't in Conan Center, consider using `FetchContent` in CMake or building from source as a fallback.
- Edit `CMakeLists.txt`:
- Add option: `option(XRPL_ENABLE_TELEMETRY "Enable OpenTelemetry tracing" OFF)`
- When ON, `find_package(opentelemetry-cpp CONFIG REQUIRED)` and add compile definition `XRPL_ENABLE_TELEMETRY`
- When OFF, do nothing (zero build impact)
- Verify the build succeeds with `-DXRPL_ENABLE_TELEMETRY=OFF` (no regressions) and with `-DXRPL_ENABLE_TELEMETRY=ON` (SDK links successfully).
**Key files**:
- `conanfile.py`
- `CMakeLists.txt`
**Reference**:
- [05-configuration-reference.md §5.4](./05-configuration-reference.md) — CMake integration, `FindOpenTelemetry.cmake`, `XRPL_ENABLE_TELEMETRY` option
- [03-implementation-strategy.md §3.2](./03-implementation-strategy.md) — Key principle: zero-cost when disabled via compile-time flags
- [02-design-decisions.md §2.1](./02-design-decisions.md) — SDK selection rationale and required OTel components
---
## Task 2: Create Core Telemetry Interface and NullTelemetry
**Objective**: Define the `Telemetry` abstract interface and a no-op implementation so the rest of the codebase can reference telemetry without hard-depending on the OTel SDK.
**What to do**:
- Create `include/xrpl/telemetry/Telemetry.h`:
- Define `namespace xrpl::telemetry`
- Define `struct Telemetry::Setup` holding: `enabled`, `exporterEndpoint`, `samplingRatio`, `serviceName`, `serviceVersion`, `serviceInstanceId`, `traceRpc`, `traceTransactions`, `traceConsensus`, `tracePeer`
- Define abstract `class Telemetry` with:
- `virtual void start() = 0;`
- `virtual void stop() = 0;`
- `virtual bool isEnabled() const = 0;`
- `virtual nostd::shared_ptr<Tracer> getTracer(string_view name = "rippled") = 0;`
- `virtual nostd::shared_ptr<Span> startSpan(string_view name, SpanKind kind = kInternal) = 0;`
- `virtual nostd::shared_ptr<Span> startSpan(string_view name, Context const& parentContext, SpanKind kind = kInternal) = 0;`
- `virtual bool shouldTraceRpc() const = 0;`
- `virtual bool shouldTraceTransactions() const = 0;`
- `virtual bool shouldTraceConsensus() const = 0;`
- Factory: `std::unique_ptr<Telemetry> make_Telemetry(Setup const&, beast::Journal);`
- Config parser: `Telemetry::Setup setup_Telemetry(Section const&, std::string const& nodePublicKey, std::string const& version);`
- Create `include/xrpl/telemetry/SpanGuard.h`:
- RAII guard that takes an `nostd::shared_ptr<Span>`, creates a `Scope`, and calls `span->End()` in destructor.
- Convenience: `setAttribute()`, `setOk()`, `setStatus()`, `addEvent()`, `recordException()`, `context()`
- See [04-code-samples.md](./04-code-samples.md) §4.2 for the full implementation.
- Create `src/libxrpl/telemetry/NullTelemetry.cpp`:
- Implements `Telemetry` with all no-ops.
- `isEnabled()` returns `false`, `startSpan()` returns a noop span.
- This is used when `XRPL_ENABLE_TELEMETRY` is OFF or `enabled=0` in config.
- Guard all OTel SDK headers behind `#ifdef XRPL_ENABLE_TELEMETRY`. The `NullTelemetry` implementation should compile without the OTel SDK present.
**Key new files**:
- `include/xrpl/telemetry/Telemetry.h`
- `include/xrpl/telemetry/SpanGuard.h`
- `src/libxrpl/telemetry/NullTelemetry.cpp`
**Reference**:
- [04-code-samples.md §4.1](./04-code-samples.md) — Full `Telemetry` interface with `Setup` struct, lifecycle, tracer access, span creation, and component filtering methods
- [04-code-samples.md §4.2](./04-code-samples.md) — Full `SpanGuard` RAII implementation and `NullSpanGuard` no-op class
- [03-implementation-strategy.md §3.1](./03-implementation-strategy.md) — Directory structure: `include/xrpl/telemetry/` for headers, `src/libxrpl/telemetry/` for implementation
- [03-implementation-strategy.md §3.7.3](./03-implementation-strategy.md) — Conditional instrumentation and zero-cost compile-time disabled pattern
---
## Task 3: Implement OTel-Backed Telemetry
> **OTLP** = OpenTelemetry Protocol
**Objective**: Implement the real `Telemetry` class that initializes the OTel SDK, configures the OTLP exporter and batch processor, and creates tracers/spans.
**What to do**:
- Create `src/libxrpl/telemetry/Telemetry.cpp` (compiled only when `XRPL_ENABLE_TELEMETRY=ON`):
- `class TelemetryImpl : public Telemetry` that:
- In `start()`: creates a `TracerProvider` with:
- Resource attributes: `service.name`, `service.version`, `service.instance.id`
- An `OtlpHttpExporter` pointed at `setup.exporterEndpoint` (default `localhost:4318`)
- A `BatchSpanProcessor` with configurable batch size and delay
- A `TraceIdRatioBasedSampler` using `setup.samplingRatio`
- Sets the global `TracerProvider`
- In `stop()`: calls `ForceFlush()` then shuts down the provider
- In `startSpan()`: delegates to `getTracer()->StartSpan(name, ...)`
- `shouldTraceRpc()` etc. read from `Setup` fields
- Create `src/libxrpl/telemetry/TelemetryConfig.cpp`:
- `setup_Telemetry()` parses the `[telemetry]` config section from `xrpld.cfg`
- Maps config keys: `enabled`, `exporter`, `endpoint`, `sampling_ratio`, `trace_rpc`, `trace_transactions`, `trace_consensus`, `trace_peer`
- Wire `make_Telemetry()` factory:
- If `setup.enabled` is true AND `XRPL_ENABLE_TELEMETRY` is defined: return `TelemetryImpl`
- Otherwise: return `NullTelemetry`
- Add telemetry source files to CMake. When `XRPL_ENABLE_TELEMETRY=ON`, compile `Telemetry.cpp` and `TelemetryConfig.cpp` and link against `opentelemetry-cpp::api`, `opentelemetry-cpp::sdk`, `opentelemetry-cpp::otlp_grpc_exporter`. When OFF, compile only `NullTelemetry.cpp`.
**Key new files**:
- `src/libxrpl/telemetry/Telemetry.cpp`
- `src/libxrpl/telemetry/TelemetryConfig.cpp`
**Key modified files**:
- `CMakeLists.txt` (add telemetry library target)
**Reference**:
- [04-code-samples.md §4.1](./04-code-samples.md) — `Telemetry` interface that `TelemetryImpl` must implement
- [05-configuration-reference.md §5.2](./05-configuration-reference.md) — `setup_Telemetry()` config parser implementation
- [02-design-decisions.md §2.2](./02-design-decisions.md) — OTLP/gRPC exporter config (endpoint, TLS options)
- [02-design-decisions.md §2.4.1](./02-design-decisions.md) — Resource attributes: `service.name`, `service.version`, `service.instance.id`, `xrpl.network.id`
- [03-implementation-strategy.md §3.4](./03-implementation-strategy.md) — Per-operation CPU costs and overhead budget for span creation
- [03-implementation-strategy.md §3.5](./03-implementation-strategy.md) — Memory overhead: static (~456 KB) and dynamic (~1.2 MB) budgets
---
## Task 4: Integrate Telemetry into Application Lifecycle
**Objective**: Wire the `Telemetry` object into `Application` so all components can access it.
**What to do**:
- Edit `src/xrpld/app/main/Application.h`:
- Forward-declare `namespace xrpl::telemetry { class Telemetry; }`
- Add pure virtual method: `virtual telemetry::Telemetry& getTelemetry() = 0;`
- Edit `src/xrpld/app/main/Application.cpp` (the `ApplicationImp` class):
- Add member: `std::unique_ptr<telemetry::Telemetry> telemetry_;`
- In the constructor, after config is loaded and node identity is known:
```cpp
auto const telemetrySection = config_->section("telemetry");
auto telemetrySetup = telemetry::setup_Telemetry(
telemetrySection,
toBase58(TokenType::NodePublic, nodeIdentity_.publicKey()),
BuildInfo::getVersionString());
telemetry_ = telemetry::make_Telemetry(telemetrySetup, logs_->journal("Telemetry"));
```
- In `start()`: call `telemetry_->start()` early
- In `stop()` or destructor: call `telemetry_->stop()` late (to flush pending spans)
- Implement `getTelemetry()` override: return `*telemetry_`
- Add `[telemetry]` section to the example config `cfg/rippled-example.cfg`:
```ini
# [telemetry]
# enabled=1
# endpoint=localhost:4317
# sampling_ratio=1.0
# trace_rpc=1
```
**Key modified files**:
- `src/xrpld/app/main/Application.h`
- `src/xrpld/app/main/Application.cpp`
- `cfg/rippled-example.cfg` (or equivalent example config)
**Reference**:
- [05-configuration-reference.md §5.3](./05-configuration-reference.md) — `ApplicationImp` changes: member declaration, constructor init, `start()`/`stop()` wiring, `getTelemetry()` override
- [05-configuration-reference.md §5.1](./05-configuration-reference.md) — `[telemetry]` config section format and all option defaults
- [03-implementation-strategy.md §3.9.2](./03-implementation-strategy.md) — File impact assessment: `Application.cpp` ~15 lines added, ~3 changed (Low risk)
---
## Task 5: Create Instrumentation Macros
**Objective**: Define convenience macros that make instrumenting code one-liners, and that compile to zero-cost no-ops when telemetry is disabled.
**What to do**:
- Create `src/xrpld/telemetry/TracingInstrumentation.h`:
- When `XRPL_ENABLE_TELEMETRY` is defined:
```cpp
#define XRPL_TRACE_SPAN(telemetry, name) \
auto _xrpl_span_ = (telemetry).startSpan(name); \
::xrpl::telemetry::SpanGuard _xrpl_guard_(_xrpl_span_)
#define XRPL_TRACE_RPC(telemetry, name) \
std::optional<::xrpl::telemetry::SpanGuard> _xrpl_guard_; \
if ((telemetry).shouldTraceRpc()) { \
_xrpl_guard_.emplace((telemetry).startSpan(name)); \
}
#define XRPL_TRACE_SET_ATTR(key, value) \
if (_xrpl_guard_.has_value()) { \
_xrpl_guard_->setAttribute(key, value); \
}
#define XRPL_TRACE_EXCEPTION(e) \
if (_xrpl_guard_.has_value()) { \
_xrpl_guard_->recordException(e); \
}
```
- When `XRPL_ENABLE_TELEMETRY` is NOT defined, all macros expand to `((void)0)`
**Key new file**:
- `src/xrpld/telemetry/TracingInstrumentation.h`
**Reference**:
- [04-code-samples.md §4.3](./04-code-samples.md) — Full macro definitions for `XRPL_TRACE_SPAN`, `XRPL_TRACE_RPC`, `XRPL_TRACE_CONSENSUS`, `XRPL_TRACE_SET_ATTR`, `XRPL_TRACE_EXCEPTION` with both enabled and disabled branches
- [03-implementation-strategy.md §3.7.3](./03-implementation-strategy.md) — Conditional instrumentation pattern: compile-time `#ifndef` and runtime `shouldTrace*()` checks
- [03-implementation-strategy.md §3.9.7](./03-implementation-strategy.md) — Before/after code examples showing minimal intrusiveness (~1-3 lines per instrumentation point)
---
## Task 6: Instrument RPC ServerHandler
> **WS** = WebSocket
**Objective**: Add tracing to the HTTP RPC entry point so every incoming RPC request creates a span.
**What to do**:
- Edit `src/xrpld/rpc/detail/ServerHandler.cpp`:
- `#include` the `TracingInstrumentation.h` header
- In `ServerHandler::onRequest(Session& session)`:
- At the top of the method, add: `XRPL_TRACE_RPC(app_.getTelemetry(), "rpc.request");`
- After the RPC command name is extracted, set attribute: `XRPL_TRACE_SET_ATTR("xrpl.rpc.command", command);`
- After the response status is known, set: `XRPL_TRACE_SET_ATTR("http.status_code", static_cast<int64_t>(statusCode));`
- Wrap error paths with: `XRPL_TRACE_EXCEPTION(e);`
- In `ServerHandler::processRequest(...)`:
- Add a child span: `XRPL_TRACE_RPC(app_.getTelemetry(), "rpc.process");`
- Set method attribute: `XRPL_TRACE_SET_ATTR("xrpl.rpc.method", request_method);`
- In `ServerHandler::onWSMessage(...)` (WebSocket path):
- Add: `XRPL_TRACE_RPC(app_.getTelemetry(), "rpc.ws.message");`
- The goal is to see spans like:
```
rpc.request
└── rpc.process
```
in Tempo/Grafana for every HTTP RPC call.
**Key modified file**:
- `src/xrpld/rpc/detail/ServerHandler.cpp` (~15-25 lines added)
**Reference**:
- [04-code-samples.md §4.5.3](./04-code-samples.md) — Complete `ServerHandler::onRequest()` instrumented code sample with W3C header extraction, span creation, attribute setting, and error handling
- [01-architecture-analysis.md §1.5](./01-architecture-analysis.md) — RPC request flow diagram: HTTP request -> attributes -> jobqueue.enqueue -> rpc.command -> response
- [01-architecture-analysis.md §1.6](./01-architecture-analysis.md) — Key trace points table: `rpc.request` in `ServerHandler.cpp::onRequest()` (Priority: High)
- [02-design-decisions.md §2.3](./02-design-decisions.md) — Span naming convention: `rpc.request`, `rpc.command.*`
- [02-design-decisions.md §2.4.2](./02-design-decisions.md) — RPC span attributes: `xrpl.rpc.command`, `xrpl.rpc.version`, `xrpl.rpc.role`, `xrpl.rpc.params`
- [03-implementation-strategy.md §3.9.2](./03-implementation-strategy.md) — File impact: `ServerHandler.cpp` ~40 lines added, ~10 changed (Low risk)
---
## Task 7: Instrument RPC Command Execution
**Objective**: Add per-command tracing inside the RPC handler so each command (e.g., `submit`, `account_info`, `server_info`) gets its own child span.
**What to do**:
- Edit `src/xrpld/rpc/detail/RPCHandler.cpp`:
- `#include` the `TracingInstrumentation.h` header
- In `doCommand(RPC::JsonContext& context, Json::Value& result)`:
- At the top: `XRPL_TRACE_RPC(context.app.getTelemetry(), "rpc.command." + context.method);`
- Set attributes:
- `XRPL_TRACE_SET_ATTR("xrpl.rpc.command", context.method);`
- `XRPL_TRACE_SET_ATTR("xrpl.rpc.version", static_cast<int64_t>(context.apiVersion));`
- `XRPL_TRACE_SET_ATTR("xrpl.rpc.role", (context.role == Role::ADMIN) ? "admin" : "user");`
- On success: `XRPL_TRACE_SET_ATTR("xrpl.rpc.status", "success");`
- On error: `XRPL_TRACE_SET_ATTR("xrpl.rpc.status", "error");` and set the error message
- After this, traces in Tempo/Grafana should look like:
```
rpc.request (xrpl.rpc.command=account_info)
└── rpc.process
└── rpc.command.account_info (xrpl.rpc.version=2, xrpl.rpc.role=user, xrpl.rpc.status=success)
```
**Key modified file**:
- `src/xrpld/rpc/detail/RPCHandler.cpp` (~15-20 lines added)
**Reference**:
- [04-code-samples.md §4.5.3](./04-code-samples.md) — `ServerHandler::onRequest()` code sample (includes child span pattern for `rpc.command.*`)
- [02-design-decisions.md §2.3](./02-design-decisions.md) — Span naming: `rpc.command.*` pattern with dynamic command name (e.g., `rpc.command.server_info`)
- [02-design-decisions.md §2.4.2](./02-design-decisions.md) — RPC attribute schema: `xrpl.rpc.command`, `xrpl.rpc.version`, `xrpl.rpc.role`, `xrpl.rpc.status`
- [01-architecture-analysis.md §1.6](./01-architecture-analysis.md) — Key trace points table: `rpc.command.*` in `RPCHandler.cpp::doCommand()` (Priority: High)
- [02-design-decisions.md §2.6.5](./02-design-decisions.md) — Correlation with PerfLog: how `doCommand()` can link trace_id with existing PerfLog entries
- [03-implementation-strategy.md §3.4.4](./03-implementation-strategy.md) — RPC request overhead budget: ~1.75 μs total per request
---
## Task 8: Build, Run, and Verify End-to-End
> **OTLP** = OpenTelemetry Protocol
**Objective**: Prove the full pipeline works: rippled emits traces -> OTel Collector receives them -> Tempo stores them for Grafana visualization.
**What to do**:
1. **Start the Docker stack**:
```bash
docker compose -f docker/telemetry/docker-compose.yml up -d
```
Verify Collector health: `curl http://localhost:13133`
2. **Build rippled with telemetry**:
```bash
# Adjust for your actual build workflow
conan install . --build=missing -o with_telemetry=True
cmake --preset default -DXRPL_ENABLE_TELEMETRY=ON
cmake --build --preset default
```
3. **Configure rippled**:
Add to `rippled.cfg` (or your local test config):
```ini
[telemetry]
enabled=1
endpoint=localhost:4317
sampling_ratio=1.0
trace_rpc=1
```
4. **Start rippled** in standalone mode:
```bash
./rippled --conf rippled.cfg -a --start
```
5. **Generate RPC traffic**:
```bash
# server_info
curl -s -X POST http://localhost:5005 \
-H "Content-Type: application/json" \
-d '{"method":"server_info","params":[{}]}'
# ledger
curl -s -X POST http://localhost:5005 \
-H "Content-Type: application/json" \
-d '{"method":"ledger","params":[{"ledger_index":"current"}]}'
# account_info (will error in standalone, that's fine — we trace errors too)
curl -s -X POST http://localhost:5005 \
-H "Content-Type: application/json" \
-d '{"method":"account_info","params":[{"account":"rHb9CJAWyB4rj91VRWn96DkukG4bwdtyTh"}]}'
```
6. **Verify in Grafana (Tempo)**:
- Open `http://localhost:3000`
- Navigate to Explore → select Tempo datasource
- Search for service `rippled`
- Confirm you see traces with spans: `rpc.request` -> `rpc.process` -> `rpc.command.server_info`
- Click into a trace and verify attributes: `xrpl.rpc.command`, `xrpl.rpc.status`, `xrpl.rpc.version`
7. **Verify zero-overhead when disabled**:
- Rebuild with `XRPL_ENABLE_TELEMETRY=OFF`, or set `enabled=0` in config
- Run the same RPC calls
- Confirm no new traces appear and no errors in rippled logs
**Verification Checklist**:
- [ ] Docker stack starts without errors
- [ ] rippled builds with `-DXRPL_ENABLE_TELEMETRY=ON`
- [ ] rippled starts and connects to OTel Collector (check rippled logs for telemetry messages)
- [ ] Traces appear in Grafana/Tempo under service "rippled"
- [ ] Span hierarchy is correct (parent-child relationships)
- [ ] Span attributes are populated (`xrpl.rpc.command`, `xrpl.rpc.status`, etc.)
- [ ] Error spans show error status and message
- [ ] Building with `XRPL_ENABLE_TELEMETRY=OFF` produces no regressions
- [ ] Setting `enabled=0` at runtime produces no traces and no errors
**Reference**:
- [06-implementation-phases.md §6.11.1](./06-implementation-phases.md) — Phase 1 definition of done: SDK compiles, runtime toggle works, span creation verified in Tempo, config validation passes
- [06-implementation-phases.md §6.11.2](./06-implementation-phases.md#6112-phase-2-rpc-tracing) — Phase 2 definition of done: 100% RPC coverage, traceparent propagation, <1ms p99 overhead, dashboard deployed
- [06-implementation-phases.md §6.8](./06-implementation-phases.md) — Success metrics: trace coverage >95%, CPU overhead <3%, memory <5 MB, latency impact <2%
- [03-implementation-strategy.md §3.9.5](./03-implementation-strategy.md) — Backward compatibility: config optional, protocol unchanged, `XRPL_ENABLE_TELEMETRY=OFF` produces identical binary
- [01-architecture-analysis.md §1.8](./01-architecture-analysis.md) — Observable outcomes: what traces, metrics, and dashboards to expect
---
## Task 9: Document POC Results and Next Steps
> **OTLP** = OpenTelemetry Protocol | **WS** = WebSocket
**Objective**: Capture findings, screenshots, and remaining work for the team.
**What to do**:
- Take screenshots of Grafana/Tempo showing:
- The service list with "rippled"
- A trace with the full span tree
- Span detail view showing attributes
- Document any issues encountered (build issues, SDK quirks, missing attributes)
- Note performance observations (build time impact, any noticeable runtime overhead)
- Write a short summary of what the POC proves and what it doesn't cover yet:
- **Proves**: OTel SDK integrates with rippled, OTLP export works, RPC traces visible
- **Doesn't cover**: Cross-node P2P context propagation, consensus tracing, protobuf trace context, W3C traceparent header extraction, tail-based sampling, production deployment
- Outline next steps (mapping to the full plan phases):
- [Phase 2](./06-implementation-phases.md) completion: [W3C header extraction](./02-design-decisions.md) (§2.5), WebSocket tracing, all [RPC handlers](./01-architecture-analysis.md) (§1.6)
- [Phase 3](./06-implementation-phases.md): [Protobuf `TraceContext` message](./04-code-samples.md) (§4.4), [transaction relay tracing](./04-code-samples.md) (§4.5.1) across nodes
- [Phase 4](./06-implementation-phases.md): [Consensus round and phase tracing](./04-code-samples.md) (§4.5.2)
- [Phase 5](./06-implementation-phases.md): [Production collector config](./05-configuration-reference.md) (§5.5.2), [Grafana dashboards](./07-observability-backends.md) (§7.6), [alerting](./07-observability-backends.md) (§7.6.3)
**Reference**:
- [06-implementation-phases.md §6.1](./06-implementation-phases.md) — Full 5-phase timeline overview and Gantt chart
- [06-implementation-phases.md §6.10](./06-implementation-phases.md) — Crawl-Walk-Run strategy: POC is the CRAWL phase, next steps are WALK and RUN
- [06-implementation-phases.md §6.12](./06-implementation-phases.md) — Recommended implementation order (14 steps across 9 weeks)
- [03-implementation-strategy.md §3.9](./03-implementation-strategy.md) — Code intrusiveness assessment and risk matrix for each remaining component
- [07-observability-backends.md §7.2](./07-observability-backends.md) — Production backend selection (Tempo, Elastic APM, Honeycomb, Datadog)
- [02-design-decisions.md §2.5](./02-design-decisions.md) — Context propagation design: W3C HTTP headers, protobuf P2P, JobQueue internal
- [00-tracing-fundamentals.md](./00-tracing-fundamentals.md) — Reference for team onboarding on distributed tracing concepts
---
## Summary
| Task | Description | New Files | Modified Files | Depends On |
| ---- | ------------------------------------ | --------- | -------------- | ---------- |
| 0 | Docker observability stack | 4 | 0 | — |
| 1 | OTel C++ SDK dependency | 0 | 2 | — |
| 2 | Core Telemetry interface + NullImpl | 3 | 0 | 1 |
| 3 | OTel-backed Telemetry implementation | 2 | 1 | 1, 2 |
| 4 | Application lifecycle integration | 0 | 3 | 2, 3 |
| 5 | Instrumentation macros | 1 | 0 | 2 |
| 6 | Instrument RPC ServerHandler | 0 | 1 | 4, 5 |
| 7 | Instrument RPC command execution | 0 | 1 | 4, 5 |
| 8 | End-to-end verification | 0 | 0 | 0-7 |
| 9 | Document results and next steps | 1 | 0 | 8 |
**Parallel work**: Tasks 0 and 1 can run in parallel. Tasks 2 and 5 have no dependency on each other. Tasks 6 and 7 can be done in parallel once Tasks 4 and 5 are complete.
---
## Next Steps (Post-POC)
> **OTLP** = OpenTelemetry Protocol | **WS** = WebSocket
### Metrics Pipeline for Grafana Dashboards
The current POC exports **traces only**. Grafana's Explore view can query Tempo for individual traces, but time-series charts (latency histograms, request throughput, error rates) require a **metrics pipeline**. To enable this:
1. **Add a `spanmetrics` connector** to the OTel Collector config that derives RED metrics (Rate, Errors, Duration) from trace spans automatically:
```yaml
connectors:
spanmetrics:
histogram:
explicit:
buckets: [1ms, 5ms, 10ms, 25ms, 50ms, 100ms, 250ms, 500ms, 1s, 5s]
dimensions:
- name: xrpl.rpc.command
- name: xrpl.rpc.status
exporters:
prometheus:
endpoint: 0.0.0.0:8889
service:
pipelines:
traces:
receivers: [otlp]
processors: [batch]
exporters: [debug, otlp/tempo, spanmetrics]
metrics:
receivers: [spanmetrics]
exporters: [prometheus]
```
2. **Add Prometheus** to the Docker Compose stack to scrape the collector's metrics endpoint.
3. **Add Prometheus as a Grafana datasource** and build dashboards for:
- RPC request latency (p50/p95/p99) by command
- RPC throughput (requests/sec) by command
- Error rate by command
- Span duration distribution
### Additional Instrumentation
- **W3C `traceparent` header extraction** in `ServerHandler` to support cross-service context propagation from external callers
- **WebSocket RPC tracing** in `ServerHandler::onWSMessage()`
- **Transaction relay tracing** across nodes using protobuf `TraceContext` messages
- **Consensus round and phase tracing** for validator coordination visibility
- **Ledger close tracing** to measure close-to-validated latency
### Production Hardening
- **Tail-based sampling** in the OTel Collector to reduce volume while retaining error/slow traces
- **TLS configuration** for the OTLP exporter in production deployments
- **Resource limits** on the batch processor queue to prevent unbounded memory growth
- **Health monitoring** for the telemetry pipeline itself (collector lag, export failures)
### POC Lessons Learned
Issues encountered during POC implementation that inform future work:
| Issue | Resolution | Impact on Future Work |
| -------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------- | ---------------------------------------------------------------- |
| Conan lockfile rejected `opentelemetry-cpp/1.18.0` | Used `--lockfile=""` to bypass | Lockfile must be regenerated when adding new dependencies |
| Conan package only builds OTLP HTTP exporter, not gRPC | Switched from gRPC to HTTP exporter (`localhost:4318/v1/traces`) | HTTP exporter is the default; gRPC requires custom Conan profile |
| CMake target `opentelemetry-cpp::api` etc. don't exist in Conan package | Use umbrella target `opentelemetry-cpp::opentelemetry-cpp` | Conan targets differ from upstream CMake targets |
| OTel Collector `logging` exporter deprecated | Renamed to `debug` exporter | Use `debug` in all collector configs going forward |
| Macro parameter `telemetry` collided with `::xrpl::telemetry::` namespace | Renamed macro params to `_tel_obj_`, `_span_name_` | Avoid common words as macro parameter names |
| `opentelemetry::trace::Scope` creates new context on move | Store scope as member, create once in constructor | SpanGuard move semantics need care with Scope lifecycle |
| `TracerProviderFactory::Create` returns `unique_ptr<sdk::TracerProvider>`, not `nostd::shared_ptr` | Use `std::shared_ptr` member, wrap in `nostd::shared_ptr` for global provider | OTel SDK factory return types don't match API provider types |

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# Phase 2: RPC Tracing Completion Task List
> **Goal**: Complete full RPC tracing coverage with W3C Trace Context propagation, unit tests, and performance validation. Build on the POC foundation to achieve production-quality RPC observability.
>
> **Scope**: W3C header extraction, TraceContext propagation utilities, unit tests for core telemetry, integration tests for RPC tracing, and performance benchmarks.
>
> **Branch**: `pratik/otel-phase2-rpc-tracing` (from `pratik/OpenTelemetry_and_DistributedTracing_planning`)
### Related Plan Documents
| Document | Relevance |
| ------------------------------------------------------------ | ------------------------------------------------------------- |
| [04-code-samples.md](./04-code-samples.md) | TraceContextPropagator (§4.4.2), RPC instrumentation (§4.5.3) |
| [02-design-decisions.md](./02-design-decisions.md) | W3C Trace Context (§2.5), span attributes (§2.4.2) |
| [06-implementation-phases.md](./06-implementation-phases.md) | Phase 2 tasks (§6.3), definition of done (§6.11.2) |
---
## Task 2.1: Implement W3C Trace Context HTTP Header Extraction
**Objective**: Extract `traceparent` and `tracestate` headers from incoming HTTP RPC requests so external callers can propagate their trace context into rippled.
**What to do**:
- Create `include/xrpl/telemetry/TraceContextPropagator.h`:
- `extractFromHeaders(headerGetter)` - extract W3C traceparent/tracestate from HTTP headers
- `injectToHeaders(ctx, headerSetter)` - inject trace context into response headers
- Use OTel's `TextMapPropagator` with `W3CTraceContextPropagator` for standards compliance
- Only compiled when `XRPL_ENABLE_TELEMETRY` is defined
- Create `src/libxrpl/telemetry/TraceContextPropagator.cpp`:
- Implement a simple `TextMapCarrier` adapter for HTTP headers
- Use `opentelemetry::context::propagation::GlobalTextMapPropagator` for extraction/injection
- Register the W3C propagator in `TelemetryImpl::start()`
- Modify `src/xrpld/rpc/detail/ServerHandler.cpp`:
- In the HTTP request handler, extract parent context from headers before creating span
- Pass extracted context to `startSpan()` as parent
- Inject trace context into response headers
**Key new files**:
- `include/xrpl/telemetry/TraceContextPropagator.h`
- `src/libxrpl/telemetry/TraceContextPropagator.cpp`
**Key modified files**:
- `src/xrpld/rpc/detail/ServerHandler.cpp`
- `src/libxrpl/telemetry/Telemetry.cpp` (register W3C propagator)
**Reference**:
- [04-code-samples.md §4.4.2](./04-code-samples.md) — TraceContextPropagator with extractFromHeaders/injectToHeaders
- [02-design-decisions.md §2.5](./02-design-decisions.md) — W3C Trace Context propagation design
---
## Task 2.2: Add XRPL_TRACE_PEER Macro
**Objective**: Add the missing peer-tracing macro for future Phase 3 use and ensure macro completeness.
**What to do**:
- Edit `src/xrpld/telemetry/TracingInstrumentation.h`:
- Add `XRPL_TRACE_PEER(_tel_obj_, _span_name_)` macro that checks `shouldTracePeer()`
- Add `XRPL_TRACE_LEDGER(_tel_obj_, _span_name_)` macro (for future ledger tracing)
- Ensure disabled variants expand to `((void)0)`
**Key modified file**:
- `src/xrpld/telemetry/TracingInstrumentation.h`
---
## Task 2.3: Add shouldTraceLedger() to Telemetry Interface
**Objective**: The `Setup` struct has a `traceLedger` field but there's no corresponding virtual method. Add it for interface completeness.
**What to do**:
- Edit `include/xrpl/telemetry/Telemetry.h`:
- Add `virtual bool shouldTraceLedger() const = 0;`
- Update all implementations:
- `src/libxrpl/telemetry/Telemetry.cpp` (TelemetryImpl, NullTelemetryOtel)
- `src/libxrpl/telemetry/NullTelemetry.cpp` (NullTelemetry)
**Key modified files**:
- `include/xrpl/telemetry/Telemetry.h`
- `src/libxrpl/telemetry/Telemetry.cpp`
- `src/libxrpl/telemetry/NullTelemetry.cpp`
---
## Task 2.4: Unit Tests for Core Telemetry Infrastructure
**Objective**: Add unit tests for the core telemetry abstractions to validate correctness and catch regressions.
**What to do**:
- Create `src/test/telemetry/Telemetry_test.cpp`:
- Test NullTelemetry: verify all methods return expected no-op values
- Test Setup defaults: verify all Setup fields have correct defaults
- Test setup_Telemetry config parser: verify parsing of [telemetry] section
- Test enabled/disabled factory paths
- Test shouldTrace\* methods respect config flags
- Create `src/test/telemetry/SpanGuard_test.cpp`:
- Test SpanGuard RAII lifecycle (span ends on destruction)
- Test move constructor works correctly
- Test setAttribute, setOk, setStatus, addEvent, recordException
- Test context() returns valid context
- Add test files to CMake build
**Key new files**:
- `src/test/telemetry/Telemetry_test.cpp`
- `src/test/telemetry/SpanGuard_test.cpp`
**Reference**:
- [06-implementation-phases.md §6.11.1](./06-implementation-phases.md) — Phase 1 exit criteria (unit tests passing)
---
## Task 2.5: Enhance RPC Span Attributes
**Objective**: Add additional attributes to RPC spans per the semantic conventions defined in the plan.
**What to do**:
- Edit `src/xrpld/rpc/detail/ServerHandler.cpp`:
- Add `http.method` attribute for HTTP requests
- Add `http.status_code` attribute for responses
- Add `net.peer.ip` attribute for client IP (if available)
- Edit `src/xrpld/rpc/detail/RPCHandler.cpp`:
- Add `xrpl.rpc.duration_ms` attribute on completion
- Add error message attribute on failure: `xrpl.rpc.error_message`
**Key modified files**:
- `src/xrpld/rpc/detail/ServerHandler.cpp`
- `src/xrpld/rpc/detail/RPCHandler.cpp`
**Reference**:
- [02-design-decisions.md §2.4.2](./02-design-decisions.md) — RPC attribute schema
---
## Task 2.6: Build Verification and Performance Baseline
**Objective**: Verify the build succeeds with and without telemetry, and establish a performance baseline.
**What to do**:
1. Build with `telemetry=ON` and verify no compilation errors
2. Build with `telemetry=OFF` and verify no regressions
3. Run existing unit tests to verify no breakage
4. Document any build issues in lessons.md
**Verification Checklist**:
- [ ] `conan install . --build=missing -o telemetry=True` succeeds
- [ ] `cmake --preset default -Dtelemetry=ON` configures correctly
- [ ] Build succeeds with telemetry ON
- [ ] Build succeeds with telemetry OFF
- [ ] Existing tests pass with telemetry ON
- [ ] Existing tests pass with telemetry OFF
---
## Task 2.8: RPC Span Attribute Enrichment — Node Health Context
> **Source**: [External Dashboard Parity](../docs/superpowers/specs/2026-03-30-external-dashboard-parity-design.md) — adds node-level health context inspired by the community [xrpl-validator-dashboard](https://github.com/realgrapedrop/xrpl-validator-dashboard).
>
> **Downstream**: Phase 7 (MetricsRegistry uses these attributes for alerting context), Phase 10 (validation checks for these attributes).
**Objective**: Add node-level health state to every `rpc.command.*` span so operators can correlate RPC behavior with node state in Tempo.
**What to do**:
- Edit `src/xrpld/rpc/detail/RPCHandler.cpp`:
- In the `rpc.command.*` span creation block (after existing `setAttribute` calls for `xrpl.rpc.command`, `xrpl.rpc.version`, etc.):
- Add `xrpl.node.amendment_blocked` (bool) — from `context.app.getOPs().isAmendmentBlocked()`
- Add `xrpl.node.server_state` (string) — from `context.app.getOPs().strOperatingMode()`
**New span attributes**:
| Attribute | Type | Source | Example |
| ----------------------------- | ------ | ------------------------------------------- | -------- |
| `xrpl.node.amendment_blocked` | bool | `context.app.getOPs().isAmendmentBlocked()` | `true` |
| `xrpl.node.server_state` | string | `context.app.getOPs().strOperatingMode()` | `"full"` |
**Rationale**: When a node is amendment-blocked or in a degraded state, every RPC response is suspect. Tagging spans with this state enables Tempo TraceQL queries like:
```
{name=~"rpc.command.*"} | xrpl.node.amendment_blocked = true
```
This surfaces all RPCs served during a blocked period — critical for post-incident analysis.
**Key modified files**:
- `src/xrpld/rpc/detail/RPCHandler.cpp`
**Exit Criteria**:
- [ ] `rpc.command.server_info` spans carry `xrpl.node.amendment_blocked` and `xrpl.node.server_state` attributes
- [ ] No measurable latency impact (attribute values are cached atomics, not computed per-call)
- [ ] Attributes appear in Tempo trace detail view
---
## Summary
| Task | Description | New Files | Modified Files | Depends On |
| ---- | ------------------------------------------- | --------- | -------------- | ---------- |
| 2.1 | W3C Trace Context header extraction | 2 | 2 | POC |
| 2.2 | Add XRPL_TRACE_PEER/LEDGER macros | 0 | 1 | POC |
| 2.3 | Add shouldTraceLedger() interface method | 0 | 3 | POC |
| 2.4 | Unit tests for core telemetry | 2 | 1 | POC |
| 2.5 | Enhanced RPC span attributes | 0 | 2 | POC |
| 2.6 | Build verification and performance baseline | 0 | 0 | 2.1-2.5 |
| 2.8 | RPC span attribute enrichment (node health) | 0 | 1 | 2.5 |
**Parallel work**: Tasks 2.1, 2.2, 2.3 can run in parallel. Task 2.4 depends on 2.3. Task 2.5 can run in parallel with 2.4. Task 2.6 depends on all others. Task 2.8 depends on 2.5 (existing span creation must be in place).
---
## Known Issues / Future Work
### Thread safety of TelemetryImpl::stop() vs startSpan()
`TelemetryImpl::stop()` resets `sdkProvider_` (a `std::shared_ptr`) without
synchronization. `getTracer()` reads the same member from RPC handler threads.
This is a data race if any thread calls `startSpan()` concurrently with `stop()`.
**Current mitigation**: `Application::stop()` shuts down `serverHandler_`,
`overlay_`, and `jobQueue_` before calling `telemetry_->stop()`, so no callers
remain. See comments in `Telemetry.cpp:stop()` and `Application.cpp`.
**TODO**: Add an `std::atomic<bool> stopped_` flag checked in `getTracer()` to
make this robust against future shutdown order changes.
### Macro incompatibility: XRPL_TRACE_SPAN vs XRPL_TRACE_SET_ATTR
`XRPL_TRACE_SPAN` and `XRPL_TRACE_SPAN_KIND` declare `_xrpl_guard_` as a bare
`SpanGuard`, but `XRPL_TRACE_SET_ATTR` and `XRPL_TRACE_EXCEPTION` call
`_xrpl_guard_.has_value()` which requires `std::optional<SpanGuard>`. Using
`XRPL_TRACE_SPAN` followed by `XRPL_TRACE_SET_ATTR` in the same scope would
fail to compile.
**Current mitigation**: No call site currently uses `XRPL_TRACE_SPAN` — all
production code uses the conditional macros (`XRPL_TRACE_RPC`, `XRPL_TRACE_TX`,
etc.) which correctly wrap the guard in `std::optional`.
**TODO**: Either make `XRPL_TRACE_SPAN`/`XRPL_TRACE_SPAN_KIND` also wrap in
`std::optional`, or document that `XRPL_TRACE_SET_ATTR` is only compatible with
the conditional macros.

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# Phase 3: Transaction Tracing Task List
> **Goal**: Trace the full transaction lifecycle from RPC submission through peer relay, including cross-node context propagation via Protocol Buffer extensions. This is the WALK phase that demonstrates true distributed tracing.
>
> **Scope**: Protocol Buffer `TraceContext` message, context serialization, PeerImp transaction instrumentation, NetworkOPs processing instrumentation, HashRouter visibility, and multi-node relay context propagation.
>
> **Branch**: `pratik/otel-phase3-tx-tracing` (from `pratik/otel-phase2-rpc-tracing`)
### Related Plan Documents
| Document | Relevance |
| ------------------------------------------------------------ | ------------------------------------------------------------------------------------------------ |
| [04-code-samples.md](./04-code-samples.md) | TraceContext protobuf (§4.4.1), PeerImp instrumentation (§4.5.1), context serialization (§4.4.2) |
| [01-architecture-analysis.md](./01-architecture-analysis.md) | Transaction flow (§1.3), key trace points (§1.6) |
| [06-implementation-phases.md](./06-implementation-phases.md) | Phase 3 tasks (§6.4), definition of done (§6.11.3) |
| [02-design-decisions.md](./02-design-decisions.md) | Context propagation design (§2.5), attribute schema (§2.4.3) |
---
## Task 3.1: Define TraceContext Protocol Buffer Message
**Objective**: Add trace context fields to the P2P protocol messages so trace IDs can propagate across nodes.
**What to do**:
- Edit `include/xrpl/proto/xrpl.proto` (or `src/ripple/proto/ripple.proto`, wherever the proto is):
- Add `TraceContext` message definition:
```protobuf
message TraceContext {
bytes trace_id = 1; // 16-byte trace identifier
bytes span_id = 2; // 8-byte span identifier
uint32 trace_flags = 3; // bit 0 = sampled
string trace_state = 4; // W3C tracestate value
}
```
- Add `optional TraceContext trace_context = 1001;` to:
- `TMTransaction`
- `TMProposeSet` (for Phase 4 use)
- `TMValidation` (for Phase 4 use)
- Use high field numbers (1001+) to avoid conflicts with existing fields
- Regenerate protobuf C++ code
**Key modified files**:
- `include/xrpl/proto/xrpl.proto` (or equivalent)
**Reference**:
- [04-code-samples.md §4.4.1](./04-code-samples.md) — TraceContext message definition
- [02-design-decisions.md §2.5.2](./02-design-decisions.md) — Protocol buffer context propagation design
---
## Task 3.2: Implement Protobuf Context Serialization
**Objective**: Create utilities to serialize/deserialize OTel trace context to/from protobuf `TraceContext` messages.
**What to do**:
- Create `include/xrpl/telemetry/TraceContextPropagator.h` (extend from Phase 2 if exists, or add protobuf methods):
- Add protobuf-specific methods:
- `static Context extractFromProtobuf(protocol::TraceContext const& proto)` — reconstruct OTel context from protobuf fields
- `static void injectToProtobuf(Context const& ctx, protocol::TraceContext& proto)` — serialize current span context into protobuf fields
- Both methods guard behind `#ifdef XRPL_ENABLE_TELEMETRY`
- Create/extend `src/libxrpl/telemetry/TraceContextPropagator.cpp`:
- Implement extraction: read trace_id (16 bytes), span_id (8 bytes), trace_flags from protobuf, construct `SpanContext`, wrap in `Context`
- Implement injection: get current span from context, serialize its TraceId, SpanId, and TraceFlags into protobuf fields
**Key new/modified files**:
- `include/xrpl/telemetry/TraceContextPropagator.h`
- `src/libxrpl/telemetry/TraceContextPropagator.cpp`
**Reference**:
- [04-code-samples.md §4.4.2](./04-code-samples.md) — Full extract/inject implementation
---
## Task 3.3: Instrument PeerImp Transaction Handling
**Objective**: Add trace spans to the peer-level transaction receive and relay path.
**What to do**:
- Edit `src/xrpld/overlay/detail/PeerImp.cpp`:
- In `onMessage(TMTransaction)` / `handleTransaction()`:
- Extract parent trace context from incoming `TMTransaction::trace_context` field (if present)
- Create `tx.receive` span as child of extracted context (or new root if none)
- Set attributes: `xrpl.tx.hash`, `xrpl.peer.id`, `xrpl.tx.status`
- On HashRouter suppression (duplicate): set `xrpl.tx.suppressed=true`, add `tx.duplicate` event
- Wrap validation call with child span `tx.validate`
- Wrap relay with `tx.relay` span
- When relaying to peers:
- Inject current trace context into outgoing `TMTransaction::trace_context`
- Set `xrpl.tx.relay_count` attribute
- Include `TracingInstrumentation.h` and use `XRPL_TRACE_TX` macro
**Key modified files**:
- `src/xrpld/overlay/detail/PeerImp.cpp`
**Reference**:
- [04-code-samples.md §4.5.1](./04-code-samples.md) — Full PeerImp instrumentation example
- [01-architecture-analysis.md §1.3](./01-architecture-analysis.md) — Transaction flow diagram
- [01-architecture-analysis.md §1.6](./01-architecture-analysis.md) — tx.receive trace point
---
## Task 3.4: Instrument NetworkOPs Transaction Processing
**Objective**: Trace the transaction processing pipeline in NetworkOPs, covering both sync and async paths.
**What to do**:
- Edit `src/xrpld/app/misc/NetworkOPs.cpp`:
- In `processTransaction()`:
- Create `tx.process` span
- Set attributes: `xrpl.tx.hash`, `xrpl.tx.type`, `xrpl.tx.local` (whether from RPC or peer)
- Record whether sync or async path is taken
- In `doTransactionAsync()`:
- Capture parent context before queuing
- Create `tx.queue` span with queue depth attribute
- Add event when transaction is dequeued for processing
- In `doTransactionSync()`:
- Create `tx.process_sync` span
- Record result (applied, queued, rejected)
**Key modified files**:
- `src/xrpld/app/misc/NetworkOPs.cpp`
**Reference**:
- [01-architecture-analysis.md §1.6](./01-architecture-analysis.md) — tx.validate and tx.process trace points
- [02-design-decisions.md §2.4.3](./02-design-decisions.md) — Transaction attribute schema
---
## Task 3.5: Instrument HashRouter for Dedup Visibility
**Objective**: Make transaction deduplication visible in traces by recording HashRouter decisions as span attributes/events.
**What to do**:
- Edit `src/xrpld/overlay/detail/PeerImp.cpp` (in handleTransaction):
- After calling `HashRouter::shouldProcess()` or `addSuppressionPeer()`:
- Record `xrpl.tx.suppressed` attribute (true/false)
- Record `xrpl.tx.flags` showing current HashRouter state (SAVED, TRUSTED, etc.)
- Add `tx.first_seen` or `tx.duplicate` event
- This is NOT a modification to HashRouter itself — just recording its decisions as span attributes in the existing PeerImp instrumentation from Task 3.3.
**Key modified files**:
- `src/xrpld/overlay/detail/PeerImp.cpp` (same changes as 3.3, logically grouped)
---
## Task 3.6: Context Propagation in Transaction Relay
**Objective**: Ensure trace context flows correctly when transactions are relayed between peers, creating linked spans across nodes.
**What to do**:
- Verify the relay path injects trace context:
- When `PeerImp` relays a transaction, the `TMTransaction` message should carry `trace_context`
- When a remote peer receives it, the context is extracted and used as parent
- Test context propagation:
- Manually verify with 2+ node setup that trace IDs match across nodes
- Confirm parent-child span relationships are correct in Tempo
- Handle edge cases:
- Missing trace context (older peers): create new root span
- Corrupted trace context: log warning, create new root span
- Sampled-out traces: respect trace flags
**Key modified files**:
- `src/xrpld/overlay/detail/PeerImp.cpp`
- `src/xrpld/overlay/detail/OverlayImpl.cpp` (if relay method needs context param)
**Reference**:
- [02-design-decisions.md §2.5](./02-design-decisions.md) — Context propagation design
- [04-code-samples.md §4.5.1](./04-code-samples.md) — Relay context injection pattern
---
## Task 3.7: Build Verification and Testing
**Objective**: Verify all Phase 3 changes compile and work correctly.
**What to do**:
1. Build with `telemetry=ON` — verify no compilation errors
2. Build with `telemetry=OFF` — verify no regressions
3. Run existing unit tests
4. Verify protobuf regeneration produces correct C++ code
5. Document any issues encountered
**Verification Checklist**:
- [ ] Protobuf changes generate valid C++
- [ ] Build succeeds with telemetry ON
- [ ] Build succeeds with telemetry OFF
- [ ] Existing tests pass
- [ ] No undefined symbols from new telemetry calls
---
## Task 3.8: Transaction Span Peer Version Attribute
> **Source**: [External Dashboard Parity](../docs/superpowers/specs/2026-03-30-external-dashboard-parity-design.md) — adds peer version context inspired by the community [xrpl-validator-dashboard](https://github.com/realgrapedrop/xrpl-validator-dashboard).
>
> **Upstream**: Phase 2 (RPC span infrastructure must exist).
> **Downstream**: Phase 10 (validation checks for this attribute).
**Objective**: Add the relaying peer's rippled version to `tx.receive` spans so operators can correlate transaction issues with peer version mismatches during network upgrades.
**What to do**:
- Edit `src/xrpld/overlay/detail/PeerImp.cpp`:
- In the `tx.receive` span block (after existing `xrpl.peer.id` setAttribute call):
- Add `xrpl.peer.version` (string) — from `this->getVersion()`
- Only set if `getVersion()` returns a non-empty string (avoid empty-string attributes)
**New span attribute**:
| Attribute | Type | Source | Example |
| ------------------- | ------ | -------------------- | ----------------- |
| `xrpl.peer.version` | string | `peer->getVersion()` | `"rippled-2.4.0"` |
**Rationale**: Transaction relay is where version mismatches cause subtle serialization or validation bugs. Tracing "this tx came from a v2.3.0 peer" helps diagnose compatibility issues. The community dashboard tracks peer versions externally; this brings version awareness into the trace itself.
**Key modified files**:
- `src/xrpld/overlay/detail/PeerImp.cpp`
**Exit Criteria**:
- [ ] `tx.receive` spans carry `xrpl.peer.version` attribute with a non-empty version string
- [ ] Attribute is omitted (not set to empty string) when `getVersion()` returns empty
- [ ] Attribute visible in Jaeger span detail view
---
## Summary
| Task | Description | New Files | Modified Files | Depends On |
| ---- | ----------------------------------- | --------- | -------------- | ---------- |
| 3.1 | TraceContext protobuf message | 0 | 1 | Phase 2 |
| 3.2 | Protobuf context serialization | 1-2 | 0 | 3.1 |
| 3.3 | PeerImp transaction instrumentation | 0 | 1 | 3.2 |
| 3.4 | NetworkOPs transaction processing | 0 | 1 | Phase 2 |
| 3.5 | HashRouter dedup visibility | 0 | 1 | 3.3 |
| 3.6 | Relay context propagation | 0 | 1-2 | 3.3, 3.5 |
| 3.7 | Build verification and testing | 0 | 0 | 3.1-3.6 |
| 3.8 | TX span peer version attribute | 0 | 1 | 3.3 |
**Parallel work**: Tasks 3.1 and 3.4 can start in parallel. Task 3.2 depends on 3.1. Tasks 3.3 and 3.5 depend on 3.2. Task 3.6 depends on 3.3 and 3.5. Task 3.8 depends on 3.3 (span must exist).
**Exit Criteria** (from [06-implementation-phases.md §6.11.3](./06-implementation-phases.md)):
- [ ] Transaction traces span across nodes
- [ ] Trace context in Protocol Buffer messages
- [ ] HashRouter deduplication visible in traces
- [ ] <5% overhead on transaction throughput
---
## Known Issues / Future Work
### Propagation utilities not yet wired into P2P flow
`extractFromProtobuf()` and `injectToProtobuf()` in `TraceContextPropagator.h`
are implemented and tested but not called from production code. To enable
cross-node distributed traces:
- Call `injectToProtobuf()` in `PeerImp` when sending `TMTransaction` /
`TMProposeSet` messages
- Call `extractFromProtobuf()` in the corresponding message handlers to
reconstruct the parent span context, then pass it to `startSpan()` as the
parent
This was deferred to validate single-node tracing performance first.
### Unused trace_state proto field
The `TraceContext.trace_state` field (field 4) in `xrpl.proto` is reserved for
W3C `tracestate` vendor-specific key-value pairs but is not read or written by
`TraceContextPropagator`. Wire it when cross-vendor trace propagation is needed.
No wire cost since proto `optional` fields are zero-cost when absent.

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@@ -0,0 +1,896 @@
# Phase 4: Consensus Tracing Task List
> **Goal**: Full observability into consensus rounds — track round lifecycle, phase transitions, proposal handling, and validation. This is the RUN phase that completes the distributed tracing story.
>
> **Scope**: RCLConsensus instrumentation for round starts, phase transitions (open/establish/accept), proposal send/receive, validation handling, and correlation with transaction traces from Phase 3.
>
> **Branch**: `pratik/otel-phase4-consensus-tracing` (from `pratik/otel-phase3-tx-tracing`)
### Related Plan Documents
| Document | Relevance |
| ------------------------------------------------------------ | ----------------------------------------------------------- |
| [04-code-samples.md](./04-code-samples.md) | Consensus instrumentation (§4.5.2), consensus span patterns |
| [01-architecture-analysis.md](./01-architecture-analysis.md) | Consensus round flow (§1.4), key trace points (§1.6) |
| [06-implementation-phases.md](./06-implementation-phases.md) | Phase 4 tasks (§6.5), definition of done (§6.11.4) |
| [02-design-decisions.md](./02-design-decisions.md) | Consensus attribute schema (§2.4.4) |
---
## Task 4.1: Instrument Consensus Round Start
**Objective**: Create a root span for each consensus round that captures the round's key parameters.
**What to do**:
- Edit `src/xrpld/app/consensus/RCLConsensus.cpp`:
- In `RCLConsensus::startRound()` (or the Adaptor's startRound):
- Create `consensus.round` span using `XRPL_TRACE_CONSENSUS` macro
- Set attributes:
- `xrpl.consensus.ledger.prev` — previous ledger hash
- `xrpl.consensus.ledger.seq` — target ledger sequence
- `xrpl.consensus.proposers` — number of trusted proposers
- `xrpl.consensus.mode` — "proposing" or "observing"
- Store the span context for use by child spans in phase transitions
- Add a member to hold current round trace context:
- `opentelemetry::context::Context currentRoundContext_` (guarded by `#ifdef`)
- Updated at round start, used by phase transition spans
**Key modified files**:
- `src/xrpld/app/consensus/RCLConsensus.cpp`
- `src/xrpld/app/consensus/RCLConsensus.h` (add context member)
**Reference**:
- [04-code-samples.md §4.5.2](./04-code-samples.md) — startRound instrumentation example
- [01-architecture-analysis.md §1.4](./01-architecture-analysis.md) — Consensus round flow
---
## Task 4.2: Instrument Phase Transitions
**Objective**: Create child spans for each consensus phase (open, establish, accept) to show timing breakdown.
**What to do**:
- Edit `src/xrpld/app/consensus/RCLConsensus.cpp`:
- Identify where phase transitions occur (the `Consensus<Adaptor>` template drives this)
- For each phase entry:
- Create span as child of `currentRoundContext_`: `consensus.phase.open`, `consensus.phase.establish`, `consensus.phase.accept`
- Set `xrpl.consensus.phase` attribute
- Add `phase.enter` event at start, `phase.exit` event at end
- Record phase duration in milliseconds
- In the `onClose` adaptor method:
- Create `consensus.ledger_close` span
- Set attributes: close_time, mode, transaction count in initial position
- Note: The Consensus template class in `src/xrpld/consensus/Consensus.h` drives phase transitions — Phase 4a instruments directly in the template
**Key modified files**:
- `src/xrpld/app/consensus/RCLConsensus.cpp`
- Possibly `include/xrpl/consensus/Consensus.h` (for template-level phase tracking)
**Reference**:
- [04-code-samples.md §4.5.2](./04-code-samples.md) — phaseTransition instrumentation
---
## Task 4.3: Instrument Proposal Handling
**Objective**: Trace proposal send and receive to show validator coordination.
**What to do**:
- Edit `src/xrpld/app/consensus/RCLConsensus.cpp`:
- In `Adaptor::propose()`:
- Create `consensus.proposal.send` span
- Set attributes: `xrpl.consensus.round` (proposal sequence), proposal hash
- Inject trace context into outgoing `TMProposeSet::trace_context` (from Phase 3 protobuf)
- In `Adaptor::peerProposal()` (or wherever peer proposals are received):
- Extract trace context from incoming `TMProposeSet::trace_context`
- Create `consensus.proposal.receive` span as child of extracted context
- Set attributes: `xrpl.consensus.proposer` (node ID), `xrpl.consensus.round`
- In `Adaptor::share(RCLCxPeerPos)`:
- Create `consensus.proposal.relay` span for relaying peer proposals
**Key modified files**:
- `src/xrpld/app/consensus/RCLConsensus.cpp`
**Reference**:
- [04-code-samples.md §4.5.2](./04-code-samples.md) — peerProposal instrumentation
- [02-design-decisions.md §2.4.4](./02-design-decisions.md) — Consensus attribute schema
---
## Task 4.4: Instrument Validation Handling
**Objective**: Trace validation send and receive to show ledger validation flow.
**What to do**:
- Edit `src/xrpld/app/consensus/RCLConsensus.cpp` (or the validation handler):
- When sending our validation:
- Create `consensus.validation.send` span
- Set attributes: validated ledger hash, sequence, signing time
- When receiving a peer validation:
- Extract trace context from `TMValidation::trace_context` (if present)
- Create `consensus.validation.receive` span
- Set attributes: `xrpl.consensus.validator` (node ID), ledger hash
**Key modified files**:
- `src/xrpld/app/consensus/RCLConsensus.cpp`
- `src/xrpld/app/misc/NetworkOPs.cpp` (if validation handling is here)
---
## Task 4.5: Add Consensus-Specific Attributes
**Objective**: Enrich consensus spans with detailed attributes for debugging and analysis.
**What to do**:
- Review all consensus spans and ensure they include:
- `xrpl.consensus.ledger.seq` — target ledger sequence number
- `xrpl.consensus.round` — consensus round number
- `xrpl.consensus.mode` — proposing/observing/wrongLedger
- `xrpl.consensus.phase` — current phase name
- `xrpl.consensus.phase_duration_ms` — time spent in phase
- `xrpl.consensus.proposers` — number of trusted proposers
- `xrpl.consensus.tx_count` — transactions in proposed set
- `xrpl.consensus.disputes` — number of disputed transactions
- `xrpl.consensus.converge_percent` — convergence percentage
**Key modified files**:
- `src/xrpld/app/consensus/RCLConsensus.cpp`
---
## Task 4.6: Correlate Transaction and Consensus Traces
**Objective**: Link transaction traces from Phase 3 with consensus traces so you can follow a transaction from submission through consensus into the ledger.
**What to do**:
- In `onClose()` or `onAccept()`:
- When building the consensus position, link the round span to individual transaction spans using span links (if OTel SDK supports it) or events
- At minimum, record the transaction hashes included in the consensus set as span events: `tx.included` with `xrpl.tx.hash` attribute
- In `processTransactionSet()` (NetworkOPs):
- If the consensus round span context is available, create child spans for each transaction applied to the ledger
**Key modified files**:
- `src/xrpld/app/consensus/RCLConsensus.cpp`
- `src/xrpld/app/misc/NetworkOPs.cpp`
---
## Task 4.7: Build Verification and Testing
**Objective**: Verify all Phase 4 changes compile and don't affect consensus timing.
**What to do**:
1. Build with `telemetry=ON` — verify no compilation errors
2. Build with `telemetry=OFF` — verify no regressions (critical for consensus code)
3. Run existing consensus-related unit tests
4. Verify that all macros expand to no-ops when disabled
5. Check that no consensus-critical code paths are affected by instrumentation overhead
**Verification Checklist**:
- [ ] Build succeeds with telemetry ON
- [ ] Build succeeds with telemetry OFF
- [ ] Existing consensus tests pass
- [ ] No new includes in consensus headers when telemetry is OFF
- [ ] Phase timing instrumentation doesn't use blocking operations
---
## Task 4.8: Consensus Validation Span Enrichment — External Dashboard Parity
> **Source**: [External Dashboard Parity](../docs/superpowers/specs/2026-03-30-external-dashboard-parity-design.md) — adds validation agreement context inspired by the community [xrpl-validator-dashboard](https://github.com/realgrapedrop/xrpl-validator-dashboard).
>
> **Upstream**: Phase 4 tasks 4.1-4.4 (span creation must exist).
> **Downstream**: Phase 7 (ValidationTracker reads these attributes), Phase 10 (validation checks).
**Objective**: Add ledger hash, validation type, and quorum data to consensus validation spans on both send and receive paths. This enables trace-level validation agreement analysis — filter by ledger hash to see which validators agreed for a given ledger.
**What to do**:
- Edit `src/xrpld/app/consensus/RCLConsensus.cpp`:
- On the `consensus.validation.send` span (in `validate()` / `doAccept()`):
- Add `xrpl.validation.ledger_hash` (string) — the ledger hash being validated
- Add `xrpl.validation.full` (bool) — whether this is a full validation (not partial)
- On the `consensus.accept` span (in `onAccept()`):
- Add `xrpl.consensus.validation_quorum` (int64) — from `app_.validators().quorum()`
- Add `xrpl.consensus.proposers_validated` (int64) — from `result.proposers`
- Edit `src/xrpld/overlay/detail/PeerImp.cpp`:
- On the `peer.validation.receive` span:
- Add `xrpl.peer.validation.ledger_hash` (string) — from deserialized `STValidation` object
- Add `xrpl.peer.validation.full` (bool) — from `STValidation` flags
**New span attributes**:
| Span | Attribute | Type | Source |
| --------------------------- | ------------------------------------ | ------ | --------------------------------- |
| `consensus.validation.send` | `xrpl.validation.ledger_hash` | string | Ledger hash from validate() args |
| `consensus.validation.send` | `xrpl.validation.full` | bool | Full vs partial validation |
| `peer.validation.receive` | `xrpl.peer.validation.ledger_hash` | string | From STValidation deserialization |
| `peer.validation.receive` | `xrpl.peer.validation.full` | bool | From STValidation flags |
| `consensus.accept` | `xrpl.consensus.validation_quorum` | int64 | `app_.validators().quorum()` |
| `consensus.accept` | `xrpl.consensus.proposers_validated` | int64 | `result.proposers` |
**Rationale**: The external dashboard's most valuable feature is validation agreement tracking. By recording the ledger hash on both outgoing and incoming validation spans, we create the raw data for agreement analysis at the trace level. Example Tempo query:
```
{name="consensus.validation.send"} | xrpl.validation.ledger_hash = "A1B2C3..."
```
Phase 7's `ValidationTracker` builds metric-level aggregation (1h/24h agreement %) on top of this data.
**Key modified files**:
- `src/xrpld/app/consensus/RCLConsensus.cpp`
- `src/xrpld/overlay/detail/PeerImp.cpp`
**Exit Criteria**:
- [ ] `consensus.validation.send` spans carry `xrpl.validation.ledger_hash` and `xrpl.validation.full`
- [ ] `peer.validation.receive` spans carry `xrpl.peer.validation.ledger_hash` and `xrpl.peer.validation.full`
- [ ] `consensus.accept` spans carry `xrpl.consensus.validation_quorum` and `xrpl.consensus.proposers_validated`
- [ ] Ledger hash attributes match between send and receive for the same ledger
- [ ] No impact on consensus performance
---
## Summary
| Task | Description | New Files | Modified Files | Depends On |
| ---- | ------------------------------------------- | --------- | -------------- | ------------- |
| 4.1 | Consensus round start instrumentation | 0 | 2 | Phase 3 |
| 4.2 | Phase transition instrumentation | 0 | 1-2 | 4.1 |
| 4.3 | Proposal handling instrumentation | 0 | 1 | 4.1 |
| 4.4 | Validation handling instrumentation | 0 | 1-2 | 4.1 |
| 4.5 | Consensus-specific attributes | 0 | 1 | 4.2, 4.3, 4.4 |
| 4.6 | Transaction-consensus correlation | 0 | 2 | 4.2, Phase 3 |
| 4.7 | Build verification and testing | 0 | 0 | 4.1-4.6 |
| 4.8 | Validation span enrichment (ext. dashboard) | 0 | 2 | 4.4 |
**Parallel work**: Tasks 4.2, 4.3, and 4.4 can run in parallel after 4.1 is complete. Task 4.5 depends on all three. Task 4.6 depends on 4.2 and Phase 3. Task 4.8 depends on 4.4 (validation spans must exist).
### Implemented Spans
| Span Name | Method | Key Attributes |
| --------------------------- | ---------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `consensus.proposal.send` | `Adaptor::propose` | `xrpl.consensus.round` |
| `consensus.ledger_close` | `Adaptor::onClose` | `xrpl.consensus.ledger.seq`, `xrpl.consensus.mode` |
| `consensus.accept` | `Adaptor::onAccept` | `xrpl.consensus.proposers`, `xrpl.consensus.round_time_ms` |
| `consensus.accept.apply` | `Adaptor::doAccept` | `xrpl.consensus.close_time`, `close_time_correct`, `close_resolution_ms`, `state`, `proposing`, `round_time_ms`, `ledger.seq`, `parent_close_time`, `close_time_self`, `close_time_vote_bins`, `resolution_direction` |
| `consensus.validation.send` | `Adaptor::onAccept` (via validate) | `xrpl.consensus.proposing` |
#### Close Time Attributes (consensus.accept.apply)
The `consensus.accept.apply` span captures ledger close time agreement details
driven by `avCT_CONSENSUS_PCT` (75% validator agreement threshold):
- **`xrpl.consensus.close_time`** — Agreed-upon ledger close time (epoch seconds). When validators disagree (`consensusCloseTime == epoch`), this is synthetically set to `prevCloseTime + 1s`.
- **`xrpl.consensus.close_time_correct`** — `true` if validators reached agreement, `false` if they "agreed to disagree" (close time forced to prev+1s).
- **`xrpl.consensus.close_resolution_ms`** — Rounding granularity for close time (starts at 30s, decreases as ledger interval stabilizes).
- **`xrpl.consensus.state`** — `"finished"` (normal) or `"moved_on"` (consensus failed, adopted best available).
- **`xrpl.consensus.proposing`** — Whether this node was proposing.
- **`xrpl.consensus.round_time_ms`** — Total consensus round duration.
- **`xrpl.consensus.parent_close_time`** — Previous ledger's close time (epoch seconds). Enables computing close-time deltas across consecutive rounds without correlating separate spans.
- **`xrpl.consensus.close_time_self`** — This node's own proposed close time before consensus voting.
- **`xrpl.consensus.close_time_vote_bins`** — Number of distinct close-time vote bins from peer proposals. Higher values indicate less agreement among validators.
- **`xrpl.consensus.resolution_direction`** — Whether close-time resolution `"increased"` (coarser), `"decreased"` (finer), or stayed `"unchanged"` relative to the previous ledger.
**Exit Criteria** (from [06-implementation-phases.md §6.11.4](./06-implementation-phases.md)):
- [x] Complete consensus round traces
- [x] Phase transitions visible
- [x] Proposals and validations traced
- [x] Close time agreement tracked (per `avCT_CONSENSUS_PCT`)
- [x] No impact on consensus timing
---
# Phase 4a: Establish-Phase Gap Fill & Cross-Node Correlation
> **Goal**: Fill tracing gaps in the consensus establish phase (disputes, convergence,
> threshold escalation, mode changes) and establish cross-node correlation using a
> deterministic shared trace ID derived from `previousLedger.id()`.
>
> **Approach**: Direct instrumentation in `Consensus.h` — the generic consensus
> template has full access to internal state (`convergePercent_`, `result_->disputes`,
> `mode_`, threshold logic). Telemetry access comes via a single new adaptor
> method `getTelemetry()`. Long-lived spans (round, establish) are stored as
> class members using `SpanGuard` directly — NOT the `XRPL_TRACE_*` convenience
> macros (which create local variables named `_xrpl_guard_`). Short-lived
> scoped spans (update_positions, check) can use the macros. All code compiles
> to no-ops when `XRPL_ENABLE_TELEMETRY` is not defined.
>
> **Branch**: `pratik/otel-phase4-consensus-tracing`
## Design: Switchable Correlation Strategy
Two strategies for cross-node trace correlation, switchable via config:
### Strategy A — Deterministic Trace ID (Default)
Derive `trace_id = SHA256(previousLedger.id())[0:16]` so all nodes in the same
consensus round share the same trace_id without P2P context propagation.
- **Pros**: All nodes appear in the same trace in Tempo/Jaeger automatically.
No collector-side post-processing needed.
- **Cons**: Overrides OTel's random trace_id generation; requires custom
`IdGenerator` or manual span context construction.
### Strategy B — Attribute-Based Correlation
Use normal random trace_id but attach `xrpl.consensus.ledger_id` as an attribute
on every consensus span. Correlation happens at query time via Tempo/Grafana
`by attribute` queries.
- **Pros**: Standard OTel trace_id semantics; no SDK customization.
- **Cons**: Cross-node correlation requires query-time joins, not automatic.
### Config
```ini
[telemetry]
# "deterministic" (default) or "attribute"
consensus_trace_strategy=deterministic
```
### Implementation
In `RCLConsensus::Adaptor::startRound()`:
- If `deterministic`:
1. Compute `trace_id_bytes = SHA256(prevLedgerID)[0:16]`
2. Construct `opentelemetry::trace::TraceId(trace_id_bytes)`
3. Create a synthetic `SpanContext` with this trace_id and a random span_id:
```cpp
auto traceId = opentelemetry::trace::TraceId(trace_id_bytes);
auto spanId = opentelemetry::trace::SpanId(random_8_bytes);
auto syntheticCtx = opentelemetry::trace::SpanContext(
traceId, spanId, opentelemetry::trace::TraceFlags(1), false);
```
4. Wrap in `opentelemetry::context::Context` via
`opentelemetry::trace::SetSpan(context, syntheticSpan)`
5. Call `startSpan("consensus.round", parentContext)` so the new span
inherits the deterministic trace_id.
- If `attribute`: start a normal `consensus.round` span, set
`xrpl.consensus.ledger_id = previousLedger.id()` as attribute.
Both strategies always set `xrpl.consensus.round_id` (round number) and
`xrpl.consensus.ledger_id` (previous ledger hash) as attributes.
---
## Design: Span Hierarchy
```
consensus.round (root — created in RCLConsensus::startRound, closed at accept)
│ link → previous round's SpanContext (follows-from)
├── consensus.establish (phaseEstablish → acceptance, in Consensus.h)
│ ├── consensus.update_positions (each updateOurPositions call)
│ │ └── consensus.dispute.resolve (per-tx dispute resolution event)
│ ├── consensus.check (each haveConsensus call)
│ └── consensus.mode_change (short-lived span in adaptor on mode transition)
├── consensus.accept (existing onAccept span — reparented under round)
└── consensus.validation.send (existing — reparented, follows-from link to round)
```
### Span Links (follows-from relationships)
| Link Source | Link Target | Rationale |
| ----------------------------------------- | -------------------------- | ------------------------------------------------------------------------------ |
| `consensus.round` (N+1) | `consensus.round` (N) | Causal chain: round N+1 exists because round N accepted |
| `consensus.validation.send` | `consensus.round` | Validation follows from the round that produced it; may outlive the round span |
| _(Phase 4b)_ Received proposal processing | Sender's `consensus.round` | Cross-node causal link via P2P context propagation |
---
## Task 4a.0: Prerequisites — Extend SpanGuard and Telemetry APIs
**Objective**: Add missing API surface needed by later tasks.
**What to do**:
1. **Add `SpanGuard::addEvent()` with attributes** (needed by Task 4a.5):
The current `addEvent(string_view name)` only accepts a name. Add an
overload that accepts key-value attributes:
```cpp
void addEvent(std::string_view name,
std::initializer_list<
std::pair<opentelemetry::nostd::string_view,
opentelemetry::common::AttributeValue>> attributes)
{
span_->AddEvent(std::string(name), attributes);
}
```
2. **Add a `Telemetry::startSpan()` overload that accepts span links** (needed by Tasks 4a.2, 4a.8):
The current `startSpan()` has no span link support. Add an overload that
accepts a vector of `SpanContext` links for follows-from relationships:
```cpp
virtual opentelemetry::nostd::shared_ptr<opentelemetry::trace::Span>
startSpan(
std::string_view name,
opentelemetry::context::Context const& parentContext,
std::vector<opentelemetry::trace::SpanContext> const& links,
opentelemetry::trace::SpanKind kind = opentelemetry::trace::SpanKind::kInternal) = 0;
```
3. **Add `XRPL_TRACE_ADD_EVENT` macro** (needed by Task 4a.5):
Add to `TracingInstrumentation.h` to expose `addEvent(name, attrs)` through
the macro interface (consistent with `XRPL_TRACE_SET_ATTR` pattern):
```cpp
#ifdef XRPL_ENABLE_TELEMETRY
#define XRPL_TRACE_ADD_EVENT(name, ...) \
if (_xrpl_guard_.has_value()) \
{ \
_xrpl_guard_->addEvent(name, __VA_ARGS__); \
}
#else
#define XRPL_TRACE_ADD_EVENT(name, ...) ((void)0)
#endif
```
**Key modified files**:
- `include/xrpl/telemetry/SpanGuard.h` — add `addEvent()` overload
- `include/xrpl/telemetry/Telemetry.h` — add `startSpan()` with links
- `src/xrpld/telemetry/Telemetry.cpp` — implement new overload
- `src/xrpld/telemetry/NullTelemetry.cpp` — no-op implementation
- `src/xrpld/telemetry/TracingInstrumentation.h` — add `XRPL_TRACE_ADD_EVENT` macro
---
## Task 4a.1: Adaptor `getTelemetry()` Method
**Objective**: Give `Consensus.h` access to the telemetry subsystem without
coupling the generic template to OTel headers.
**What to do**:
- Add `getTelemetry()` method to the Adaptor concept (returns
`xrpl::telemetry::Telemetry&`). The return type is already forward-declared
behind `#ifdef XRPL_ENABLE_TELEMETRY`.
- Implement in `RCLConsensus::Adaptor` — delegates to `app_.getTelemetry()`.
- In `Consensus.h`, the `XRPL_TRACE_*` macros call
`adaptor_.getTelemetry()` — when telemetry is disabled, the macros expand to
`((void)0)` and the method is never called.
**Key modified files**:
- `src/xrpld/app/consensus/RCLConsensus.h` — declare `getTelemetry()`
- `src/xrpld/app/consensus/RCLConsensus.cpp` — implement `getTelemetry()`
---
## Task 4a.2: Switchable Round Span with Deterministic Trace ID
**Objective**: Create a `consensus.round` root span in `startRound()` that uses
the switchable correlation strategy. Store span context as a member for child
spans in `Consensus.h`.
**What to do**:
- In `RCLConsensus::Adaptor::startRound()` (or a new helper):
- Read `consensus_trace_strategy` from config.
- **Deterministic**: compute `trace_id = SHA256(prevLedgerID)[0:16]`.
Construct a `SpanContext` with this trace_id, then start
`consensus.round` span as child of that context.
- **Attribute**: start normal `consensus.round` span.
- Set attributes on both: `xrpl.consensus.round_id`,
`xrpl.consensus.ledger_id`, `xrpl.consensus.ledger.seq`,
`xrpl.consensus.mode`.
- Store the round span in `Consensus` as a member (see Task 4a.3).
- If a previous round's span context is available, add a **span link**
(follows-from) to establish the round chain.
- Add `createDeterministicTraceId(hash)` utility to
`include/xrpl/telemetry/Telemetry.h` (returns 16-byte trace ID from a
256-bit hash by truncation).
- Add `consensus_trace_strategy` to `Telemetry::Setup` and
`TelemetryConfig.cpp` parser:
```cpp
/** Cross-node correlation strategy: "deterministic" or "attribute". */
std::string consensusTraceStrategy = "deterministic";
```
**Key modified files**:
- `src/xrpld/app/consensus/RCLConsensus.cpp`
- `include/xrpl/telemetry/Telemetry.h` — `createDeterministicTraceId()`
- `src/xrpld/telemetry/TelemetryConfig.cpp` — parse new config option
---
## Task 4a.3: Span Members in `Consensus.h`
**Objective**: Add span storage to the `Consensus` class so that spans created
in `startRound()` (adaptor) are accessible from `phaseEstablish()`,
`updateOurPositions()`, and `haveConsensus()` (template methods).
**What to do**:
- Add to `Consensus` private members (guarded by `#ifdef XRPL_ENABLE_TELEMETRY`):
```cpp
#ifdef XRPL_ENABLE_TELEMETRY
std::optional<xrpl::telemetry::SpanGuard> roundSpan_;
std::optional<xrpl::telemetry::SpanGuard> establishSpan_;
opentelemetry::context::Context prevRoundContext_;
#endif
```
- `roundSpan_` is created in `startRound()` via the adaptor and stored.
Its `SpanGuard::Scope` member keeps the span active on the thread context
for the entire round lifetime.
- `establishSpan_` is created when entering phaseEstablish and cleared on accept.
It becomes a child of `roundSpan_` via OTel's thread-local context propagation.
- `prevRoundContext_` stores the previous round's context for follows-from links.
**Threading assumption**: `startRound()`, `phaseEstablish()`, `updateOurPositions()`,
and `haveConsensus()` all run on the same thread (the consensus job queue thread).
This is required for the `SpanGuard::Scope`-based parent-child hierarchy to work.
The `Consensus` class documentation confirms it is NOT thread-safe and calls are
serialized by the application.
- Add conditional include at top of `Consensus.h`:
```cpp
#ifdef XRPL_ENABLE_TELEMETRY
#include <xrpl/telemetry/SpanGuard.h>
#include <xrpld/telemetry/TracingInstrumentation.h>
#endif
```
**Key modified files**:
- `src/xrpld/consensus/Consensus.h`
---
## Task 4a.4: Instrument `phaseEstablish()`
**Objective**: Create `consensus.establish` span wrapping the establish phase,
with attributes for convergence progress.
**What to do**:
- At the start of `phaseEstablish()` (line 1298), if `establishSpan_` is not
yet created, create it as child of `roundSpan_` using the **direct API**
(NOT the `XRPL_TRACE_CONSENSUS` macro, which creates a local variable):
```cpp
#ifdef XRPL_ENABLE_TELEMETRY
if (!establishSpan_ && adaptor_.getTelemetry().shouldTraceConsensus())
{
establishSpan_.emplace(
adaptor_.getTelemetry().startSpan("consensus.establish"));
}
#endif
```
- Set attributes on each call:
- `xrpl.consensus.converge_percent` — `convergePercent_`
- `xrpl.consensus.establish_count` — `establishCounter_`
- `xrpl.consensus.proposers` — `currPeerPositions_.size()`
- On phase exit (transition to accept), close the establish span and record
final duration.
**Key modified files**:
- `src/xrpld/consensus/Consensus.h` — `phaseEstablish()` method
---
## Task 4a.5: Instrument `updateOurPositions()`
**Objective**: Trace each position update cycle including dispute resolution
details.
**What to do**:
- At the start of `updateOurPositions()` (line 1418), create a scoped child
span. This method is called and returns within a single `phaseEstablish()`
call, so the `XRPL_TRACE_CONSENSUS` macro works here (scoped local):
```cpp
XRPL_TRACE_CONSENSUS(adaptor_.getTelemetry(), "consensus.update_positions");
```
- Set attributes:
- `xrpl.consensus.disputes_count` — `result_->disputes.size()`
- `xrpl.consensus.converge_percent` — current convergence
- `xrpl.consensus.proposers_agreed` — count of peers with same position
- `xrpl.consensus.proposers_total` — total peer positions
- Inside the dispute resolution loop, for each dispute that changes our vote,
add an **event** with attributes using `XRPL_TRACE_ADD_EVENT` (from Task 4a.0):
```cpp
XRPL_TRACE_ADD_EVENT("dispute.resolve", {
{"xrpl.tx.id", std::string(tx_id)},
{"xrpl.dispute.our_vote", our_vote},
{"xrpl.dispute.yays", static_cast<int64_t>(yays)},
{"xrpl.dispute.nays", static_cast<int64_t>(nays)}
});
```
**Key modified files**:
- `src/xrpld/consensus/Consensus.h` — `updateOurPositions()` method
---
## Task 4a.6: Instrument `haveConsensus()` (Threshold & Convergence)
**Objective**: Trace consensus checking including threshold escalation
(`ConsensusParms::AvalancheState::{init, mid, late, stuck}`).
**What to do**:
- At the start of `haveConsensus()` (line 1598), create a scoped child span:
```cpp
XRPL_TRACE_CONSENSUS(adaptor_.getTelemetry(), "consensus.check");
```
- Set attributes:
- `xrpl.consensus.agree_count` — peers that agree with our position
- `xrpl.consensus.disagree_count` — peers that disagree
- `xrpl.consensus.converge_percent` — convergence percentage
- `xrpl.consensus.result` — ConsensusState result (Yes/No/MovedOn)
- The free function `checkConsensus()` in `Consensus.cpp` (line 151) determines
thresholds based on `currentAgreeTime`. Threshold values come from
`ConsensusParms::avalancheCutoffs` (defined in `ConsensusParms.h`).
The escalation states are `ConsensusParms::AvalancheState::{init, mid, late, stuck}`.
Record the effective threshold as an attribute on the span:
- `xrpl.consensus.threshold_percent` — current threshold from `avalancheCutoffs`
**Key modified files**:
- `src/xrpld/consensus/Consensus.h` — `haveConsensus()` method
---
## Task 4a.7: Instrument Mode Changes
**Objective**: Trace consensus mode transitions (proposing ↔ observing,
wrongLedger, switchedLedger).
**What to do**:
Mode changes are rare (typically 0-1 per round), so a **standalone short-lived
span** is appropriate (not an event). This captures timing of the mode change
itself.
- In `RCLConsensus::Adaptor::onModeChange()`, create a scoped span:
```cpp
XRPL_TRACE_CONSENSUS(app_.getTelemetry(), "consensus.mode_change");
XRPL_TRACE_SET_ATTR("xrpl.consensus.mode.old", to_string(before).c_str());
XRPL_TRACE_SET_ATTR("xrpl.consensus.mode.new", to_string(after).c_str());
```
- Note: `MonitoredMode::set()` (line 304 in `Consensus.h`) calls
`adaptor_.onModeChange(before, after)` — so the span is created in the
adaptor, which already has telemetry access. No instrumentation needed
in `Consensus.h` for this task.
**Key modified files**:
- `src/xrpld/app/consensus/RCLConsensus.cpp` — `onModeChange()`
---
## Task 4a.8: Reparent Existing Spans Under Round
**Objective**: Make existing consensus spans (`consensus.accept`,
`consensus.accept.apply`, `consensus.validation.send`) children of the
`consensus.round` root span instead of being standalone.
**What to do**:
- The existing spans in `onAccept()`, `doAccept()`, and `validate()` use
`XRPL_TRACE_CONSENSUS(app_.getTelemetry(), ...)` which creates standalone
spans on the current thread's context.
- After Task 4a.2 creates the round span and stores it, these methods run on
the same thread within the round span's scope, so they automatically become
children. Verify this works correctly.
- For `consensus.validation.send`: add a **span link** (follows-from) to the
round span context, since the validation may be processed after the round
completes.
**Key modified files**:
- `src/xrpld/app/consensus/RCLConsensus.cpp` — verify parent-child hierarchy
---
## Task 4a.9: Build Verification and Testing
**Objective**: Verify all Phase 4a changes compile cleanly with telemetry ON
and OFF, and don't affect consensus timing.
**What to do**:
1. Build with `telemetry=ON` — verify no compilation errors
2. Build with `telemetry=OFF` — verify macros expand to no-ops, no new includes
leak into `Consensus.h` when disabled
3. Run existing consensus unit tests
4. Verify `#ifdef XRPL_ENABLE_TELEMETRY` guards on all new members in
`Consensus.h`
5. Run `pccl` pre-commit checks
**Verification Checklist**:
- [x] Build succeeds with telemetry ON
- [x] Build succeeds with telemetry OFF
- [x] Existing consensus tests pass
- [x] `Consensus.h` has zero OTel includes when telemetry is OFF
- [x] No new virtual calls in hot consensus paths
- [x] `pccl` passes
---
## Phase 4a Summary
| Task | Description | New Files | Modified Files | Depends On |
| ---- | ------------------------------------------------ | --------- | -------------- | ---------- |
| 4a.0 | Prerequisites: extend SpanGuard & Telemetry APIs | 0 | 4 | Phase 4 |
| 4a.1 | Adaptor `getTelemetry()` method | 0 | 2 | Phase 4 |
| 4a.2 | Switchable round span with deterministic traceID | 0 | 3 | 4a.0, 4a.1 |
| 4a.3 | Span members in `Consensus.h` | 0 | 1 | 4a.1 |
| 4a.4 | Instrument `phaseEstablish()` | 0 | 1 | 4a.3 |
| 4a.5 | Instrument `updateOurPositions()` | 0 | 1 | 4a.0, 4a.3 |
| 4a.6 | Instrument `haveConsensus()` (thresholds) | 0 | 1 | 4a.3 |
| 4a.7 | Instrument mode changes | 0 | 1 | 4a.1 |
| 4a.8 | Reparent existing spans under round | 0 | 1 | 4a.0, 4a.2 |
| 4a.9 | Build verification and testing | 0 | 0 | 4a.0-4a.8 |
**Parallel work**: Tasks 4a.0 and 4a.1 can run in parallel. Tasks 4a.4, 4a.5, 4a.6, and 4a.7 can run in parallel after 4a.3 (and 4a.0 for 4a.5).
### New Spans (Phase 4a)
| Span Name | Location | Key Attributes |
| ---------------------------- | ------------------ | ---------------------------------------------------------------------------------- |
| `consensus.round` | `RCLConsensus.cpp` | `round_id`, `ledger_id`, `ledger.seq`, `mode`; link → prev round |
| `consensus.establish` | `Consensus.h` | `converge_percent`, `establish_count`, `proposers` |
| `consensus.update_positions` | `Consensus.h` | `disputes_count`, `converge_percent`, `proposers_agreed`, `proposers_total` |
| `consensus.check` | `Consensus.h` | `agree_count`, `disagree_count`, `converge_percent`, `result`, `threshold_percent` |
| `consensus.mode_change` | `RCLConsensus.cpp` | `mode.old`, `mode.new` |
### New Events (Phase 4a)
| Event Name | Parent Span | Attributes |
| ----------------- | ---------------------------- | ----------------------------------- |
| `dispute.resolve` | `consensus.update_positions` | `tx_id`, `our_vote`, `yays`, `nays` |
### New Attributes (Phase 4a)
```cpp
// Round-level (on consensus.round)
"xrpl.consensus.round_id" = int64 // Consensus round number
"xrpl.consensus.ledger_id" = string // previousLedger.id() hash
"xrpl.consensus.trace_strategy" = string // "deterministic" or "attribute"
// Establish-level
"xrpl.consensus.converge_percent" = int64 // Convergence % (0-100+)
"xrpl.consensus.establish_count" = int64 // Number of establish iterations
"xrpl.consensus.disputes_count" = int64 // Active disputes
"xrpl.consensus.proposers_agreed" = int64 // Peers agreeing with us
"xrpl.consensus.proposers_total" = int64 // Total peer positions
"xrpl.consensus.agree_count" = int64 // Peers that agree (haveConsensus)
"xrpl.consensus.disagree_count" = int64 // Peers that disagree
"xrpl.consensus.threshold_percent" = int64 // Current threshold (50/65/70/95)
"xrpl.consensus.result" = string // "yes", "no", "moved_on"
// Mode change
"xrpl.consensus.mode.old" = string // Previous mode
"xrpl.consensus.mode.new" = string // New mode
```
### Implementation Notes
- **Separation of concerns**: All non-trivial telemetry code extracted to private
helpers (`startRoundTracing`, `createValidationSpan`, `startEstablishTracing`,
`updateEstablishTracing`, `endEstablishTracing`). Business logic methods contain
only single-line `#ifdef` blocks calling these helpers.
- **Thread safety**: `createValidationSpan()` runs on the jtACCEPT worker thread.
Instead of accessing `roundSpan_` across threads, a `roundSpanContext_` snapshot
(lightweight `SpanContext` value type) is captured on the consensus thread in
`startRoundTracing()` and read by `createValidationSpan()`. The job queue
provides the happens-before guarantee.
- **Macro safety**: `XRPL_TRACE_ADD_EVENT` uses `do { } while (0)` to prevent
dangling-else issues.
- **Config validation**: `consensus_trace_strategy` is validated to be either
`"deterministic"` or `"attribute"`, falling back to `"deterministic"` for
unrecognised values.
- **Plan deviation**: `roundSpan_` is stored in `RCLConsensus::Adaptor` (not
`Consensus.h`) because the adaptor has access to telemetry config and can
implement the deterministic trace ID strategy. `establishSpan_` is correctly
in `Consensus.h` as planned.
---
# Phase 4b: Cross-Node Propagation (Future — Documentation Only)
> **Goal**: Wire `TraceContextPropagator` for P2P messages so that proposals
> and validations carry trace context between nodes. This enables true
> distributed tracing where a proposal sent by Node A creates a child span
> on Node B.
>
> **Status**: NOT IMPLEMENTED. The protobuf fields and propagator class exist
> but are not wired. This section documents the design for future work.
## Architecture
```
Node A (proposing) Node B (receiving)
───────────────── ──────────────────
consensus.round consensus.round
├── propose() ├── peerProposal()
│ └── TraceContextPropagator │ └── TraceContextPropagator
│ ::injectToProtobuf( │ ::extractFromProtobuf(
│ TMProposeSet.trace_context) │ TMProposeSet.trace_context)
│ │ └── span link → Node A's context
└── validate() └── onValidation()
└── inject into TMValidation └── extract from TMValidation
```
## Wiring Points
| Message | Inject Location | Extract Location | Protobuf Field |
| --------------- | ---------------------------------- | ----------------------------------- | -------------------------- |
| `TMProposeSet` | `Adaptor::propose()` | `PeerImp::onMessage(TMProposeSet)` | field 1001: `TraceContext` |
| `TMValidation` | `Adaptor::validate()` | `PeerImp::onMessage(TMValidation)` | field 1001: `TraceContext` |
| `TMTransaction` | `NetworkOPs::processTransaction()` | `PeerImp::onMessage(TMTransaction)` | field 1001: `TraceContext` |
## Span Link Semantics
Received messages use **span links** (follows-from), NOT parent-child:
- The receiver's processing span links to the sender's context
- This preserves each node's independent trace tree
- Cross-node correlation visible via linked traces in Tempo/Jaeger
## Interaction with Deterministic Trace ID (Strategy A)
When using deterministic trace_id (Phase 4a default), cross-node spans already
share the same trace_id. P2P propagation adds **span-level** linking:
- Without propagation: spans from different nodes appear in the same trace
(same trace_id) but without parent-child or follows-from relationships.
- With propagation: spans have explicit links showing which proposal/validation
from Node A caused processing on Node B.
## Prerequisites
- Phase 4a (this task list) — establish phase tracing must be in place
- `TraceContextPropagator` class (already exists in
`include/xrpl/telemetry/TraceContextPropagator.h`)
- Protobuf `TraceContext` message (already exists, field 1001)

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# Phase 5: Integration Test Task List
> **Goal**: End-to-end verification of the complete telemetry pipeline using a
> 6-node consensus network. Proves that RPC, transaction, and consensus spans
> flow through the observability stack (otel-collector, Tempo, Prometheus,
> Grafana) under realistic conditions.
>
> **Scope**: Integration test script, manual testing plan, 6-node local network
> setup, Tempo/Prometheus/Grafana verification.
>
> **Branch**: `pratik/otel-phase5-docs-deployment`
### Related Plan Documents
| Document | Relevance |
| ---------------------------------------------------------------- | ------------------------------------------ |
| [07-observability-backends.md](./07-observability-backends.md) | Tempo, Grafana, Prometheus setup |
| [05-configuration-reference.md](./05-configuration-reference.md) | Collector config, Docker Compose |
| [06-implementation-phases.md](./06-implementation-phases.md) | Phase 5 tasks, definition of done |
| [Phase5_taskList.md](./Phase5_taskList.md) | Phase 5 main task list (5.6 = integration) |
---
## Task IT.1: Create Integration Test Script
**Objective**: Automated bash script that stands up a 6-node xrpld network
with telemetry, exercises all span categories, and verifies data in
Tempo/Prometheus.
**What to do**:
- Create `docker/telemetry/integration-test.sh`:
- Prerequisites check (docker, xrpld binary, curl, jq)
- Start observability stack via `docker compose`
- Generate 6 validator key pairs via temp standalone xrpld
- Generate 6 node configs + shared `validators.txt`
- Start 6 xrpld nodes in consensus mode (`--start`, no `-a`)
- Wait for all nodes to reach `"proposing"` state (120s timeout)
**Key new file**: `docker/telemetry/integration-test.sh`
**Verification**:
- [ ] Script starts without errors
- [ ] All 6 nodes reach "proposing" state
- [ ] Observability stack is healthy (otel-collector, Tempo, Prometheus, Grafana)
---
## Task IT.2: RPC Span Verification (Phase 2)
**Objective**: Verify RPC spans flow through the telemetry pipeline.
**What to do**:
- Send `server_info`, `server_state`, `ledger` RPCs to node1 (port 5005)
- Wait for batch export (5s)
- Query Tempo API for:
- `rpc.request` spans (ServerHandler::onRequest)
- `rpc.process` spans (ServerHandler::processRequest)
- `rpc.command.server_info` spans (callMethod)
- `rpc.command.server_state` spans (callMethod)
- `rpc.command.ledger` spans (callMethod)
- Verify `xrpl.rpc.command` attribute present on `rpc.command.*` spans
**Verification**:
- [ ] Tempo shows `rpc.request` traces
- [ ] Tempo shows `rpc.process` traces
- [ ] Tempo shows `rpc.command.*` traces with correct attributes
---
## Task IT.3: Transaction Span Verification (Phase 3)
**Objective**: Verify transaction spans flow through the telemetry pipeline.
**What to do**:
- Get genesis account sequence via `account_info` RPC
- Submit Payment transaction using genesis seed (`snoPBrXtMeMyMHUVTgbuqAfg1SUTb`)
- Wait for consensus inclusion (10s)
- Query Tempo API for:
- `tx.process` spans (NetworkOPsImp::processTransaction) on submitting node
- `tx.receive` spans (PeerImp::handleTransaction) on peer nodes
- Verify `xrpl.tx.hash` attribute on `tx.process` spans
- Verify `xrpl.peer.id` attribute on `tx.receive` spans
**Verification**:
- [ ] Tempo shows `tx.process` traces with `xrpl.tx.hash`
- [ ] Tempo shows `tx.receive` traces with `xrpl.peer.id`
---
## Task IT.4: Consensus Span Verification (Phase 4)
**Objective**: Verify consensus spans flow through the telemetry pipeline.
**What to do**:
- Consensus runs automatically in 6-node network
- Query Tempo API for:
- `consensus.proposal.send` (Adaptor::propose)
- `consensus.ledger_close` (Adaptor::onClose)
- `consensus.accept` (Adaptor::onAccept)
- `consensus.validation.send` (Adaptor::validate)
- Verify attributes:
- `xrpl.consensus.mode` on `consensus.ledger_close`
- `xrpl.consensus.proposers` on `consensus.accept`
- `xrpl.consensus.ledger.seq` on `consensus.validation.send`
**Verification**:
- [ ] Tempo shows `consensus.ledger_close` traces with `xrpl.consensus.mode`
- [ ] Tempo shows `consensus.accept` traces with `xrpl.consensus.proposers`
- [ ] Tempo shows `consensus.proposal.send` traces
- [ ] Tempo shows `consensus.validation.send` traces
---
## Task IT.5: Spanmetrics Verification (Phase 5)
**Objective**: Verify spanmetrics connector derives RED metrics from spans.
**What to do**:
- Query Prometheus for `traces_span_metrics_calls_total`
- Query Prometheus for `traces_span_metrics_duration_milliseconds_count`
- Verify Grafana loads at `http://localhost:3000`
**Verification**:
- [ ] Prometheus returns non-empty results for `traces_span_metrics_calls_total`
- [ ] Prometheus returns non-empty results for duration histogram
- [ ] Grafana UI accessible with dashboards visible
---
## Task IT.6: Manual Testing Plan
**Objective**: Document how to run tests manually for future reference.
**What to do**:
- Create `docker/telemetry/TESTING.md` with:
- Prerequisites section
- Single-node standalone test (quick verification)
- 6-node consensus test (full verification)
- Expected span catalog (all 12 span names with attributes)
- Verification queries (Tempo API, Prometheus API)
- Troubleshooting guide
**Key new file**: `docker/telemetry/TESTING.md`
**Verification**:
- [ ] Document covers both single-node and multi-node testing
- [ ] All 12 span names documented with source file and attributes
- [ ] Troubleshooting section covers common failure modes
---
## Task IT.7: Run and Verify
**Objective**: Execute the integration test and validate results.
**What to do**:
- Run `docker/telemetry/integration-test.sh` locally
- Debug any failures
- Leave stack running for manual verification
- Share URLs:
- Tempo: `http://localhost:3200`
- Grafana: `http://localhost:3000`
- Prometheus: `http://localhost:9090`
**Verification**:
- [ ] Script completes with all checks passing
- [ ] Tempo UI shows rippled service with all expected span names
- [ ] Grafana dashboards load and show data
---
## Task IT.8: Commit
**Objective**: Commit all new files to Phase 5 branch.
**What to do**:
- Run `pcc` (pre-commit checks)
- Commit 3 new files to `pratik/otel-phase5-docs-deployment`
**Verification**:
- [ ] `pcc` passes
- [ ] Commit created on Phase 5 branch
---
## Summary
| Task | Description | New Files | Depends On |
| ---- | ----------------------------- | --------- | ---------- |
| IT.1 | Integration test script | 1 | Phase 5 |
| IT.2 | RPC span verification | 0 | IT.1 |
| IT.3 | Transaction span verification | 0 | IT.1 |
| IT.4 | Consensus span verification | 0 | IT.1 |
| IT.5 | Spanmetrics verification | 0 | IT.1 |
| IT.6 | Manual testing plan | 1 | -- |
| IT.7 | Run and verify | 0 | IT.1-IT.6 |
| IT.8 | Commit | 0 | IT.7 |
**Exit Criteria**:
- [ ] All 6 xrpld nodes reach "proposing" state
- [ ] All 11 expected span names visible in Tempo
- [ ] Spanmetrics available in Prometheus
- [ ] Grafana dashboards show data
- [ ] Manual testing plan document complete

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# Phase 5: Documentation & Deployment Task List
> **Goal**: Production readiness — Grafana dashboards, spanmetrics pipeline, operator runbook, alert definitions, and final integration testing. This phase ensures the telemetry system is useful and maintainable in production.
>
> **Scope**: Grafana dashboard definitions, OTel Collector spanmetrics connector, Prometheus integration, alert rules, operator documentation, and production-ready Docker Compose stack.
>
> **Branch**: `pratik/otel-phase5-docs-deployment` (from `pratik/otel-phase4-consensus-tracing`)
### Related Plan Documents
| Document | Relevance |
| ---------------------------------------------------------------- | -------------------------------------------------------------------------- |
| [07-observability-backends.md](./07-observability-backends.md) | Tempo setup (§7.1), Grafana dashboards (§7.6), alerts (§7.6.3) |
| [05-configuration-reference.md](./05-configuration-reference.md) | Collector config (§5.5), production config (§5.5.2), Docker Compose (§5.6) |
| [06-implementation-phases.md](./06-implementation-phases.md) | Phase 5 tasks (§6.6), definition of done (§6.11.5) |
---
## Task 5.1: Add Spanmetrics Connector to OTel Collector
**Objective**: Derive RED metrics (Rate, Errors, Duration) from trace spans automatically, enabling Grafana time-series dashboards.
**What to do**:
- Edit `docker/telemetry/otel-collector-config.yaml`:
- Add `spanmetrics` connector:
```yaml
connectors:
spanmetrics:
histogram:
explicit:
buckets: [1ms, 5ms, 10ms, 25ms, 50ms, 100ms, 250ms, 500ms, 1s, 5s]
dimensions:
- name: xrpl.rpc.command
- name: xrpl.rpc.status
- name: xrpl.consensus.phase
- name: xrpl.tx.type
```
- Add `prometheus` exporter:
```yaml
exporters:
prometheus:
endpoint: 0.0.0.0:8889
```
- Wire the pipeline:
```yaml
service:
pipelines:
traces:
receivers: [otlp]
processors: [batch]
exporters: [debug, otlp/tempo, spanmetrics]
metrics:
receivers: [spanmetrics]
exporters: [prometheus]
```
- Edit `docker/telemetry/docker-compose.yml`:
- Expose port `8889` on the collector for Prometheus scraping
- Add Prometheus service
- Add Prometheus as Grafana datasource
**Key modified files**:
- `docker/telemetry/otel-collector-config.yaml`
- `docker/telemetry/docker-compose.yml`
**Key new files**:
- `docker/telemetry/prometheus.yml` (Prometheus scrape config)
- `docker/telemetry/grafana/provisioning/datasources/prometheus.yaml`
**Reference**:
- [POC_taskList.md §Next Steps](./POC_taskList.md) — Metrics pipeline for Grafana dashboards
---
## Task 5.2: Create Grafana Dashboards
**Objective**: Provide pre-built Grafana dashboards for RPC performance, transaction lifecycle, and consensus health.
**What to do**:
- Create `docker/telemetry/grafana/provisioning/dashboards/dashboards.yaml` (provisioning config)
- Create dashboard JSON files:
1. **RPC Performance Dashboard** (`rpc-performance.json`):
- RPC request latency (p50/p95/p99) by command — histogram panel
- RPC throughput (requests/sec) by command — time series
- RPC error rate by command — bar gauge
- Top slowest RPC commands — table
2. **Transaction Overview Dashboard** (`transaction-overview.json`):
- Transaction processing rate — time series
- Transaction latency distribution — histogram
- Suppression rate (duplicates) — stat panel
- Transaction processing path (sync vs async) — pie chart
3. **Consensus Health Dashboard** (`consensus-health.json`):
- Consensus round duration — time series
- Phase duration breakdown (open/establish/accept) — stacked bar
- Proposals sent/received per round — stat panel
- Consensus mode distribution (proposing/observing) — pie chart
- Store dashboards in `docker/telemetry/grafana/dashboards/`
**Key new files**:
- `docker/telemetry/grafana/provisioning/dashboards/dashboards.yaml`
- `docker/telemetry/grafana/dashboards/rpc-performance.json`
- `docker/telemetry/grafana/dashboards/transaction-overview.json`
- `docker/telemetry/grafana/dashboards/consensus-health.json`
**Reference**:
- [07-observability-backends.md §7.6](./07-observability-backends.md) — Grafana dashboard specifications
- [01-architecture-analysis.md §1.8.3](./01-architecture-analysis.md) — Dashboard panel examples
---
## Task 5.3: Define Alert Rules
**Objective**: Create alert definitions for key telemetry anomalies.
**What to do**:
- Create `docker/telemetry/grafana/provisioning/alerting/alerts.yaml`:
- **RPC Latency Alert**: p99 latency > 1s for any command over 5 minutes
- **RPC Error Rate Alert**: Error rate > 5% for any command over 5 minutes
- **Consensus Duration Alert**: Round duration > 10s (warn), > 30s (critical)
- **Transaction Processing Alert**: Processing rate drops below threshold
- **Telemetry Pipeline Health**: No spans received for > 2 minutes
**Key new files**:
- `docker/telemetry/grafana/provisioning/alerting/alerts.yaml`
**Reference**:
- [07-observability-backends.md §7.6.3](./07-observability-backends.md) — Alert rule definitions
---
## Task 5.4: Production Collector Configuration
**Objective**: Create a production-ready OTel Collector configuration with tail-based sampling and resource limits.
**What to do**:
- Create `docker/telemetry/otel-collector-config-production.yaml`:
- Tail-based sampling policy:
- Always sample errors and slow traces
- 10% base sampling rate for normal traces
- Always sample first trace for each unique RPC command
- Resource limits:
- Memory limiter processor (80% of available memory)
- Queued retry for export failures
- TLS configuration for production endpoints
- Health check endpoint
**Key new files**:
- `docker/telemetry/otel-collector-config-production.yaml`
**Reference**:
- [05-configuration-reference.md §5.5.2](./05-configuration-reference.md) — Production collector config
---
## Task 5.5: Operator Runbook
**Objective**: Create operator documentation for managing the telemetry system in production.
**What to do**:
- Create `docs/telemetry-runbook.md`:
- **Setup**: How to enable telemetry in rippled
- **Configuration**: All config options with descriptions
- **Collector Deployment**: Docker Compose vs. Kubernetes vs. bare metal
- **Troubleshooting**: Common issues and resolutions
- No traces appearing
- High memory usage from telemetry
- Collector connection failures
- Sampling configuration tuning
- **Performance Tuning**: Batch size, queue size, sampling ratio guidelines
- **Upgrading**: How to upgrade OTel SDK and Collector versions
**Key new files**:
- `docs/telemetry-runbook.md`
---
## Task 5.6: Final Integration Testing
**Objective**: Validate the complete telemetry stack end-to-end.
**What to do**:
1. Start full Docker stack (Collector, Tempo, Grafana, Prometheus)
2. Build rippled with `telemetry=ON`
3. Run in standalone mode with telemetry enabled
4. Generate RPC traffic and verify traces in Tempo
5. Verify dashboards populate in Grafana
6. Verify alerts trigger correctly
7. Test telemetry OFF path (no regressions)
8. Run full test suite
**Verification Checklist**:
- [ ] Docker stack starts without errors
- [ ] Traces appear in Tempo with correct hierarchy
- [ ] Grafana dashboards show metrics derived from spans
- [ ] Prometheus scrapes spanmetrics successfully
- [ ] Alerts can be triggered by simulated conditions
- [ ] Build succeeds with telemetry ON and OFF
- [ ] Full test suite passes
---
## Summary
| Task | Description | New Files | Modified Files | Depends On |
| ---- | ---------------------------------- | --------- | -------------- | ---------- |
| 5.1 | Spanmetrics connector + Prometheus | 2 | 2 | Phase 4 |
| 5.2 | Grafana dashboards | 4 | 0 | 5.1 |
| 5.3 | Alert definitions | 1 | 0 | 5.1 |
| 5.4 | Production collector config | 1 | 0 | Phase 4 |
| 5.5 | Operator runbook | 1 | 0 | Phase 4 |
| 5.6 | Final integration testing | 0 | 0 | 5.1-5.5 |
**Parallel work**: Tasks 5.1, 5.4, and 5.5 can run in parallel. Tasks 5.2 and 5.3 depend on 5.1. Task 5.6 depends on all others.
**Exit Criteria** (from [06-implementation-phases.md §6.11.5](./06-implementation-phases.md)):
- [ ] Dashboards deployed and showing data
- [ ] Alerts configured and tested
- [ ] Operator documentation complete
- [ ] Production collector config ready
- [ ] Full test suite passes

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@@ -0,0 +1,673 @@
# OpenTelemetry Distributed Tracing for rippled
---
## Slide 1: Introduction
> **CNCF** = Cloud Native Computing Foundation
### What is OpenTelemetry?
OpenTelemetry is an open-source, CNCF-backed observability framework for distributed tracing, metrics, and logs.
### Why OpenTelemetry for rippled?
- **End-to-End Transaction Visibility**: Track transactions from submission → consensus → ledger inclusion
- **Cross-Node Correlation**: Follow requests across multiple independent nodes using a unique `trace_id`
- **Consensus Round Analysis**: Understand timing and behavior across validators
- **Incident Debugging**: Correlate events across distributed nodes during issues
```mermaid
flowchart LR
A["Node A<br/>tx.receive<br/>trace_id: abc123"] --> B["Node B<br/>tx.relay<br/>trace_id: abc123"] --> C["Node C<br/>tx.validate<br/>trace_id: abc123"] --> D["Node D<br/>ledger.apply<br/>trace_id: abc123"]
style A fill:#1565c0,stroke:#0d47a1,color:#fff
style B fill:#2e7d32,stroke:#1b5e20,color:#fff
style C fill:#2e7d32,stroke:#1b5e20,color:#fff
style D fill:#e65100,stroke:#bf360c,color:#fff
```
**Reading the diagram:**
- **Node A (blue, leftmost)**: The originating node that first receives the transaction and assigns a new `trace_id: abc123`; this ID becomes the correlation key for the entire distributed trace.
- **Node B and Node C (green, middle)**: Relay and validation nodes — each creates its own span but carries the same `trace_id`, so their work is linked to the original submission without any central coordinator.
- **Node D (orange, rightmost)**: The final node that applies the transaction to the ledger; the trace now spans the full lifecycle from submission to ledger inclusion.
- **Left-to-right flow**: The horizontal progression shows the real-world message path — a transaction hops from node to node, and the shared `trace_id` stitches all hops into a single queryable trace.
> **Trace ID: abc123** — All nodes share the same trace, enabling cross-node correlation.
---
## Slide 2: OpenTelemetry vs Open Source Alternatives
> **CNCF** = Cloud Native Computing Foundation
| Feature | OpenTelemetry | Jaeger | Zipkin | SkyWalking | Pinpoint | Prometheus |
| ------------------- | ---------------- | ---------------- | ------------------ | ---------- | ---------- | ---------- |
| **Tracing** | YES | YES | YES | YES | YES | NO |
| **Metrics** | YES | NO | NO | YES | YES | YES |
| **Logs** | YES | NO | NO | YES | NO | NO |
| **C++ SDK** | YES Official | YES (Deprecated) | YES (Unmaintained) | NO | NO | YES |
| **Vendor Neutral** | YES Primary goal | NO | NO | NO | NO | NO |
| **Instrumentation** | Manual + Auto | Manual | Manual | Auto-first | Auto-first | Manual |
| **Backend** | Any (exporters) | Self | Self | Self | Self | Self |
| **CNCF Status** | Incubating | Graduated | NO | Incubating | NO | Graduated |
> **Why OpenTelemetry?** It's the only actively maintained, full-featured C++ option with vendor neutrality — allowing export to Tempo, Prometheus, Grafana, or any commercial backend without changing instrumentation.
---
## Slide 3: Adoption Scope — Traces Only (Current Plan)
OpenTelemetry supports three signal types: **Traces**, **Metrics**, and **Logs**. rippled already captures metrics (StatsD via Beast Insight) and logs (Journal/PerfLog). The question is: how much of OTel do we adopt?
> **Scenario A**: Add distributed tracing. Keep StatsD for metrics and Journal for logs.
```mermaid
flowchart LR
subgraph rippled["rippled Process"]
direction TB
OTel["OTel SDK<br/>(Traces)"]
Insight["Beast Insight<br/>(StatsD Metrics)"]
Journal["Journal + PerfLog<br/>(Logging)"]
end
OTel -->|"OTLP"| Collector["OTel Collector"]
Insight -->|"UDP"| StatsD["StatsD Server"]
Journal -->|"File I/O"| LogFile["perf.log / debug.log"]
Collector --> Tempo["Tempo"]
StatsD --> Graphite["Graphite / Grafana"]
LogFile --> Loki["Loki (optional)"]
style rippled fill:#424242,stroke:#212121,color:#fff
style OTel fill:#2e7d32,stroke:#1b5e20,color:#fff
style Insight fill:#1565c0,stroke:#0d47a1,color:#fff
style Journal fill:#e65100,stroke:#bf360c,color:#fff
style Collector fill:#2e7d32,stroke:#1b5e20,color:#fff
```
| Aspect | Details |
| ------------------------------ | --------------------------------------------------------------------------------------------------------------- |
| **What changes for operators** | Deploy OTel Collector + trace backend. Existing StatsD and log pipelines stay as-is. |
| **Codebase impact** | New `Telemetry` module (~1500 LOC). Beast Insight and Journal untouched. |
| **New capabilities** | Cross-node trace correlation, span-based debugging, request lifecycle visibility. |
| **What we still can't do** | Correlate metrics with specific traces natively. StatsD metrics remain fire-and-forget with no trace exemplars. |
| **Maintenance burden** | Three separate observability systems to maintain (OTel + StatsD + Journal). |
| **Risk** | Lowest — additive change, no existing systems disturbed. |
---
## Slide 4: Future Adoption — Metrics & Logs via OTel
### Scenario B: + OTel Metrics (Replace StatsD)
> Migrate StatsD to OTel Metrics API, exposing Prometheus-compatible metrics. Remove Beast Insight.
```mermaid
flowchart LR
subgraph rippled["rippled Process"]
direction TB
OTel["OTel SDK<br/>(Traces + Metrics)"]
Journal["Journal + PerfLog<br/>(Logging)"]
end
OTel -->|"OTLP"| Collector["OTel Collector"]
Journal -->|"File I/O"| LogFile["perf.log / debug.log"]
Collector --> Tempo["Tempo<br/>(Traces)"]
Collector --> Prom["Prometheus<br/>(Metrics)"]
LogFile --> Loki["Loki (optional)"]
style rippled fill:#424242,stroke:#212121,color:#fff
style OTel fill:#2e7d32,stroke:#1b5e20,color:#fff
style Journal fill:#e65100,stroke:#bf360c,color:#fff
style Collector fill:#2e7d32,stroke:#1b5e20,color:#fff
```
- **Better metrics?** Yes — Prometheus gives native histograms (p50/p95/p99), multi-dimensional labels, and exemplars linking metric spikes to traces.
- **Codebase**: Remove `Beast::Insight` + `StatsDCollector` (~2000 LOC). Single SDK for traces and metrics.
- **Operator effort**: Rewrite dashboards from StatsD/Graphite queries to PromQL. Run both in parallel during transition.
- **Risk**: Medium — operators must migrate monitoring infrastructure.
### Scenario C: + OTel Logs (Full Stack)
> Also replace Journal logging with OTel Logs API. Single SDK for everything.
```mermaid
flowchart LR
subgraph rippled["rippled Process"]
OTel["OTel SDK<br/>(Traces + Metrics + Logs)"]
end
OTel -->|"OTLP"| Collector["OTel Collector"]
Collector --> Tempo["Tempo<br/>(Traces)"]
Collector --> Prom["Prometheus<br/>(Metrics)"]
Collector --> Loki["Loki / Elastic<br/>(Logs)"]
style rippled fill:#424242,stroke:#212121,color:#fff
style OTel fill:#2e7d32,stroke:#1b5e20,color:#fff
style Collector fill:#2e7d32,stroke:#1b5e20,color:#fff
```
- **Structured logging**: OTel Logs API outputs structured records with `trace_id`, `span_id`, severity, and attributes by design.
- **Full correlation**: Every log line carries `trace_id`. Click trace → see logs. Click metric spike → see trace → see logs.
- **Codebase**: Remove Beast Insight (~2000 LOC) + simplify Journal/PerfLog (~3000 LOC). One dependency instead of three.
- **Risk**: Highest — `beast::Journal` is deeply embedded in every component. Large refactor. OTel C++ Logs API is newer (stable since v1.11, less battle-tested).
### Recommendation
```mermaid
flowchart LR
A["Phase 1<br/><b>Traces Only</b><br/>(Current Plan)"] --> B["Phase 2<br/><b>+ Metrics</b><br/>(Replace StatsD)"] --> C["Phase 3<br/><b>+ Logs</b><br/>(Full OTel)"]
style A fill:#2e7d32,stroke:#1b5e20,color:#fff
style B fill:#1565c0,stroke:#0d47a1,color:#fff
style C fill:#e65100,stroke:#bf360c,color:#fff
```
| Phase | Signal | Strategy | Risk |
| -------------------- | --------- | -------------------------------------------------------------- | ------ |
| **Phase 1** (now) | Traces | Add OTel traces. Keep StatsD and Journal. Prove value. | Low |
| **Phase 2** (future) | + Metrics | Migrate StatsD → Prometheus via OTel. Remove Beast Insight. | Medium |
| **Phase 3** (future) | + Logs | Adopt OTel Logs API. Align with structured logging initiative. | High |
> **Key Takeaway**: Start with traces (unique value, lowest risk), then incrementally adopt metrics and logs as the OTel infrastructure proves itself.
---
## Slide 5: Comparison with rippled's Existing Solutions
### Current Observability Stack
| Aspect | PerfLog (JSON) | StatsD (Metrics) | OpenTelemetry (NEW) |
| --------------------- | --------------------- | --------------------- | --------------------------- |
| **Type** | Logging | Metrics | Distributed Tracing |
| **Scope** | Single node | Single node | **Cross-node** |
| **Data** | JSON log entries | Counters, gauges | Spans with context |
| **Correlation** | By timestamp | By metric name | By `trace_id` |
| **Overhead** | Low (file I/O) | Low (UDP) | Low-Medium (configurable) |
| **Question Answered** | "What happened here?" | "How many? How fast?" | **"What was the journey?"** |
### Use Case Matrix
| Scenario | PerfLog | StatsD | OpenTelemetry |
| -------------------------------- | ------- | ------ | ------------- |
| "How many TXs per second?" | ❌ | ✅ | ❌ |
| "Why was this specific TX slow?" | ⚠️ | ❌ | ✅ |
| "Which node delayed consensus?" | ❌ | ❌ | ✅ |
| "Show TX journey across 5 nodes" | ❌ | ❌ | ✅ |
> **Key Insight**: In the **traces-only** approach (Phase 1), OpenTelemetry **complements** existing systems. In future phases, OTel metrics and logs could **replace** StatsD and Journal respectively — see Slides 3-4 for the full adoption roadmap.
---
## Slide 6: Architecture
> **OTLP** = OpenTelemetry Protocol | **WS** = WebSocket
### High-Level Integration Architecture
```mermaid
flowchart TB
subgraph rippled["rippled Node"]
subgraph services["Core Services"]
direction LR
RPC["RPC Server<br/>(HTTP/WS)"] ~~~ Overlay["Overlay<br/>(P2P Network)"] ~~~ Consensus["Consensus<br/>(RCLConsensus)"]
end
Telemetry["Telemetry Module<br/>(OpenTelemetry SDK)"]
services --> Telemetry
end
Telemetry -->|OTLP/gRPC| Collector["OTel Collector"]
Collector --> Tempo["Grafana Tempo"]
Collector --> Elastic["Elastic APM"]
style rippled fill:#424242,stroke:#212121,color:#fff
style services fill:#1565c0,stroke:#0d47a1,color:#fff
style Telemetry fill:#2e7d32,stroke:#1b5e20,color:#fff
style Collector fill:#e65100,stroke:#bf360c,color:#fff
```
**Reading the diagram:**
- **Core Services (blue, top)**: RPC Server, Overlay, and Consensus are the three primary components that generate trace data — they represent the entry points for client requests, peer messages, and consensus rounds respectively.
- **Telemetry Module (green, middle)**: The OpenTelemetry SDK sits below the core services and receives span data from all three; it acts as a single collection point within the rippled process.
- **OTel Collector (orange, center)**: An external process that receives spans over OTLP/gRPC from the Telemetry Module; it decouples rippled from backend choices and handles batching, sampling, and routing.
- **Backends (bottom row)**: Tempo and Elastic APM are interchangeable — the Collector fans out to any combination, so operators can switch backends without modifying rippled code.
- **Top-to-bottom flow**: Data flows from instrumented code down through the SDK, out over the network to the Collector, and finally into storage/visualization backends.
### Context Propagation
```mermaid
sequenceDiagram
participant Client
participant NodeA as Node A
participant NodeB as Node B
Client->>NodeA: Submit TX (no context)
Note over NodeA: Creates trace_id: abc123<br/>span: tx.receive
NodeA->>NodeB: Relay TX<br/>(traceparent: abc123)
Note over NodeB: Links to trace_id: abc123<br/>span: tx.relay
```
- **HTTP/RPC**: W3C Trace Context headers (`traceparent`)
- **P2P Messages**: Protocol Buffer extension fields
---
## Slide 7: Implementation Plan
### 5-Phase Rollout (9 Weeks)
> **Note**: Dates shown are relative to project start, not calendar dates.
```mermaid
gantt
title Implementation Timeline
dateFormat YYYY-MM-DD
axisFormat Week %W
section Phase 1
Core Infrastructure :p1, 2024-01-01, 2w
section Phase 2
RPC Tracing :p2, after p1, 2w
section Phase 3
Transaction Tracing :p3, after p2, 2w
section Phase 4
Consensus Tracing :p4, after p3, 2w
section Phase 5
Documentation :p5, after p4, 1w
```
### Phase Details
| Phase | Focus | Key Deliverables | Effort |
| ----- | ------------------- | -------------------------------------------- | ------- |
| 1 | Core Infrastructure | SDK integration, Telemetry interface, Config | 10 days |
| 2 | RPC Tracing | HTTP context extraction, Handler spans | 10 days |
| 3 | Transaction Tracing | Protobuf context, P2P relay propagation | 10 days |
| 4 | Consensus Tracing | Round spans, Proposal/validation tracing | 10 days |
| 5 | Documentation | Runbook, Dashboards, Training | 7 days |
**Total Effort**: ~47 developer-days (2 developers)
> **Future Phases** (not in current scope): After traces are stable, OTel metrics can replace StatsD (~3 weeks), and OTel logs can replace Journal (~4 weeks, aligned with structured logging initiative). See Slides 3-4 for the full adoption roadmap.
---
## Slide 8: Performance Overhead
> **OTLP** = OpenTelemetry Protocol
### Estimated System Impact
| Metric | Overhead | Notes |
| ----------------- | ---------- | ------------------------------------------------ |
| **CPU** | 1-3% | Span creation and attribute setting |
| **Memory** | ~10 MB | SDK statics + batch buffer + worker thread stack |
| **Network** | 10-50 KB/s | Compressed OTLP export to collector |
| **Latency (p99)** | <2% | With proper sampling configuration |
#### How We Arrived at These Numbers
**Assumptions (XRPL mainnet baseline)**:
| Parameter | Value | Source |
| ------------------------- | ---------------------- | --------------------------------------------------------------------------------------------------- |
| Transaction throughput | ~25 TPS (peaks to ~50) | Mainnet average |
| Default peers per node | 21 | `peerfinder/detail/Tuning.h` (`defaultMaxPeers`) |
| Consensus round frequency | ~1 round / 3-4 seconds | `ConsensusParms.h` (`ledgerMIN_CONSENSUS=1950ms`) |
| Proposers per round | ~20-35 | Mainnet UNL size |
| P2P message rate | ~160 msgs/sec | See message breakdown below |
| Avg TX processing time | ~200 μs | Profiled baseline |
| Single span creation cost | 500-1000 ns | OTel C++ SDK benchmarks (see [3.5.4](./03-implementation-strategy.md#354-performance-data-sources)) |
**P2P message breakdown** (per node, mainnet):
| Message Type | Rate | Derivation |
| ------------- | ------------ | --------------------------------------------------------------------- |
| TMTransaction | ~100/sec | ~25 TPS × ~4 relay hops per TX, deduplicated by HashRouter |
| TMValidation | ~50/sec | ~35 validators × ~1 validation/3s round ~12/sec, plus relay fan-out |
| TMProposeSet | ~10/sec | ~35 proposers / 3s round ~12/round, clustered in establish phase |
| **Total** | **~160/sec** | **Only traced message types counted** |
**CPU (1-3%) — Calculation**:
Per-transaction tracing cost breakdown:
| Operation | Cost | Notes |
| ----------------------------------------------- | ----------- | ------------------------------------------ |
| `tx.receive` span (create + end + 4 attributes) | ~1400 ns | ~1000ns create + ~200ns end + 4×50ns attrs |
| `tx.validate` span | ~1200 ns | ~1000ns create + ~200ns for 2 attributes |
| `tx.relay` span | ~1200 ns | ~1000ns create + ~200ns for 2 attributes |
| Context injection into P2P message | ~200 ns | Serialize trace_id + span_id into protobuf |
| **Total per TX** | **~4.0 μs** | |
> **CPU overhead**: 4.0 μs / 200 μs baseline = **~2.0% per transaction**. Under high load with consensus + RPC spans overlapping, reaches ~3%. Consensus itself adds only ~36 μs per 3-second round (~0.001%), so the TX path dominates. On production server hardware (3+ GHz Xeon), span creation drops to ~500-600 ns, bringing per-TX cost to ~2.6 μs (~1.3%). See [Section 3.5.4](./03-implementation-strategy.md#354-performance-data-sources) for benchmark sources.
**Memory (~10 MB) — Calculation**:
| Component | Size | Notes |
| --------------------------------------------- | ------------------ | ------------------------------------- |
| TracerProvider + Exporter (gRPC channel init) | ~320 KB | Allocated once at startup |
| BatchSpanProcessor (circular buffer) | ~16 KB | 2049 × 8-byte AtomicUniquePtr entries |
| BatchSpanProcessor (worker thread stack) | ~8 MB | Default Linux thread stack size |
| Active spans (in-flight, max ~1000) | ~500-800 KB | ~500-800 bytes/span × 1000 concurrent |
| Export queue (batch buffer, max 2048 spans) | ~1 MB | ~500 bytes/span × 2048 queue depth |
| Thread-local context storage (~100 threads) | ~6.4 KB | ~64 bytes/thread |
| **Total** | **~10 MB ceiling** | |
> Memory plateaus once the export queue fills — the `max_queue_size=2048` config bounds growth.
> The worker thread stack (~8 MB) dominates the static footprint but is virtual memory; actual RSS
> depends on stack usage (typically much less). Active spans are larger than originally estimated
> (~500-800 bytes) because the OTel SDK `Span` object includes a mutex (~40 bytes), `SpanData`
> recordable (~250 bytes base), and `std::map`-based attribute storage (~200-500 bytes for 3-5
> string attributes). See [Section 3.5.4](./03-implementation-strategy.md#354-performance-data-sources) for source references.
**Network (10-50 KB/s) — Calculation**:
Two sources of network overhead:
**(A) OTLP span export to Collector:**
| Sampling Rate | Effective Spans/sec | Avg Span Size (compressed) | Bandwidth |
| -------------------------- | ------------------- | -------------------------- | ------------ |
| 100% (dev only) | ~500 | ~500 bytes | ~250 KB/s |
| **10% (recommended prod)** | **~50** | **~500 bytes** | **~25 KB/s** |
| 1% (minimal) | ~5 | ~500 bytes | ~2.5 KB/s |
> The ~500 spans/sec at 100% comes from: ~100 TX spans + ~160 P2P context spans + ~23 consensus spans/round + ~50 RPC spans = ~500/sec. OTLP protobuf with gzip compression yields ~500 bytes/span average.
**(B) P2P trace context overhead** (added to existing messages, always-on regardless of sampling):
| Message Type | Rate | Context Size | Bandwidth |
| ------------- | -------- | ------------ | ------------- |
| TMTransaction | ~100/sec | 29 bytes | ~2.9 KB/s |
| TMValidation | ~50/sec | 29 bytes | ~1.5 KB/s |
| TMProposeSet | ~10/sec | 29 bytes | ~0.3 KB/s |
| **Total P2P** | | | **~4.7 KB/s** |
> **Combined**: 25 KB/s (OTLP export at 10%) + 5 KB/s (P2P context) ≈ **~30 KB/s typical**. The 10-50 KB/s range covers 10-20% sampling under normal to peak mainnet load.
**Latency (<2%) — Calculation**:
| Path | Tracing Cost | Baseline | Overhead |
| ------------------------------ | ------------ | -------- | -------- |
| Fast RPC (e.g., `server_info`) | 2.75 μs | ~1 ms | 0.275% |
| Slow RPC (e.g., `path_find`) | 2.75 μs | ~100 ms | 0.003% |
| Transaction processing | 4.0 μs | ~200 μs | 2.0% |
| Consensus round | 36 μs | ~3 sec | 0.001% |
> At p99, even the worst case (TX processing at 2.0%) is within the 1-3% range. RPC and consensus overhead are negligible. On production hardware, TX overhead drops to ~1.3%.
### Per-Message Overhead (Context Propagation)
Each P2P message carries trace context with the following overhead:
| Field | Size | Description |
| ------------- | ------------- | ----------------------------------------- |
| `trace_id` | 16 bytes | Unique identifier for the entire trace |
| `span_id` | 8 bytes | Current span (becomes parent on receiver) |
| `trace_flags` | 1 byte | Sampling decision flags |
| `trace_state` | 0-4 bytes | Optional vendor-specific data |
| **Total** | **~29 bytes** | **Added per traced P2P message** |
```mermaid
flowchart LR
subgraph msg["P2P Message with Trace Context"]
A["Original Message<br/>(variable size)"] --> B["+ TraceContext<br/>(~29 bytes)"]
end
subgraph breakdown["Context Breakdown"]
C["trace_id<br/>16 bytes"]
D["span_id<br/>8 bytes"]
E["flags<br/>1 byte"]
F["state<br/>0-4 bytes"]
end
B --> breakdown
style A fill:#424242,stroke:#212121,color:#fff
style B fill:#2e7d32,stroke:#1b5e20,color:#fff
style C fill:#1565c0,stroke:#0d47a1,color:#fff
style D fill:#1565c0,stroke:#0d47a1,color:#fff
style E fill:#e65100,stroke:#bf360c,color:#fff
style F fill:#4a148c,stroke:#2e0d57,color:#fff
```
**Reading the diagram:**
- **Original Message (gray, left)**: The existing P2P message payload of variable size this is unchanged; trace context is appended, never modifying the original data.
- **+ TraceContext (green, right of message)**: The additional 29-byte context block attached to each traced message; the arrow from the original message shows it is a pure addition.
- **Context Breakdown (right subgraph)**: The four fields `trace_id` (16 bytes), `span_id` (8 bytes), `flags` (1 byte), and `state` (0-4 bytes) show exactly what is added and their individual sizes.
- **Color coding**: Blue fields (`trace_id`, `span_id`) are the core identifiers required for trace correlation; orange (`flags`) controls sampling decisions; purple (`state`) is optional vendor data typically omitted.
> **Note**: 29 bytes represents ~1-6% overhead depending on message size (500B simple TX to 5KB proposal), which is acceptable for the observability benefits provided.
### Mitigation Strategies
```mermaid
flowchart LR
A["Head Sampling<br/>10% default"] --> B["Tail Sampling<br/>Keep errors/slow"] --> C["Batch Export<br/>Reduce I/O"] --> D["Conditional Compile<br/>XRPL_ENABLE_TELEMETRY"]
style A fill:#1565c0,stroke:#0d47a1,color:#fff
style B fill:#2e7d32,stroke:#1b5e20,color:#fff
style C fill:#e65100,stroke:#bf360c,color:#fff
style D fill:#4a148c,stroke:#2e0d57,color:#fff
```
> For a detailed explanation of head vs. tail sampling, see Slide 9.
### Kill Switches (Rollback Options)
1. **Config Disable**: Set `enabled=0` in config instant disable, no restart needed for sampling
2. **Rebuild**: Compile with `XRPL_ENABLE_TELEMETRY=OFF` zero overhead (no-op)
3. **Full Revert**: Clean separation allows easy commit reversion
---
## Slide 9: Sampling Strategies — Head vs. Tail
> Sampling controls **which traces are recorded and exported**. Without sampling, every operation generates a trace — at 500+ spans/sec, this overwhelms storage and network. Sampling lets you keep the signal, discard the noise.
### Head Sampling (Decision at Start)
The sampling decision is made **when a trace begins**, before any work is done. A random number is generated; if it falls within the configured ratio, the entire trace is recorded. Otherwise, the trace is silently dropped.
```mermaid
flowchart LR
A["New Request<br/>Arrives"] --> B{"Random < 10%?"}
B -->|"Yes (1 in 10)"| C["Record Entire Trace<br/>(all spans)"]
B -->|"No (9 in 10)"| D["Drop Entire Trace<br/>(zero overhead)"]
style C fill:#2e7d32,stroke:#1b5e20,color:#fff
style D fill:#c62828,stroke:#8c2809,color:#fff
style B fill:#1565c0,stroke:#0d47a1,color:#fff
```
| Aspect | Details |
| ----------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **Where it runs** | Inside rippled (SDK-level). Configured via `sampling_ratio` in `rippled.cfg`. |
| **When the decision happens** | At trace creation time before the first span is even populated. |
| **How it works** | `sampling_ratio=0.1` means each trace has a 10% probability of being recorded. Dropped traces incur near-zero overhead (no spans created, no attributes set, no export). |
| **Propagation** | Once a trace is sampled, the `trace_flags` field (1 byte in the context header) tells downstream nodes to also sample it. Unsampled traces propagate `trace_flags=0`, so downstream nodes skip them too. |
| **Pros** | Lowest overhead. Simple to configure. Predictable resource usage. |
| **Cons** | **Blind** it doesn't know if the trace will be interesting. A rare error or slow consensus round has only a 10% chance of being captured. |
| **Best for** | High-volume, steady-state traffic where most traces look similar (e.g., routine RPC requests). |
**rippled configuration**:
```ini
[telemetry]
# Record 10% of traces (recommended for production)
sampling_ratio=0.1
```
### Tail Sampling (Decision at End)
The sampling decision is made **after the trace completes**, based on its actual content was it slow? Did it error? Was it a consensus round? This requires buffering complete traces before deciding.
```mermaid
flowchart TB
A["All Traces<br/>Buffered (100%)"] --> B["OTel Collector<br/>Evaluates Rules"]
B --> C{"Error?"}
C -->|Yes| K["KEEP"]
C -->|No| D{"Slow?<br/>(>5s consensus,<br/>>1s RPC)"}
D -->|Yes| K
D -->|No| E{"Random < 10%?"}
E -->|Yes| K
E -->|No| F["DROP"]
style K fill:#2e7d32,stroke:#1b5e20,color:#fff
style F fill:#c62828,stroke:#8c2809,color:#fff
style B fill:#1565c0,stroke:#0d47a1,color:#fff
style C fill:#e65100,stroke:#bf360c,color:#fff
style D fill:#e65100,stroke:#bf360c,color:#fff
style E fill:#4a148c,stroke:#2e0d57,color:#fff
```
| Aspect | Details |
| ----------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **Where it runs** | In the **OTel Collector** (external process), not inside rippled. rippled exports 100% of traces; the Collector decides what to keep. |
| **When the decision happens** | After the Collector has received all spans for a trace (waits `decision_wait=10s` for stragglers). |
| **How it works** | Policy rules evaluate the completed trace: keep all errors, keep slow operations above a threshold, keep all consensus rounds, then probabilistically sample the rest at 10%. |
| **Pros** | **Never misses important traces**. Errors, slow requests, and consensus anomalies are always captured regardless of probability. |
| **Cons** | Higher resource usage rippled must export 100% of spans to the Collector, which buffers them in memory before deciding. The Collector needs more RAM (configured via `num_traces` and `decision_wait`). |
| **Best for** | Production troubleshooting where you can't afford to miss errors or anomalies. |
**Collector configuration** (tail sampling rules for rippled):
```yaml
processors:
tail_sampling:
decision_wait: 10s # Wait for all spans in a trace
num_traces: 100000 # Buffer up to 100K concurrent traces
policies:
- name: errors # Always keep error traces
type: status_code
status_code: { status_codes: [ERROR] }
- name: slow-consensus # Keep consensus rounds >5s
type: latency
latency: { threshold_ms: 5000 }
- name: slow-rpc # Keep slow RPC requests >1s
type: latency
latency: { threshold_ms: 1000 }
- name: probabilistic # Sample 10% of everything else
type: probabilistic
probabilistic: { sampling_percentage: 10 }
```
### Head vs. Tail — Side-by-Side
| | Head Sampling | Tail Sampling |
| ----------------------------- | ---------------------------------------- | ------------------------------------------------ |
| **Decision point** | Trace start (inside rippled) | Trace end (in OTel Collector) |
| **Knows trace content?** | No (random coin flip) | Yes (evaluates completed trace) |
| **Overhead on rippled** | Lowest (dropped traces = no-op) | Higher (must export 100% to Collector) |
| **Collector resource usage** | Low (receives only sampled traces) | Higher (buffers all traces before deciding) |
| **Captures all errors?** | No (only if trace was randomly selected) | **Yes** (error policy catches them) |
| **Captures slow operations?** | No (random) | **Yes** (latency policy catches them) |
| **Configuration** | `rippled.cfg`: `sampling_ratio=0.1` | `otel-collector.yaml`: `tail_sampling` processor |
| **Best for** | High-throughput steady-state | Troubleshooting & anomaly detection |
### Recommended Strategy for rippled
Use **both** in a layered approach:
```mermaid
flowchart LR
subgraph rippled["rippled (Head Sampling)"]
HS["sampling_ratio=1.0<br/>(export everything)"]
end
subgraph collector["OTel Collector (Tail Sampling)"]
TS["Keep: errors + slow + 10% random<br/>Drop: routine traces"]
end
subgraph storage["Backend Storage"]
ST["Only interesting traces<br/>stored long-term"]
end
rippled -->|"100% of spans"| collector -->|"~15-20% kept"| storage
style rippled fill:#424242,stroke:#212121,color:#fff
style collector fill:#1565c0,stroke:#0d47a1,color:#fff
style storage fill:#2e7d32,stroke:#1b5e20,color:#fff
```
> **Why this works**: rippled exports everything (no blind drops), the Collector applies intelligent filtering (keep errors/slow/anomalies, sample the rest), and only ~15-20% of traces reach storage. If Collector resource usage becomes a concern, add head sampling at `sampling_ratio=0.5` to halve the export volume while still giving the Collector enough data for good tail-sampling decisions.
---
## Slide 10: Data Collection & Privacy
### What Data is Collected
| Category | Attributes Collected | Purpose |
| --------------- | ------------------------------------------------------------------------------------ | --------------------------- |
| **Transaction** | `tx.hash`, `tx.type`, `tx.result`, `tx.fee`, `ledger_index` | Trace transaction lifecycle |
| **Consensus** | `round`, `phase`, `mode`, `proposers` (count of proposing validators), `duration_ms` | Analyze consensus timing |
| **RPC** | `command`, `version`, `status`, `duration_ms` | Monitor RPC performance |
| **Peer** | `peer.id`(public key), `latency_ms`, `message.type`, `message.size` | Network topology analysis |
| **Ledger** | `ledger.hash`, `ledger.index`, `close_time`, `tx_count` | Ledger progression tracking |
| **Job** | `job.type`, `queue_ms`, `worker` | JobQueue performance |
### What is NOT Collected (Privacy Guarantees)
```mermaid
flowchart LR
subgraph notCollected["❌ NOT Collected"]
direction LR
A["Private Keys"] ~~~ B["Account Balances"] ~~~ C["Transaction Amounts"]
end
subgraph alsoNot["❌ Also Excluded"]
direction LR
D["IP Addresses<br/>(configurable)"] ~~~ E["Personal Data"] ~~~ F["Raw TX Payloads"]
end
style A fill:#c62828,stroke:#8c2809,color:#fff
style B fill:#c62828,stroke:#8c2809,color:#fff
style C fill:#c62828,stroke:#8c2809,color:#fff
style D fill:#c62828,stroke:#8c2809,color:#fff
style E fill:#c62828,stroke:#8c2809,color:#fff
style F fill:#c62828,stroke:#8c2809,color:#fff
```
**Reading the diagram:**
- **NOT Collected (top row, red)**: Private Keys, Account Balances, and Transaction Amounts are explicitly excluded these are financial/security-sensitive fields that telemetry never touches.
- **Also Excluded (bottom row, red)**: IP Addresses (configurable per deployment), Personal Data, and Raw TX Payloads are also excluded these protect operator and user privacy.
- **All-red styling**: Every box is styled in red to visually reinforce that these are hard exclusions, not optional the telemetry system has no code path to collect any of these fields.
- **Two-row layout**: The split between "NOT Collected" and "Also Excluded" distinguishes between financial data (top) and operational/personal data (bottom), making the privacy boundaries clear to auditors.
### Privacy Protection Mechanisms
| Mechanism | Description |
| -------------------------- | ------------------------------------------------------------- |
| **Account Hashing** | `xrpl.tx.account` is hashed at collector level before storage |
| **Configurable Redaction** | Sensitive fields can be excluded via config |
| **Sampling** | Only 10% of traces recorded by default (reduces exposure) |
| **Local Control** | Node operators control what gets exported |
| **No Raw Payloads** | Transaction content is never recorded, only metadata |
> **Key Principle**: Telemetry collects **operational metadata** (timing, counts, hashes) — never **sensitive content** (keys, balances, amounts).
---
_End of Presentation_

View File

@@ -1529,3 +1529,46 @@ validators.txt
# set to ssl_verify to 0.
[ssl_verify]
1
#-------------------------------------------------------------------------------
#
# 11. Telemetry (OpenTelemetry Tracing)
#
#-------------------------------------------------------------------------------
#
# Enables distributed tracing via OpenTelemetry. Requires building with
# -DXRPL_ENABLE_TELEMETRY=ON (telemetry Conan option).
#
# [telemetry]
#
# enabled=0
#
# Enable or disable telemetry at runtime. Default: 0 (disabled).
#
# endpoint=http://localhost:4318/v1/traces
#
# The OpenTelemetry Collector endpoint (OTLP/HTTP). Default: http://localhost:4318/v1/traces.
#
# exporter=otlp_http
#
# Exporter type: otlp_http. Default: otlp_http.
#
# sampling_ratio=1.0
#
# Fraction of traces to sample (0.0 to 1.0). Default: 1.0 (all traces).
#
# trace_rpc=1
#
# Enable RPC request tracing. Default: 1.
#
# trace_transactions=1
#
# Enable transaction lifecycle tracing. Default: 1.
#
# trace_consensus=1
#
# Enable consensus round tracing. Default: 1.
#
# trace_peer=0
#
# Enable peer message tracing (high volume). Default: 0.
#

View File

@@ -204,6 +204,23 @@ target_link_libraries(
add_module(xrpl tx)
target_link_libraries(xrpl.libxrpl.tx PUBLIC xrpl.libxrpl.ledger)
# Telemetry module — OpenTelemetry distributed tracing support.
# Sources: include/xrpl/telemetry/ (headers), src/libxrpl/telemetry/ (impl).
# When telemetry=ON, links the Conan-provided umbrella target
# opentelemetry-cpp::opentelemetry-cpp (individual component targets like
# ::api, ::sdk are not available in the Conan package).
add_module(xrpl telemetry)
target_link_libraries(
xrpl.libxrpl.telemetry
PUBLIC xrpl.libxrpl.basics xrpl.libxrpl.beast
)
if(telemetry)
target_link_libraries(
xrpl.libxrpl.telemetry
PUBLIC opentelemetry-cpp::opentelemetry-cpp
)
endif()
add_library(xrpl.libxrpl)
set_target_properties(xrpl.libxrpl PROPERTIES OUTPUT_NAME xrpl)
@@ -235,6 +252,7 @@ target_link_modules(
resource
server
shamap
telemetry
tx
)

View File

@@ -3,22 +3,25 @@
"requires": [
"zlib/1.3.1#cac0f6daea041b0ccf42934163defb20%1774439233.809",
"xxhash/0.8.3#681d36a0a6111fc56e5e45ea182c19cc%1765850149.987",
"sqlite3/3.51.0#66aa11eabd0e34954c5c1c061ad44abe%1774467355.988",
"sqlite3/3.51.0#66aa11eabd0e34954c5c1c061ad44abe%1763899256.358",
"soci/4.0.3#fe32b9ad5eb47e79ab9e45a68f363945%1774450067.231",
"snappy/1.1.10#968fef506ff261592ec30c574d4a7809%1765850147.878",
"secp256k1/0.7.1#481881709eb0bdd0185a12b912bbe8ad%1770910500.329",
"rocksdb/10.5.1#4a197eca381a3e5ae8adf8cffa5aacd0%1765850186.86",
"re2/20251105#8579cfd0bda4daf0683f9e3898f964b4%1774398111.888",
"protobuf/6.33.5#d96d52ba5baaaa532f47bda866ad87a5%1774467363.12",
"protobuf/6.33.5#d96d52ba5baaaa532f47bda866ad87a5%1773224203.27",
"opentelemetry-cpp/1.18.0#efd9851e173f8a13b9c7d35232de8cf1%1750409186.472",
"openssl/3.6.1#e6399de266349245a4542fc5f6c71552%1774458290.139",
"nudb/2.0.9#11149c73f8f2baff9a0198fe25971fc7%1774883011.384",
"nudb/2.0.9#0432758a24204da08fee953ec9ea03cb%1769436073.32",
"nlohmann_json/3.11.3#45828be26eb619a2e04ca517bb7b828d%1701220705.259",
"lz4/1.10.0#59fc63cac7f10fbe8e05c7e62c2f3504%1765850143.914",
"libiconv/1.17#1e65319e945f2d31941a9d28cc13c058%1765842973.492",
"libcurl/8.18.0#364bc3755cb9ef84ed9a7ae9c7efc1c1%1770984390.024",
"libbacktrace/cci.20210118#a7691bfccd8caaf66309df196790a5a1%1765842973.03",
"libarchive/3.8.1#ffee18995c706e02bf96e7a2f7042e0d%1765850144.736",
"jemalloc/5.3.0#e951da9cf599e956cebc117880d2d9f8%1729241615.244",
"gtest/1.17.0#5224b3b3ff3b4ce1133cbdd27d53ee7d%1768312129.152",
"grpc/1.78.1#b1a9e74b145cc471bed4dc64dc6eb2c1%1774467387.342",
"grpc/1.78.1#b1a9e74b145cc471bed4dc64dc6eb2c1%1772623605.068",
"ed25519/2015.03#ae761bdc52730a843f0809bdf6c1b1f6%1765850143.772",
"date/3.0.4#862e11e80030356b53c2c38599ceb32b%1765850143.772",
"c-ares/1.34.6#545240bb1c40e2cacd4362d6b8967650%1774439234.681",
@@ -29,10 +32,16 @@
"build_requires": [
"zlib/1.3.1#cac0f6daea041b0ccf42934163defb20%1774439233.809",
"strawberryperl/5.32.1.1#8d114504d172cfea8ea1662d09b6333e%1774447376.964",
"protobuf/6.33.5#d96d52ba5baaaa532f47bda866ad87a5%1774467363.12",
"protobuf/6.33.5#d96d52ba5baaaa532f47bda866ad87a5%1773224203.27",
"pkgconf/2.5.1#93c2051284cba1279494a43a4fcfeae2%1757684701.089",
"opentelemetry-proto/1.4.0#4096a3b05916675ef9628f3ffd571f51%1732731336.11",
"ninja/1.13.2#c8c5dc2a52ed6e4e42a66d75b4717ceb%1764096931.974",
"nasm/2.16.01#31e26f2ee3c4346ecd347911bd126904%1765850144.707",
"msys2/cci.latest#d22fe7b2808f5fd34d0a7923ace9c54f%1770657326.649",
"meson/1.10.0#60786758ea978964c24525de19603cf4%1768294926.103",
"m4/1.4.19#5d7a4994e5875d76faf7acf3ed056036%1774365463.87",
"libtool/2.4.7#14e7739cc128bc1623d2ed318008e47e%1755679003.847",
"gnu-config/cci.20210814#466e9d4d7779e1c142443f7ea44b4284%1762363589.329",
"cmake/4.3.0#b939a42e98f593fb34d3a8c5cc860359%1774439249.183",
"b2/5.4.2#ffd6084a119587e70f11cd45d1a386e2%1774439233.447",
"automake/1.16.5#b91b7c384c3deaa9d535be02da14d04f%1755524470.56",
@@ -41,15 +50,16 @@
],
"python_requires": [],
"overrides": {
"boost/1.90.0#d5e8defe7355494953be18524a7f135b": [
null,
"boost/1.90.0"
],
"protobuf/[>=5.27.0 <7]": [
"protobuf/6.33.5"
],
"lz4/1.9.4": [
"lz4/1.10.0"
],
"boost/[>=1.83.0 <1.91.0]": [
"boost/1.90.0"
],
"sqlite3/[>=3.44 <4]": [
"sqlite3/3.51.0"
],

View File

@@ -22,6 +22,7 @@ class Xrpl(ConanFile):
"rocksdb": [True, False],
"shared": [True, False],
"static": [True, False],
"telemetry": [True, False],
"tests": [True, False],
"unity": [True, False],
"xrpld": [True, False],
@@ -54,6 +55,7 @@ class Xrpl(ConanFile):
"rocksdb": True,
"shared": False,
"static": True,
"telemetry": True,
"tests": False,
"unity": False,
"xrpld": False,
@@ -145,6 +147,10 @@ class Xrpl(ConanFile):
self.requires("jemalloc/5.3.0")
if self.options.rocksdb:
self.requires("rocksdb/10.5.1")
# OpenTelemetry C++ SDK for distributed tracing (optional).
# Provides OTLP/HTTP exporter, batch span processor, and trace API.
if self.options.telemetry:
self.requires("opentelemetry-cpp/1.18.0")
self.requires("xxhash/0.8.3", transitive_headers=True)
exports_sources = (
@@ -173,6 +179,7 @@ class Xrpl(ConanFile):
tc.variables["rocksdb"] = self.options.rocksdb
tc.variables["BUILD_SHARED_LIBS"] = self.options.shared
tc.variables["static"] = self.options.static
tc.variables["telemetry"] = self.options.telemetry
tc.variables["unity"] = self.options.unity
tc.variables["xrpld"] = self.options.xrpld
tc.generate()
@@ -225,3 +232,5 @@ class Xrpl(ConanFile):
]
if self.options.rocksdb:
libxrpl.requires.append("rocksdb::librocksdb")
if self.options.telemetry:
libxrpl.requires.append("opentelemetry-cpp::opentelemetry-cpp")

View File

@@ -87,6 +87,8 @@ words:
- daria
- dcmake
- dearmor
- Dedup
- dedup
- deleteme
- demultiplexer
- deserializaton
@@ -97,6 +99,7 @@ words:
- doxyfile
- dxrpl
- endmacro
- EOCFG
- exceptioned
- Falco
- fcontext
@@ -182,6 +185,7 @@ words:
- NOLINTNEXTLINE
- nonxrp
- noripple
- nostd
- nudb
- nullptr
- nunl
@@ -194,8 +198,11 @@ words:
- permdex
- perminute
- permissioned
- pgrep
- pkill
- pointee
- populator
- pratik
- preauth
- preauthorization
- preauthorize
@@ -210,7 +217,9 @@ words:
- qalloc
- queuable
- Raphson
- reparent
- replayer
- reqps
- rerere
- retriable
- RIPD
@@ -267,6 +276,7 @@ words:
- txjson
- txn
- txns
- txqueue
- txs
- UBSAN
- ubsan
@@ -307,6 +317,10 @@ words:
- xchain
- ximinez
- EXPECT_STREQ
- Gantt
- gantt
- otelc
- traceql
- XMACRO
- xrpkuwait
- xrpl
@@ -314,3 +328,5 @@ words:
- xrplf
- xxhash
- xxhasher
- xychart
- zpages

2
docker/telemetry/.gitignore vendored Normal file
View File

@@ -0,0 +1,2 @@
# Runtime data generated by xrpld and telemetry stack
data/

512
docker/telemetry/TESTING.md Normal file
View File

@@ -0,0 +1,512 @@
# OpenTelemetry Integration Testing Guide
This document describes how to verify the rippled OpenTelemetry telemetry
pipeline end-to-end, from span generation through the observability stack
(otel-collector, Tempo, Prometheus, Grafana).
---
## Prerequisites
### Build xrpld with telemetry
```bash
conan install . --build=missing -o telemetry=True
cmake --preset default -Dtelemetry=ON
cmake --build --preset default --target xrpld
```
The binary is at `.build/xrpld`.
### Required tools
- **Docker** with `docker compose` (v2)
- **curl**
- **jq** (JSON processor)
### Verify binary
```bash
.build/xrpld --version
```
---
## Test 1: Single-Node Standalone (Quick Verification)
This test verifies RPC and transaction spans in standalone mode. Consensus
spans will not fire because standalone mode does not run consensus.
### Step 1: Start the observability stack
```bash
docker compose -f docker/telemetry/docker-compose.yml up -d
```
Wait for services to be ready:
```bash
# otel-collector health
curl -sf http://localhost:13133/ && echo "collector ready"
# Tempo readiness
curl -sf http://localhost:3200/ready > /dev/null && echo "tempo ready"
```
### Step 2: Start xrpld in standalone mode
```bash
.build/xrpld --conf docker/telemetry/xrpld-telemetry.cfg -a --start
```
Wait a few seconds for the node to initialize.
### Step 3: Exercise RPC spans
```bash
# server_info
curl -s http://localhost:5005 \
-d '{"method":"server_info"}' | jq .result.info.server_state
# server_state
curl -s http://localhost:5005 \
-d '{"method":"server_state"}' | jq .result.state.server_state
# ledger
curl -s http://localhost:5005 \
-d '{"method":"ledger","params":[{"ledger_index":"current"}]}' \
| jq .result.ledger_current_index
```
### Step 4: Submit a transaction
Close the ledger first (required in standalone mode):
```bash
curl -s http://localhost:5005 -d '{"method":"ledger_accept"}'
```
Submit a Payment from the genesis account:
```bash
curl -s http://localhost:5005 -d '{
"method": "submit",
"params": [{
"secret": "snoPBrXtMeMyMHUVTgbuqAfg1SUTb",
"tx_json": {
"TransactionType": "Payment",
"Account": "rHb9CJAWyB4rj91VRWn96DkukG4bwdtyTh",
"Destination": "rPMh7Pi9ct699iZUTWzJaUMR1o42VEfGqF",
"Amount": "10000000"
}
}]
}' | jq .result.engine_result
```
Expected result: `"tesSUCCESS"`.
Close the ledger again to finalize:
```bash
curl -s http://localhost:5005 -d '{"method":"ledger_accept"}'
```
### Step 5: Verify traces in Tempo
Wait 5 seconds for the batch export, then:
```bash
TEMPO="http://localhost:3200"
# Check rippled service is registered
curl -s "$TEMPO/api/v2/search/tag/resource.service.name/values" | jq '.tagValues[].value'
# Check RPC spans
curl -s "$TEMPO/api/search" \
--data-urlencode 'q={resource.service.name="rippled" && name="rpc.request"}' \
--data-urlencode 'limit=5' | jq '.traces | length'
curl -s "$TEMPO/api/search" \
--data-urlencode 'q={resource.service.name="rippled" && name="rpc.process"}' \
--data-urlencode 'limit=5' | jq '.traces | length'
curl -s "$TEMPO/api/search" \
--data-urlencode 'q={resource.service.name="rippled" && name="rpc.command.server_info"}' \
--data-urlencode 'limit=5' | jq '.traces | length'
# Check transaction spans
curl -s "$TEMPO/api/search" \
--data-urlencode 'q={resource.service.name="rippled" && name="tx.process"}' \
--data-urlencode 'limit=5' | jq '.traces | length'
```
Or open Grafana Explore with Tempo datasource: http://localhost:3000
### Step 6: Teardown
```bash
# Kill xrpld (Ctrl+C or)
kill $(pgrep -f 'xrpld.*xrpld-telemetry')
# Stop observability stack
docker compose -f docker/telemetry/docker-compose.yml down
# Clean xrpld data
rm -rf data/
```
### Expected spans (standalone mode)
| Span Name | Expected | Notes |
| --------------------------- | -------- | ----------------------------- |
| `rpc.request` | Yes | Every HTTP RPC call |
| `rpc.process` | Yes | Every RPC processing |
| `rpc.command.server_info` | Yes | server_info RPC |
| `rpc.command.server_state` | Yes | server_state RPC |
| `rpc.command.ledger` | Yes | ledger RPC |
| `rpc.command.submit` | Yes | submit RPC |
| `rpc.command.ledger_accept` | Yes | ledger_accept RPC |
| `tx.process` | Yes | Transaction submission |
| `tx.receive` | No | No peers in standalone |
| `consensus.*` | No | Consensus disabled standalone |
---
## Test 2: 6-Node Consensus Network (Full Verification)
This test verifies ALL span categories including consensus and peer
transaction relay, using a 6-node validator network.
### Automated
Run the integration test script:
```bash
bash docker/telemetry/integration-test.sh
```
The script will:
1. Start the observability stack
2. Generate 6 validator key pairs
3. Create config files for each node
4. Start all 6 nodes
5. Wait for consensus ("proposing" state)
6. Exercise RPC, submit transactions
7. Verify all span categories in Tempo
8. Verify spanmetrics in Prometheus
9. Print results and leave the stack running
### Manual
If you prefer to run the steps manually:
#### Step 1: Start observability stack
```bash
docker compose -f docker/telemetry/docker-compose.yml up -d
```
#### Step 2: Generate validator keys
Start a temporary standalone xrpld:
```bash
.build/xrpld --conf docker/telemetry/xrpld-telemetry.cfg -a --start &
TEMP_PID=$!
sleep 5
```
Generate 6 key pairs:
```bash
for i in $(seq 1 6); do
curl -s http://localhost:5005 \
-d '{"method":"validation_create"}' | jq '.result'
done
```
Record the `validation_seed` and `validation_public_key` for each.
Kill the temporary node:
```bash
kill $TEMP_PID
rm -rf data/
```
#### Step 3: Create node configs
For each node (1-6), create a config file. Template:
```ini
[server]
port_rpc
port_peer
[port_rpc]
port = {5004 + node_number}
ip = 127.0.0.1
admin = 127.0.0.1
protocol = http
[port_peer]
port = {51234 + node_number}
ip = 0.0.0.0
protocol = peer
[node_db]
type=NuDB
path=/tmp/xrpld-integration/node{N}/nudb
online_delete=256
[database_path]
/tmp/xrpld-integration/node{N}/db
[debug_logfile]
/tmp/xrpld-integration/node{N}/debug.log
[validation_seed]
{seed from step 2}
[validators_file]
/tmp/xrpld-integration/validators.txt
[ips_fixed]
127.0.0.1 51235
127.0.0.1 51236
127.0.0.1 51237
127.0.0.1 51238
127.0.0.1 51239
127.0.0.1 51240
[peer_private]
1
[telemetry]
enabled=1
endpoint=http://localhost:4318/v1/traces
exporter=otlp_http
sampling_ratio=1.0
batch_size=512
batch_delay_ms=2000
max_queue_size=2048
trace_rpc=1
trace_transactions=1
trace_consensus=1
trace_peer=0
trace_ledger=1
[rpc_startup]
{ "command": "log_level", "severity": "warning" }
[ssl_verify]
0
```
#### Step 4: Create validators.txt
```ini
[validators]
{public_key_1}
{public_key_2}
{public_key_3}
{public_key_4}
{public_key_5}
{public_key_6}
```
#### Step 5: Start all 6 nodes
```bash
for i in $(seq 1 6); do
.build/xrpld --conf /tmp/xrpld-integration/node$i/xrpld.cfg --start &
echo $! > /tmp/xrpld-integration/node$i/xrpld.pid
done
```
#### Step 6: Wait for consensus
Poll each node until `server_state` = `"proposing"`:
```bash
for port in 5005 5006 5007 5008 5009 5010; do
while true; do
state=$(curl -s http://localhost:$port \
-d '{"method":"server_info"}' \
| jq -r '.result.info.server_state')
echo "Port $port: $state"
[ "$state" = "proposing" ] && break
sleep 5
done
done
```
#### Step 7: Exercise RPC and submit transaction
```bash
# RPC calls
curl -s http://localhost:5005 -d '{"method":"server_info"}'
curl -s http://localhost:5005 -d '{"method":"server_state"}'
curl -s http://localhost:5005 -d '{"method":"ledger","params":[{"ledger_index":"current"}]}'
# Submit transaction
curl -s http://localhost:5005 -d '{
"method": "submit",
"params": [{
"secret": "snoPBrXtMeMyMHUVTgbuqAfg1SUTb",
"tx_json": {
"TransactionType": "Payment",
"Account": "rHb9CJAWyB4rj91VRWn96DkukG4bwdtyTh",
"Destination": "rPMh7Pi9ct699iZUTWzJaUMR1o42VEfGqF",
"Amount": "10000000"
}
}]
}'
```
Wait 15 seconds for consensus and batch export.
#### Step 8: Verify in Tempo
See the "Verification Queries" section below.
---
## Expected Span Catalog
All 12 production span names instrumented across Phases 2-4:
| Span Name | Source File | Phase | Key Attributes | How to Trigger |
| --------------------------- | --------------------- | ----- | --------------------------------------------------------------------------------- | ------------------------- |
| `rpc.request` | ServerHandler.cpp:271 | 2 | -- | Any HTTP RPC call |
| `rpc.process` | ServerHandler.cpp:573 | 2 | -- | Any HTTP RPC call |
| `rpc.ws_message` | ServerHandler.cpp:384 | 2 | -- | WebSocket RPC message |
| `rpc.command.<name>` | RPCHandler.cpp:161 | 2 | `xrpl.rpc.command`, `xrpl.rpc.version`, `xrpl.rpc.role` | Any RPC command |
| `tx.process` | NetworkOPs.cpp:1227 | 3 | `xrpl.tx.hash`, `xrpl.tx.local`, `xrpl.tx.path` | Submit transaction |
| `tx.receive` | PeerImp.cpp:1273 | 3 | `xrpl.peer.id` | Peer relays transaction |
| `consensus.proposal.send` | RCLConsensus.cpp:177 | 4 | `xrpl.consensus.round` | Consensus proposing phase |
| `consensus.ledger_close` | RCLConsensus.cpp:282 | 4 | `xrpl.consensus.ledger.seq`, `xrpl.consensus.mode` | Ledger close event |
| `consensus.accept` | RCLConsensus.cpp:395 | 4 | `xrpl.consensus.proposers`, `xrpl.consensus.round_time_ms` | Ledger accepted |
| `consensus.validation.send` | RCLConsensus.cpp:753 | 4 | `xrpl.consensus.ledger.seq`, `xrpl.consensus.proposing` | Validation sent |
| `consensus.accept.apply` | RCLConsensus.cpp:453 | 4 | `xrpl.consensus.close_time`, `close_time_correct`, `close_resolution_ms`, `state` | Ledger apply + close time |
---
## Verification Queries
### Tempo API
Base URL: `http://localhost:3200`
```bash
TEMPO="http://localhost:3200"
# List all services
curl -s "$TEMPO/api/v2/search/tag/resource.service.name/values" | jq '.tagValues[].value'
# Query traces by operation
for op in "rpc.request" "rpc.process" \
"rpc.command.server_info" "rpc.command.server_state" "rpc.command.ledger" \
"tx.process" "tx.receive" \
"consensus.proposal.send" "consensus.ledger_close" \
"consensus.accept" "consensus.accept.apply" \
"consensus.validation.send"; do
count=$(curl -s "$TEMPO/api/search" \
--data-urlencode "q={resource.service.name=\"rippled\" && name=\"$op\"}" \
--data-urlencode "limit=5" \
| jq '.traces | length')
printf "%-35s %s traces\n" "$op" "$count"
done
```
### Prometheus API
Base URL: `http://localhost:9090`
```bash
PROM="http://localhost:9090"
# Span call counts (from spanmetrics connector)
curl -s "$PROM/api/v1/query?query=traces_span_metrics_calls_total" \
| jq '.data.result[] | {span: .metric.span_name, count: .value[1]}'
# Latency histogram
curl -s "$PROM/api/v1/query?query=traces_span_metrics_duration_milliseconds_count" \
| jq '.data.result[] | {span: .metric.span_name, count: .value[1]}'
# RPC calls by command
curl -s "$PROM/api/v1/query?query=traces_span_metrics_calls_total{span_name=~\"rpc.command.*\"}" \
| jq '.data.result[] | {command: .metric["xrpl.rpc.command"], count: .value[1]}'
```
### Grafana
Open http://localhost:3000 (anonymous admin access enabled).
Pre-configured dashboards:
- **RPC Performance**: Request rates, latency percentiles by command
- **Transaction Overview**: Transaction processing rates and paths
- **Consensus Health**: Consensus round duration and proposer counts
Pre-configured datasources:
- **Tempo**: Trace data at `http://tempo:3200`
- **Prometheus**: Metrics at `http://prometheus:9090`
---
## Troubleshooting
### No traces in Tempo
1. Check otel-collector logs:
```bash
docker compose -f docker/telemetry/docker-compose.yml logs otel-collector
```
2. Verify xrpld telemetry config has `enabled=1` and correct endpoint
3. Check that otel-collector port 4318 is accessible:
```bash
curl -sf http://localhost:4318 && echo "reachable"
```
4. Increase `batch_delay_ms` or decrease `batch_size` in xrpld config
### Nodes not reaching "proposing" state
1. Check that all peer ports (51235-51240) are not in use:
```bash
for p in 51235 51236 51237 51238 51239 51240; do
ss -tlnp | grep ":$p " && echo "port $p in use"
done
```
2. Verify `[ips_fixed]` lists all 6 peer ports
3. Verify `validators.txt` has all 6 public keys
4. Check node debug logs: `tail -50 /tmp/xrpld-integration/node1/debug.log`
5. Ensure `[peer_private]` is set to `1` (prevents reaching out to public network)
### Transaction not processing
1. Verify genesis account exists:
```bash
curl -s http://localhost:5005 \
-d '{"method":"account_info","params":[{"account":"rHb9CJAWyB4rj91VRWn96DkukG4bwdtyTh"}]}' \
| jq .result.account_data.Balance
```
2. Check submit response for error codes
3. In standalone mode, remember to call `ledger_accept` after submitting
### Spanmetrics not appearing in Prometheus
1. Verify otel-collector config has `spanmetrics` connector
2. Check that the metrics pipeline is configured:
```yaml
service:
pipelines:
metrics:
receivers: [spanmetrics]
exporters: [prometheus]
```
3. Verify Prometheus can reach collector:
```bash
curl -s http://localhost:9090/api/v1/targets | jq '.data.activeTargets'
```

View File

@@ -0,0 +1,81 @@
# Docker Compose stack for rippled OpenTelemetry observability.
#
# Provides services for local development:
# - otel-collector: receives OTLP traces from rippled, batches and
# forwards them to Tempo. Listens on ports 4317 (gRPC)
# and 4318 (HTTP).
# - tempo: Grafana Tempo tracing backend, queryable via Grafana Explore
# on port 3000. Recommended for production (S3/GCS storage, TraceQL).
# - grafana: dashboards on port 3000, pre-configured with Tempo
# and Prometheus datasources.
#
# Usage:
# docker compose -f docker/telemetry/docker-compose.yml up -d
#
# Configure rippled to export traces by adding to xrpld.cfg:
# [telemetry]
# enabled=1
# endpoint=http://localhost:4318/v1/traces
version: "3.8"
services:
otel-collector:
image: otel/opentelemetry-collector-contrib:latest
command: ["--config=/etc/otel-collector-config.yaml"]
ports:
- "4317:4317" # OTLP gRPC
- "4318:4318" # OTLP HTTP
- "8889:8889" # Prometheus metrics (spanmetrics)
- "13133:13133" # Health check
volumes:
- ./otel-collector-config.yaml:/etc/otel-collector-config.yaml:ro
depends_on:
- tempo
networks:
- rippled-telemetry
tempo:
image: grafana/tempo:2.7.2
command: ["-config.file=/etc/tempo.yaml"]
ports:
- "3200:3200" # Tempo HTTP API (health, query)
volumes:
- ./tempo.yaml:/etc/tempo.yaml:ro
- tempo-data:/var/tempo
networks:
- rippled-telemetry
prometheus:
image: prom/prometheus:latest
ports:
- "9090:9090"
volumes:
- ./prometheus.yml:/etc/prometheus/prometheus.yml:ro
depends_on:
- otel-collector
networks:
- rippled-telemetry
grafana:
image: grafana/grafana:latest
environment:
- GF_AUTH_ANONYMOUS_ENABLED=true
- GF_AUTH_ANONYMOUS_ORG_ROLE=Admin
ports:
- "3000:3000"
volumes:
- ./grafana/provisioning:/etc/grafana/provisioning:ro
- ./grafana/dashboards:/var/lib/grafana/dashboards:ro
depends_on:
- tempo
- prometheus
networks:
- rippled-telemetry
volumes:
tempo-data:
networks:
rippled-telemetry:
driver: bridge

View File

@@ -0,0 +1,244 @@
{
"annotations": {
"list": []
},
"editable": true,
"fiscalYearStartMonth": 0,
"graphTooltip": 1,
"id": null,
"links": [],
"panels": [
{
"title": "Consensus Round Duration",
"type": "timeseries",
"gridPos": {
"h": 8,
"w": 12,
"x": 0,
"y": 0
},
"targets": [
{
"datasource": {
"type": "prometheus"
},
"expr": "histogram_quantile(0.95, sum by (le) (rate(traces_span_metrics_duration_milliseconds_bucket{exported_instance=~\"$node\", span_name=\"consensus.accept\"}[5m])))",
"legendFormat": "P95 Round Duration"
},
{
"datasource": {
"type": "prometheus"
},
"expr": "histogram_quantile(0.50, sum by (le) (rate(traces_span_metrics_duration_milliseconds_bucket{exported_instance=~\"$node\", span_name=\"consensus.accept\"}[5m])))",
"legendFormat": "P50 Round Duration"
}
],
"fieldConfig": {
"defaults": {
"unit": "ms"
},
"overrides": []
}
},
{
"title": "Consensus Proposals Sent Rate",
"type": "timeseries",
"gridPos": {
"h": 8,
"w": 12,
"x": 12,
"y": 0
},
"targets": [
{
"datasource": {
"type": "prometheus"
},
"expr": "sum(rate(traces_span_metrics_calls_total{exported_instance=~\"$node\", span_name=\"consensus.proposal.send\"}[5m]))",
"legendFormat": "Proposals / Sec"
}
],
"fieldConfig": {
"defaults": {
"unit": "ops"
},
"overrides": []
}
},
{
"title": "Ledger Close Duration",
"type": "timeseries",
"gridPos": {
"h": 8,
"w": 12,
"x": 0,
"y": 8
},
"targets": [
{
"datasource": {
"type": "prometheus"
},
"expr": "histogram_quantile(0.95, sum by (le) (rate(traces_span_metrics_duration_milliseconds_bucket{exported_instance=~\"$node\", span_name=\"consensus.ledger_close\"}[5m])))",
"legendFormat": "P95 Close Duration"
}
],
"fieldConfig": {
"defaults": {
"unit": "ms"
},
"overrides": []
}
},
{
"title": "Validation Send Rate",
"type": "stat",
"gridPos": {
"h": 8,
"w": 12,
"x": 12,
"y": 8
},
"targets": [
{
"datasource": {
"type": "prometheus"
},
"expr": "sum(rate(traces_span_metrics_calls_total{exported_instance=~\"$node\", span_name=\"consensus.validation.send\"}[5m]))",
"legendFormat": "Validations / Sec"
}
],
"fieldConfig": {
"defaults": {
"unit": "ops"
},
"overrides": []
}
},
{
"title": "Ledger Apply Duration (doAccept)",
"description": "Time spent applying the consensus result to build a new ledger. Measured by the consensus.accept.apply span in doAccept().",
"type": "timeseries",
"gridPos": {
"h": 8,
"w": 12,
"x": 0,
"y": 16
},
"targets": [
{
"datasource": {
"type": "prometheus"
},
"expr": "histogram_quantile(0.95, sum by (le) (rate(traces_span_metrics_duration_milliseconds_bucket{exported_instance=~\"$node\", span_name=\"consensus.accept.apply\"}[5m])))",
"legendFormat": "P95 Apply Duration"
},
{
"datasource": {
"type": "prometheus"
},
"expr": "histogram_quantile(0.50, sum by (le) (rate(traces_span_metrics_duration_milliseconds_bucket{exported_instance=~\"$node\", span_name=\"consensus.accept.apply\"}[5m])))",
"legendFormat": "P50 Apply Duration"
}
],
"fieldConfig": {
"defaults": {
"unit": "ms",
"custom": {
"axisLabel": "Duration (ms)",
"spanNulls": true,
"insertNulls": false,
"showPoints": "auto",
"pointSize": 3
}
},
"overrides": []
}
},
{
"title": "Close Time Agreement",
"description": "Rate of close time agreement vs disagreement across consensus rounds. Based on xrpl.consensus.close_time_correct attribute (true = validators agreed, false = agreed to disagree per avCT_CONSENSUS_PCT).",
"type": "timeseries",
"gridPos": {
"h": 8,
"w": 12,
"x": 12,
"y": 16
},
"targets": [
{
"datasource": {
"type": "prometheus"
},
"expr": "sum(rate(traces_span_metrics_calls_total{exported_instance=~\"$node\", span_name=\"consensus.accept.apply\"}[5m]))",
"legendFormat": "Total Rounds / Sec"
}
],
"fieldConfig": {
"defaults": {
"unit": "ops",
"custom": {
"axisLabel": "Rounds / Sec",
"spanNulls": true,
"insertNulls": false,
"showPoints": "auto",
"pointSize": 3
}
},
"overrides": []
}
}
],
"schemaVersion": 39,
"tags": ["rippled", "consensus", "telemetry"],
"templating": {
"list": [
{
"name": "node",
"label": "Node",
"description": "Filter by rippled node (service.instance.id \u2014 e.g. Node-1)",
"type": "query",
"query": "label_values(traces_span_metrics_calls_total, exported_instance)",
"datasource": {
"type": "prometheus",
"uid": "prometheus"
},
"includeAll": true,
"allValue": ".*",
"current": {
"text": "All",
"value": "$__all"
},
"multi": true,
"refresh": 2,
"sort": 1
},
{
"name": "consensus_mode",
"label": "Consensus Mode",
"description": "Filter by consensus mode (Proposing, Observing, Wrong Ledger, Switched Ledger)",
"type": "query",
"query": "label_values(traces_span_metrics_calls_total{span_name=\"consensus.ledger_close\"}, xrpl_consensus_mode)",
"datasource": {
"type": "prometheus",
"uid": "prometheus"
},
"includeAll": true,
"allValue": ".*",
"current": {
"text": "All",
"value": "$__all"
},
"multi": true,
"refresh": 2,
"sort": 1
}
]
},
"time": {
"from": "now-1h",
"to": "now"
},
"title": "rippled Consensus Health",
"uid": "rippled-consensus"
}

View File

@@ -0,0 +1,189 @@
{
"annotations": {
"list": []
},
"editable": true,
"fiscalYearStartMonth": 0,
"graphTooltip": 1,
"id": null,
"links": [],
"panels": [
{
"title": "RPC Request Rate by Command",
"type": "timeseries",
"gridPos": {
"h": 8,
"w": 12,
"x": 0,
"y": 0
},
"targets": [
{
"datasource": {
"type": "prometheus"
},
"expr": "sum by (xrpl_rpc_command) (rate(traces_span_metrics_calls_total{xrpl_rpc_command=~\"$command\", exported_instance=~\"$node\", span_name=~\"rpc.command.*\"}[5m]))",
"legendFormat": "{{xrpl_rpc_command}}"
}
],
"fieldConfig": {
"defaults": {
"unit": "reqps",
"custom": {
"axisLabel": "Requests / Sec",
"spanNulls": true,
"insertNulls": false,
"showPoints": "auto",
"pointSize": 3
}
},
"overrides": []
}
},
{
"title": "RPC Latency P95 by Command",
"type": "timeseries",
"gridPos": {
"h": 8,
"w": 12,
"x": 12,
"y": 0
},
"targets": [
{
"datasource": {
"type": "prometheus"
},
"expr": "histogram_quantile(0.95, sum by (le, xrpl_rpc_command) (rate(traces_span_metrics_duration_milliseconds_bucket{xrpl_rpc_command=~\"$command\", exported_instance=~\"$node\", span_name=~\"rpc.command.*\"}[5m])))",
"legendFormat": "P95 {{xrpl_rpc_command}}"
}
],
"fieldConfig": {
"defaults": {
"unit": "ms",
"custom": {
"axisLabel": "Latency (ms)",
"spanNulls": true,
"insertNulls": false,
"showPoints": "auto",
"pointSize": 3
}
},
"overrides": []
}
},
{
"title": "RPC Error Rate",
"type": "bargauge",
"gridPos": {
"h": 8,
"w": 12,
"x": 0,
"y": 8
},
"targets": [
{
"datasource": {
"type": "prometheus"
},
"expr": "sum by (xrpl_rpc_command) (rate(traces_span_metrics_calls_total{xrpl_rpc_command=~\"$command\", exported_instance=~\"$node\", span_name=~\"rpc.command.*\", status_code=\"STATUS_CODE_ERROR\"}[5m])) / sum by (xrpl_rpc_command) (rate(traces_span_metrics_calls_total{exported_instance=~\"$node\", xrpl_rpc_command=~\"$command\", span_name=~\"rpc.command.*\"}[5m])) * 100",
"legendFormat": "{{xrpl_rpc_command}}"
}
],
"fieldConfig": {
"defaults": {
"unit": "percent",
"thresholds": {
"steps": [
{
"color": "green",
"value": null
},
{
"color": "yellow",
"value": 1
},
{
"color": "red",
"value": 5
}
]
}
},
"overrides": []
}
},
{
"title": "RPC Latency Heatmap",
"type": "heatmap",
"gridPos": {
"h": 8,
"w": 12,
"x": 12,
"y": 8
},
"targets": [
{
"datasource": {
"type": "prometheus"
},
"expr": "sum(increase(traces_span_metrics_duration_milliseconds_bucket{xrpl_rpc_command=~\"$command\", exported_instance=~\"$node\", span_name=~\"rpc.command.*\"}[5m])) by (le)",
"legendFormat": "{{le}}",
"format": "heatmap"
}
]
}
],
"schemaVersion": 39,
"tags": ["rippled", "rpc", "telemetry"],
"templating": {
"list": [
{
"name": "node",
"label": "Node",
"description": "Filter by rippled node (service.instance.id \u2014 e.g. Node-1)",
"type": "query",
"query": "label_values(traces_span_metrics_calls_total, exported_instance)",
"datasource": {
"type": "prometheus",
"uid": "prometheus"
},
"includeAll": true,
"allValue": ".*",
"current": {
"text": "All",
"value": "$__all"
},
"multi": true,
"refresh": 2,
"sort": 1
},
{
"name": "command",
"label": "RPC Command",
"description": "Filter by RPC command name (e.g., server_info, submit)",
"type": "query",
"query": "label_values(traces_span_metrics_calls_total{span_name=~\"rpc.command.*\"}, xrpl_rpc_command)",
"datasource": {
"type": "prometheus",
"uid": "prometheus"
},
"includeAll": true,
"allValue": ".*",
"current": {
"text": "All",
"value": "$__all"
},
"multi": true,
"refresh": 2,
"sort": 1
}
]
},
"time": {
"from": "now-1h",
"to": "now"
},
"title": "rippled RPC Performance",
"uid": "rippled-rpc-perf"
}

View File

@@ -0,0 +1,172 @@
{
"annotations": {
"list": []
},
"editable": true,
"fiscalYearStartMonth": 0,
"graphTooltip": 1,
"id": null,
"links": [],
"panels": [
{
"title": "Transaction Processing Rate",
"type": "timeseries",
"gridPos": {
"h": 8,
"w": 12,
"x": 0,
"y": 0
},
"targets": [
{
"datasource": {
"type": "prometheus"
},
"expr": "sum(rate(traces_span_metrics_calls_total{exported_instance=~\"$node\", span_name=\"tx.process\"}[5m]))",
"legendFormat": "tx.process/sec"
},
{
"datasource": {
"type": "prometheus"
},
"expr": "sum(rate(traces_span_metrics_calls_total{exported_instance=~\"$node\", span_name=\"tx.receive\"}[5m]))",
"legendFormat": "tx.receive/sec"
}
],
"fieldConfig": {
"defaults": {
"unit": "ops"
},
"overrides": []
}
},
{
"title": "Transaction Processing Latency",
"type": "timeseries",
"gridPos": {
"h": 8,
"w": 12,
"x": 12,
"y": 0
},
"targets": [
{
"datasource": {
"type": "prometheus"
},
"expr": "histogram_quantile(0.95, sum by (le) (rate(traces_span_metrics_duration_milliseconds_bucket{exported_instance=~\"$node\", span_name=\"tx.process\"}[5m])))",
"legendFormat": "p95"
},
{
"datasource": {
"type": "prometheus"
},
"expr": "histogram_quantile(0.50, sum by (le) (rate(traces_span_metrics_duration_milliseconds_bucket{exported_instance=~\"$node\", span_name=\"tx.process\"}[5m])))",
"legendFormat": "p50"
}
],
"fieldConfig": {
"defaults": {
"unit": "ms"
},
"overrides": []
}
},
{
"title": "Transaction Path Distribution",
"type": "piechart",
"gridPos": {
"h": 8,
"w": 12,
"x": 0,
"y": 8
},
"targets": [
{
"datasource": {
"type": "prometheus"
},
"expr": "sum by (xrpl_tx_local) (rate(traces_span_metrics_calls_total{exported_instance=~\"$node\", xrpl_tx_local=~\"$tx_origin\", span_name=\"tx.process\"}[5m]))",
"legendFormat": "local={{xrpl_tx_local}}"
}
]
},
{
"title": "Transaction Receive vs Suppressed",
"type": "timeseries",
"gridPos": {
"h": 8,
"w": 12,
"x": 12,
"y": 8
},
"targets": [
{
"datasource": {
"type": "prometheus"
},
"expr": "sum(rate(traces_span_metrics_calls_total{exported_instance=~\"$node\", span_name=\"tx.receive\"}[5m]))",
"legendFormat": "total received"
}
],
"fieldConfig": {
"defaults": {
"unit": "ops"
},
"overrides": []
}
}
],
"schemaVersion": 39,
"tags": ["rippled", "transactions", "telemetry"],
"templating": {
"list": [
{
"name": "node",
"label": "Node",
"description": "Filter by rippled node (service.instance.id \u2014 e.g. Node-1)",
"type": "query",
"query": "label_values(traces_span_metrics_calls_total, exported_instance)",
"datasource": {
"type": "prometheus",
"uid": "prometheus"
},
"includeAll": true,
"allValue": ".*",
"current": {
"text": "All",
"value": "$__all"
},
"multi": true,
"refresh": 2,
"sort": 1
},
{
"name": "tx_origin",
"label": "TX Origin",
"description": "Filter by transaction origin (true = local submit, false = peer relay)",
"type": "query",
"query": "label_values(traces_span_metrics_calls_total{span_name=\"tx.process\"}, xrpl_tx_local)",
"datasource": {
"type": "prometheus",
"uid": "prometheus"
},
"includeAll": true,
"allValue": ".*",
"current": {
"text": "All",
"value": "$__all"
},
"multi": true,
"refresh": 2,
"sort": 1
}
]
},
"time": {
"from": "now-1h",
"to": "now"
},
"title": "rippled Transaction Overview",
"uid": "rippled-transactions"
}

View File

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apiVersion: 1
providers:
- name: rippled-telemetry
orgId: 1
folder: rippled
type: file
disableDeletion: false
editable: true
options:
path: /var/lib/grafana/dashboards
foldersFromFilesStructure: false

View File

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apiVersion: 1
datasources:
- name: Prometheus
type: prometheus
uid: prometheus
access: proxy
url: http://prometheus:9090
isDefault: true
editable: true

View File

@@ -0,0 +1,147 @@
# Grafana datasource provisioning for Grafana Tempo.
# Auto-configures Tempo as a trace data source on Grafana startup.
# Access Grafana at http://localhost:3000, then use Explore -> Tempo
# to browse rippled traces using TraceQL.
#
# Search filters provide pre-configured dropdowns in the Explore UI.
# Each phase adds filters for the span attributes it introduces.
# Phase 1b (infra): Base filters — node identity, service, span name, status.
# Phase 2 (RPC): RPC command, status, role filters.
# Phase 3 (TX): Transaction hash, local/peer origin, status.
# Phase 4 (Cons): Consensus mode, round, ledger sequence, close time.
apiVersion: 1
datasources:
- name: Tempo
type: tempo
access: proxy
url: http://tempo:3200
uid: tempo
jsonData:
nodeGraph:
enabled: true
serviceMap:
datasourceUid: prometheus
tracesToMetrics:
datasourceUid: prometheus
spanStartTimeShift: "-1h"
spanEndTimeShift: "1h"
search:
filters:
# --- Node identification filters ---
# service.name: logical service name (default: "rippled").
# Useful when running multiple service types in the same collector.
- id: service-name
tag: service.name
operator: "="
scope: resource
type: static
# service.instance.id: unique node identifier — configurable via
# the service_instance_id setting in [telemetry], defaults to the
# node's public key. E.g. "Node-1" or "nHB1X37...".
- id: node-id
tag: service.instance.id
operator: "="
scope: resource
type: static
# service.version: rippled build version (e.g., "2.4.0-b1").
# Filter traces from specific software releases.
- id: node-version
tag: service.version
operator: "="
scope: resource
type: dynamic
# xrpl.network.id: numeric network identifier
# (0 = mainnet, 1 = testnet, 2 = devnet, etc.).
- id: network-id
tag: xrpl.network.id
operator: "="
scope: resource
type: dynamic
# xrpl.network.type: human-readable network name
# ("mainnet", "testnet", "devnet", "standalone").
- id: network-type
tag: xrpl.network.type
operator: "="
scope: resource
type: static
# --- Span intrinsic filters ---
- id: span-name
tag: name
operator: "="
scope: intrinsic
type: static
- id: span-status
tag: status
operator: "="
scope: intrinsic
type: static
- id: span-duration
tag: duration
operator: ">"
scope: intrinsic
type: static
# Phase 2: RPC tracing filters
- id: rpc-command
tag: xrpl.rpc.command
operator: "="
scope: span
type: static
- id: rpc-status
tag: xrpl.rpc.status
operator: "="
scope: span
type: dynamic
- id: rpc-role
tag: xrpl.rpc.role
operator: "="
scope: span
type: dynamic
# Phase 3: Transaction tracing filters
- id: tx-hash
tag: xrpl.tx.hash
operator: "="
scope: span
type: static
- id: tx-origin
tag: xrpl.tx.local
operator: "="
scope: span
type: dynamic
- id: tx-status
tag: xrpl.tx.status
operator: "="
scope: span
type: dynamic
# Phase 4: Consensus tracing filters
- id: consensus-mode
tag: xrpl.consensus.mode
operator: "="
scope: span
type: static
- id: consensus-round
tag: xrpl.consensus.round
operator: "="
scope: span
type: dynamic
- id: consensus-ledger-seq
tag: xrpl.consensus.ledger.seq
operator: "="
scope: span
type: static
- id: consensus-close-time-correct
tag: xrpl.consensus.close_time_correct
operator: "="
scope: span
type: dynamic
- id: consensus-state
tag: xrpl.consensus.state
operator: "="
scope: span
type: dynamic
- id: consensus-close-resolution
tag: xrpl.consensus.close_resolution_ms
operator: "="
scope: span
type: dynamic

View File

@@ -0,0 +1,558 @@
#!/usr/bin/env bash
# Integration test for rippled OpenTelemetry instrumentation.
#
# Launches a 6-node xrpld consensus network with telemetry enabled,
# exercises RPC / transaction / consensus code paths, then verifies
# that the expected spans and metrics appear in Tempo and Prometheus.
#
# Usage:
# bash docker/telemetry/integration-test.sh
#
# Prerequisites:
# - .build/xrpld built with telemetry=ON
# - docker compose (v2)
# - curl, jq
#
# The script leaves the observability stack and xrpld nodes running
# so you can manually inspect Tempo (localhost:3200) and Grafana
# (localhost:3000). Run with --cleanup to tear down instead.
set -euo pipefail
# ---------------------------------------------------------------------------
# Configuration
# ---------------------------------------------------------------------------
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
REPO_ROOT="$(cd "$SCRIPT_DIR/../.." && pwd)"
XRPLD="$REPO_ROOT/.build/xrpld"
COMPOSE_FILE="$SCRIPT_DIR/docker-compose.yml"
STANDALONE_CFG="$SCRIPT_DIR/xrpld-telemetry.cfg"
WORKDIR="/tmp/xrpld-integration"
NUM_NODES=6
PEER_PORT_BASE=51235
RPC_PORT_BASE=5005
CONSENSUS_TIMEOUT=120
GENESIS_ACCOUNT="rHb9CJAWyB4rj91VRWn96DkukG4bwdtyTh"
GENESIS_SEED="snoPBrXtMeMyMHUVTgbuqAfg1SUTb"
DEST_ACCOUNT="" # Generated dynamically via wallet_propose
TEMPO="http://localhost:3200"
PROM="http://localhost:9090"
# Counters for pass/fail
PASS=0
FAIL=0
# ---------------------------------------------------------------------------
# Helpers
# ---------------------------------------------------------------------------
log() { printf "\033[1;34m[INFO]\033[0m %s\n" "$*"; }
ok() { printf "\033[1;32m[PASS]\033[0m %s\n" "$*"; PASS=$((PASS + 1)); }
fail() { printf "\033[1;31m[FAIL]\033[0m %s\n" "$*"; FAIL=$((FAIL + 1)); }
die() { printf "\033[1;31m[ERROR]\033[0m %s\n" "$*" >&2; exit 1; }
check_span() {
local op="$1"
local count
count=$(curl -sf "$TEMPO/api/search" \
--data-urlencode "q={resource.service.name=\"rippled\" && name=\"$op\"}" \
--data-urlencode "limit=5" \
| jq '.traces | length' 2>/dev/null || echo 0)
if [ "$count" -gt 0 ]; then
ok "$op ($count traces)"
else
fail "$op (0 traces)"
fi
}
cleanup() {
log "Cleaning up..."
# Kill xrpld nodes
for i in $(seq 1 "$NUM_NODES"); do
local pidfile="$WORKDIR/node$i/xrpld.pid"
if [ -f "$pidfile" ]; then
kill "$(cat "$pidfile")" 2>/dev/null || true
rm -f "$pidfile"
fi
done
# Also kill any straggling xrpld processes from our workdir
pkill -f "$WORKDIR" 2>/dev/null || true
# Stop docker stack
docker compose -f "$COMPOSE_FILE" down 2>/dev/null || true
# Remove workdir
rm -rf "$WORKDIR"
log "Cleanup complete."
}
# Handle --cleanup flag
if [ "${1:-}" = "--cleanup" ]; then
cleanup
exit 0
fi
# ---------------------------------------------------------------------------
# Step 0: Prerequisites
# ---------------------------------------------------------------------------
log "Checking prerequisites..."
command -v docker >/dev/null 2>&1 || die "docker not found"
docker compose version >/dev/null 2>&1 || die "docker compose (v2) not found"
command -v curl >/dev/null 2>&1 || die "curl not found"
command -v jq >/dev/null 2>&1 || die "jq not found"
[ -x "$XRPLD" ] || die "xrpld binary not found at $XRPLD (build with telemetry=ON)"
[ -f "$COMPOSE_FILE" ] || die "docker-compose.yml not found at $COMPOSE_FILE"
[ -f "$STANDALONE_CFG" ] || die "xrpld-telemetry.cfg not found at $STANDALONE_CFG"
log "All prerequisites met."
# ---------------------------------------------------------------------------
# Step 1: Clean previous run
# ---------------------------------------------------------------------------
log "Cleaning previous run data..."
for i in $(seq 1 "$NUM_NODES"); do
pidfile="$WORKDIR/node$i/xrpld.pid"
if [ -f "$pidfile" ]; then
kill "$(cat "$pidfile")" 2>/dev/null || true
fi
done
pkill -f "$WORKDIR" 2>/dev/null || true
# Kill any xrpld using the standalone config (from key generation)
pkill -f "xrpld-telemetry.cfg" 2>/dev/null || true
sleep 2
rm -rf "$WORKDIR"
mkdir -p "$WORKDIR"
# ---------------------------------------------------------------------------
# Step 2: Start observability stack
# ---------------------------------------------------------------------------
log "Starting observability stack..."
docker compose -f "$COMPOSE_FILE" up -d
log "Waiting for otel-collector to be ready..."
for attempt in $(seq 1 30); do
# The OTLP HTTP endpoint returns 405 for GET (expects POST), which
# means it is listening. curl -sf would fail on 405, so we check
# the HTTP status code explicitly.
status=$(curl -so /dev/null -w '%{http_code}' http://localhost:4318/ 2>/dev/null || echo 000)
if [ "$status" != "000" ]; then
log "otel-collector ready (attempt $attempt, HTTP $status)."
break
fi
if [ "$attempt" -eq 30 ]; then
die "otel-collector not ready after 30s"
fi
sleep 1
done
log "Waiting for Tempo to be ready..."
for attempt in $(seq 1 30); do
if curl -sf "$TEMPO/ready" >/dev/null 2>&1; then
log "Tempo ready (attempt $attempt)."
break
fi
if [ "$attempt" -eq 30 ]; then
die "Tempo not ready after 30s"
fi
sleep 1
done
# ---------------------------------------------------------------------------
# Step 3: Generate validator keys
# ---------------------------------------------------------------------------
log "Generating $NUM_NODES validator key pairs..."
# Start a temporary standalone xrpld for key generation
TEMP_DATA="$WORKDIR/temp-keygen"
mkdir -p "$TEMP_DATA"
# Create a minimal temp config for key generation
TEMP_CFG="$TEMP_DATA/xrpld.cfg"
cat > "$TEMP_CFG" <<EOCFG
[server]
port_rpc_temp
[port_rpc_temp]
port = 5099
ip = 127.0.0.1
admin = 127.0.0.1
protocol = http
[node_db]
type=NuDB
path=$TEMP_DATA/nudb
online_delete=256
[database_path]
$TEMP_DATA/db
[debug_logfile]
$TEMP_DATA/debug.log
[ssl_verify]
0
EOCFG
"$XRPLD" --conf "$TEMP_CFG" -a --start > "$TEMP_DATA/stdout.log" 2>&1 &
TEMP_PID=$!
log "Temporary xrpld started (PID $TEMP_PID), waiting for RPC..."
for attempt in $(seq 1 30); do
if curl -sf http://localhost:5099 -d '{"method":"server_info"}' >/dev/null 2>&1; then
log "Temporary xrpld RPC ready (attempt $attempt)."
break
fi
if [ "$attempt" -eq 30 ]; then
kill "$TEMP_PID" 2>/dev/null || true
die "Temporary xrpld RPC not ready after 30s"
fi
sleep 1
done
declare -a SEEDS
declare -a PUBKEYS
for i in $(seq 1 "$NUM_NODES"); do
result=$(curl -sf http://localhost:5099 -d '{"method":"validation_create"}')
seed=$(echo "$result" | jq -r '.result.validation_seed')
pubkey=$(echo "$result" | jq -r '.result.validation_public_key')
if [ -z "$seed" ] || [ "$seed" = "null" ]; then
kill "$TEMP_PID" 2>/dev/null || true
die "Failed to generate key pair $i"
fi
SEEDS+=("$seed")
PUBKEYS+=("$pubkey")
log " Node $i: $pubkey"
done
kill "$TEMP_PID" 2>/dev/null || true
wait "$TEMP_PID" 2>/dev/null || true
rm -rf "$TEMP_DATA"
log "Key generation complete."
# ---------------------------------------------------------------------------
# Step 4: Generate node configs and validators.txt
# ---------------------------------------------------------------------------
log "Generating node configs..."
# Create shared validators.txt
VALIDATORS_FILE="$WORKDIR/validators.txt"
{
echo "[validators]"
for i in $(seq 0 $((NUM_NODES - 1))); do
echo "${PUBKEYS[$i]}"
done
} > "$VALIDATORS_FILE"
# Create per-node configs
for i in $(seq 1 "$NUM_NODES"); do
NODE_DIR="$WORKDIR/node$i"
mkdir -p "$NODE_DIR/nudb" "$NODE_DIR/db"
RPC_PORT=$((RPC_PORT_BASE + i - 1))
PEER_PORT=$((PEER_PORT_BASE + i - 1))
SEED="${SEEDS[$((i - 1))]}"
# Build ips_fixed list (all peers except self)
IPS_FIXED=""
for j in $(seq 1 "$NUM_NODES"); do
if [ "$j" -ne "$i" ]; then
IPS_FIXED="${IPS_FIXED}127.0.0.1 $((PEER_PORT_BASE + j - 1))
"
fi
done
cat > "$NODE_DIR/xrpld.cfg" <<EOCFG
[server]
port_rpc
port_peer
[port_rpc]
port = $RPC_PORT
ip = 127.0.0.1
admin = 127.0.0.1
protocol = http
[port_peer]
port = $PEER_PORT
ip = 0.0.0.0
protocol = peer
[node_db]
type=NuDB
path=$NODE_DIR/nudb
online_delete=256
[database_path]
$NODE_DIR/db
[debug_logfile]
$NODE_DIR/debug.log
[validation_seed]
$SEED
[validators_file]
$VALIDATORS_FILE
[ips_fixed]
${IPS_FIXED}
[peer_private]
1
[telemetry]
enabled=1
service_instance_id=Node-${i}
endpoint=http://localhost:4318/v1/traces
exporter=otlp_http
sampling_ratio=1.0
batch_size=512
batch_delay_ms=2000
max_queue_size=2048
trace_rpc=1
trace_transactions=1
trace_consensus=1
trace_peer=0
trace_ledger=1
[rpc_startup]
{ "command": "log_level", "severity": "warning" }
[ssl_verify]
0
EOCFG
log " Node $i config: RPC=$RPC_PORT, Peer=$PEER_PORT"
done
# ---------------------------------------------------------------------------
# Step 5: Start all 6 nodes
# ---------------------------------------------------------------------------
log "Starting $NUM_NODES xrpld nodes..."
for i in $(seq 1 "$NUM_NODES"); do
NODE_DIR="$WORKDIR/node$i"
"$XRPLD" --conf "$NODE_DIR/xrpld.cfg" --start > "$NODE_DIR/stdout.log" 2>&1 &
echo $! > "$NODE_DIR/xrpld.pid"
log " Node $i started (PID $(cat "$NODE_DIR/xrpld.pid"))"
done
# Give nodes a moment to initialize
sleep 5
# ---------------------------------------------------------------------------
# Step 6: Wait for consensus
# ---------------------------------------------------------------------------
log "Waiting for nodes to reach 'proposing' state (timeout: ${CONSENSUS_TIMEOUT}s)..."
start_time=$(date +%s)
nodes_ready=0
while [ "$nodes_ready" -lt "$NUM_NODES" ]; do
elapsed=$(( $(date +%s) - start_time ))
if [ "$elapsed" -ge "$CONSENSUS_TIMEOUT" ]; then
fail "Consensus timeout after ${CONSENSUS_TIMEOUT}s ($nodes_ready/$NUM_NODES nodes ready)"
log "Continuing with partial consensus..."
break
fi
nodes_ready=0
for i in $(seq 1 "$NUM_NODES"); do
RPC_PORT=$((RPC_PORT_BASE + i - 1))
state=$(curl -sf "http://localhost:$RPC_PORT" \
-d '{"method":"server_info"}' 2>/dev/null \
| jq -r '.result.info.server_state' 2>/dev/null || echo "unreachable")
if [ "$state" = "proposing" ]; then
nodes_ready=$((nodes_ready + 1))
fi
done
printf "\r %d/%d nodes proposing (%ds elapsed)..." "$nodes_ready" "$NUM_NODES" "$elapsed"
if [ "$nodes_ready" -lt "$NUM_NODES" ]; then
sleep 3
fi
done
echo ""
if [ "$nodes_ready" -eq "$NUM_NODES" ]; then
ok "All $NUM_NODES nodes reached 'proposing' state"
else
fail "Only $nodes_ready/$NUM_NODES nodes reached 'proposing' state"
fi
# ---------------------------------------------------------------------------
# Step 6b: Wait for validated ledger
# ---------------------------------------------------------------------------
log "Waiting for first validated ledger..."
for attempt in $(seq 1 60); do
val_seq=$(curl -sf "http://localhost:$RPC_PORT_BASE" \
-d '{"method":"server_info"}' 2>/dev/null \
| jq -r '.result.info.validated_ledger.seq // 0' 2>/dev/null || echo 0)
if [ "$val_seq" -gt 2 ] 2>/dev/null; then
ok "First validated ledger: seq $val_seq"
break
fi
if [ "$attempt" -eq 60 ]; then
fail "No validated ledger after 60s"
fi
sleep 1
done
# ---------------------------------------------------------------------------
# Step 7: Exercise RPC spans (Phase 2)
# ---------------------------------------------------------------------------
log "Exercising RPC spans..."
curl -sf "http://localhost:$RPC_PORT_BASE" \
-d '{"method":"server_info"}' > /dev/null
curl -sf "http://localhost:$RPC_PORT_BASE" \
-d '{"method":"server_state"}' > /dev/null
curl -sf "http://localhost:$RPC_PORT_BASE" \
-d '{"method":"ledger","params":[{"ledger_index":"current"}]}' > /dev/null
log "RPC commands sent. Waiting 5s for batch export..."
sleep 5
# ---------------------------------------------------------------------------
# Step 8: Submit transaction (Phase 3)
# ---------------------------------------------------------------------------
log "Submitting Payment transaction..."
# Generate a destination wallet
log " Generating destination wallet..."
wallet_result=$(curl -sf "http://localhost:$RPC_PORT_BASE" \
-d '{"method":"wallet_propose"}')
DEST_ACCOUNT=$(echo "$wallet_result" | jq -r '.result.account_id' 2>/dev/null)
if [ -z "$DEST_ACCOUNT" ] || [ "$DEST_ACCOUNT" = "null" ]; then
fail "Could not generate destination wallet"
DEST_ACCOUNT="rrrrrrrrrrrrrrrrrrrrrhoLvTp" # ACCOUNT_ZERO fallback
fi
log " Destination: $DEST_ACCOUNT"
# Get genesis account info
acct_result=$(curl -sf "http://localhost:$RPC_PORT_BASE" \
-d "{\"method\":\"account_info\",\"params\":[{\"account\":\"$GENESIS_ACCOUNT\"}]}")
seq_num=$(echo "$acct_result" | jq -r '.result.account_data.Sequence' 2>/dev/null || echo "unknown")
log " Genesis account sequence: $seq_num"
# Submit payment
submit_result=$(curl -sf "http://localhost:$RPC_PORT_BASE" -d "{
\"method\": \"submit\",
\"params\": [{
\"secret\": \"$GENESIS_SEED\",
\"tx_json\": {
\"TransactionType\": \"Payment\",
\"Account\": \"$GENESIS_ACCOUNT\",
\"Destination\": \"$DEST_ACCOUNT\",
\"Amount\": \"10000000\"
}
}]
}")
engine_result=$(echo "$submit_result" | jq -r '.result.engine_result' 2>/dev/null || echo "unknown")
tx_hash=$(echo "$submit_result" | jq -r '.result.tx_json.hash' 2>/dev/null || echo "unknown")
if [ "$engine_result" = "tesSUCCESS" ] || [ "$engine_result" = "terQUEUED" ]; then
ok "Transaction submitted: $engine_result (hash: ${tx_hash:0:16}...)"
else
fail "Transaction submission: $engine_result"
log " Full response: $(echo "$submit_result" | jq -c .result 2>/dev/null)"
fi
log "Waiting 15s for consensus round + batch export..."
sleep 15
# ---------------------------------------------------------------------------
# Step 9: Verify Tempo traces
# ---------------------------------------------------------------------------
log "Verifying spans in Tempo..."
# Check service registration
services=$(curl -sf "$TEMPO/api/v2/search/tag/resource.service.name/values" \
| jq -r '.tagValues[].value' 2>/dev/null || echo "")
if echo "$services" | grep -q "rippled"; then
ok "Service 'rippled' registered in Tempo"
else
fail "Service 'rippled' NOT found in Tempo (found: $services)"
fi
log ""
log "--- Phase 2: RPC Spans ---"
check_span "rpc.request"
check_span "rpc.process"
check_span "rpc.command.server_info"
check_span "rpc.command.server_state"
check_span "rpc.command.ledger"
log ""
log "--- Phase 3: Transaction Spans ---"
check_span "tx.process"
check_span "tx.receive"
log ""
log "--- Phase 4: Consensus Spans ---"
check_span "consensus.proposal.send"
check_span "consensus.ledger_close"
check_span "consensus.accept"
check_span "consensus.validation.send"
# ---------------------------------------------------------------------------
# Step 10: Verify Prometheus spanmetrics
# ---------------------------------------------------------------------------
log ""
log "--- Phase 5: Spanmetrics ---"
log "Waiting 20s for Prometheus scrape cycle..."
sleep 20
calls_count=$(curl -sf "$PROM/api/v1/query?query=traces_span_metrics_calls_total" \
| jq '.data.result | length' 2>/dev/null || echo 0)
if [ "$calls_count" -gt 0 ]; then
ok "Prometheus: traces_span_metrics_calls_total ($calls_count series)"
else
fail "Prometheus: traces_span_metrics_calls_total (0 series)"
fi
duration_count=$(curl -sf "$PROM/api/v1/query?query=traces_span_metrics_duration_milliseconds_count" \
| jq '.data.result | length' 2>/dev/null || echo 0)
if [ "$duration_count" -gt 0 ]; then
ok "Prometheus: duration histogram ($duration_count series)"
else
fail "Prometheus: duration histogram (0 series)"
fi
# Check Grafana
if curl -sf http://localhost:3000/api/health > /dev/null 2>&1; then
ok "Grafana: healthy at localhost:3000"
else
fail "Grafana: not reachable at localhost:3000"
fi
# ---------------------------------------------------------------------------
# Step 11: Summary
# ---------------------------------------------------------------------------
echo ""
echo "==========================================================="
echo " INTEGRATION TEST RESULTS"
echo "==========================================================="
printf " \033[1;32mPASSED: %d\033[0m\n" "$PASS"
printf " \033[1;31mFAILED: %d\033[0m\n" "$FAIL"
echo "==========================================================="
echo ""
echo " Observability stack is running:"
echo ""
echo " Tempo: http://localhost:3200"
echo " Grafana: http://localhost:3000"
echo " Prometheus: http://localhost:9090"
echo ""
echo " xrpld nodes (6) are running:"
for i in $(seq 1 "$NUM_NODES"); do
RPC_PORT=$((RPC_PORT_BASE + i - 1))
PEER_PORT=$((PEER_PORT_BASE + i - 1))
echo " Node $i: RPC=localhost:$RPC_PORT Peer=:$PEER_PORT PID=$(cat "$WORKDIR/node$i/xrpld.pid" 2>/dev/null || echo 'unknown')"
done
echo ""
echo " To tear down:"
echo " bash docker/telemetry/integration-test.sh --cleanup"
echo ""
echo "==========================================================="
if [ "$FAIL" -gt 0 ]; then
exit 1
fi

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# OpenTelemetry Collector configuration for rippled development.
#
# Pipelines:
# traces: OTLP receiver -> batch processor -> debug + Tempo + spanmetrics
# metrics: spanmetrics connector -> Prometheus exporter
#
# rippled sends traces via OTLP/HTTP to port 4318. The collector batches
# them, forwards to Tempo, and derives RED metrics via the spanmetrics
# connector, which Prometheus scrapes on port 8889.
receivers:
otlp:
protocols:
grpc:
endpoint: 0.0.0.0:4317
http:
endpoint: 0.0.0.0:4318
processors:
batch:
timeout: 1s
send_batch_size: 100
connectors:
spanmetrics:
# Expose service.instance.id (node public key) as a Prometheus label so
# Grafana dashboards can filter metrics by individual node.
resource_metrics_key_attributes:
- service.instance.id
histogram:
explicit:
buckets: [1ms, 5ms, 10ms, 25ms, 50ms, 100ms, 250ms, 500ms, 1s, 5s]
dimensions:
- name: xrpl.rpc.command
- name: xrpl.rpc.status
- name: xrpl.consensus.mode
- name: xrpl.tx.local
exporters:
debug:
verbosity: detailed
otlp/tempo:
endpoint: tempo:4317
tls:
insecure: true
prometheus:
endpoint: 0.0.0.0:8889
service:
pipelines:
traces:
receivers: [otlp]
processors: [batch]
exporters: [debug, otlp/tempo, spanmetrics]
metrics:
receivers: [spanmetrics]
exporters: [prometheus]

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# Prometheus configuration for scraping spanmetrics from OTel Collector.
global:
scrape_interval: 15s
evaluation_interval: 15s
scrape_configs:
- job_name: otel-collector
static_configs:
- targets: ["otel-collector:8889"]

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# Grafana Tempo configuration for rippled telemetry stack.
#
# Runs in single-binary mode for local development.
# Receives traces via OTLP/gRPC from the OTel Collector and stores
# them locally. Queryable via Grafana Explore using the Tempo datasource.
#
# Search filters are configured on the Grafana datasource side
# (grafana/provisioning/datasources/tempo.yaml). Tempo auto-indexes
# all span attributes for search in single-binary mode.
#
# For production, replace local storage with S3/GCS backend and adjust
# retention via the compactor settings. See:
# https://grafana.com/docs/tempo/latest/configuration/
stream_over_http_enabled: true
server:
http_listen_port: 3200
distributor:
receivers:
otlp:
protocols:
grpc:
endpoint: 0.0.0.0:4317
ingester:
max_block_duration: 5m
compactor:
compaction:
block_retention: 1h
# Enable metrics generator for service graph and span metrics.
# Produces RED metrics (rate, errors, duration) per service/span,
# feeding Grafana's service map visualization.
metrics_generator:
registry:
external_labels:
source: tempo
storage:
path: /var/tempo/generator/wal
remote_write:
- url: http://prometheus:9090/api/v1/write
overrides:
defaults:
metrics_generator:
processors:
- service-graphs
- span-metrics
storage:
trace:
backend: local
wal:
path: /var/tempo/wal
local:
path: /var/tempo/blocks

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# Standalone xrpld configuration with OpenTelemetry enabled.
#
# Usage:
# 1. Start the observability stack:
# docker compose -f docker/telemetry/docker-compose.yml up -d
# 2. Run xrpld in standalone mode:
# ./xrpld --conf docker/telemetry/xrpld-telemetry.cfg -a --start
# 3. Send RPC commands to exercise tracing:
# curl -s http://localhost:5005 -d '{"method":"server_info"}'
# 4. View traces in Jaeger UI: http://localhost:16686
[server]
port_rpc_admin_local
port_ws_admin_local
[port_rpc_admin_local]
port = 5005
ip = 127.0.0.1
admin = 127.0.0.1
protocol = http
[port_ws_admin_local]
port = 6006
ip = 127.0.0.1
admin = 127.0.0.1
protocol = ws
[node_db]
type=NuDB
path=docker/telemetry/data/nudb
online_delete=256
advisory_delete=0
[database_path]
docker/telemetry/data
[debug_logfile]
docker/telemetry/data/debug.log
[rpc_startup]
{ "command": "log_level", "severity": "debug" }
[ssl_verify]
0
# --- OpenTelemetry tracing ---
[telemetry]
enabled=1
service_instance_id=rippled-standalone
endpoint=http://localhost:4318/v1/traces
exporter=otlp_http
sampling_ratio=1.0
batch_size=512
batch_delay_ms=5000
max_queue_size=2048
trace_rpc=1
trace_transactions=1
trace_consensus=1
trace_peer=0
trace_ledger=1

275
docs/build/telemetry.md vendored Normal file
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@@ -0,0 +1,275 @@
# OpenTelemetry Tracing for Rippled
This document explains how to build rippled with OpenTelemetry distributed tracing support, configure the runtime telemetry options, and set up the observability backend to view traces.
- [OpenTelemetry Tracing for Rippled](#opentelemetry-tracing-for-rippled)
- [Overview](#overview)
- [Building with Telemetry](#building-with-telemetry)
- [Summary](#summary)
- [Build steps](#build-steps)
- [Install dependencies](#install-dependencies)
- [Call CMake](#call-cmake)
- [Build](#build)
- [Building without telemetry](#building-without-telemetry)
- [Runtime Configuration](#runtime-configuration)
- [Configuration options](#configuration-options)
- [Observability Stack](#observability-stack)
- [Start the stack](#start-the-stack)
- [Verify the stack](#verify-the-stack)
- [View traces in Grafana Explore](#view-traces-in-grafana-explore)
- [Running Tests](#running-tests)
- [Troubleshooting](#troubleshooting)
- [No traces appear in Grafana](#no-traces-appear-in-grafana)
- [Conan lockfile error](#conan-lockfile-error)
- [CMake target not found](#cmake-target-not-found)
- [Architecture](#architecture)
- [Key files](#key-files)
- [Conditional compilation](#conditional-compilation)
## Overview
Rippled supports optional [OpenTelemetry](https://opentelemetry.io/) distributed tracing.
When enabled, it instruments RPC requests with trace spans that are exported via
OTLP/HTTP to an OpenTelemetry Collector, which forwards them to a tracing backend
such as Grafana Tempo.
Telemetry is **off by default** at both compile time and runtime:
- **Compile time**: The Conan option `telemetry` and CMake option `telemetry` must be set to `True`/`ON`.
When disabled, all tracing macros compile to `((void)0)` with zero overhead.
- **Runtime**: The `[telemetry]` config section must set `enabled=1`.
When disabled at runtime, a no-op implementation is used.
## Building with Telemetry
### Summary
Follow the same instructions as mentioned in [BUILD.md](../../BUILD.md) but with the following changes:
1. Pass `-o telemetry=True` to `conan install` to pull the `opentelemetry-cpp` dependency.
2. CMake will automatically pick up `telemetry=ON` from the Conan-generated toolchain.
3. Build as usual.
---
### Build steps
```bash
cd /path/to/rippled
rm -rf .build
mkdir .build
cd .build
```
#### Install dependencies
The `telemetry` option adds `opentelemetry-cpp/1.18.0` as a dependency.
If the Conan lockfile does not yet include this package, bypass it with `--lockfile=""`.
```bash
conan install .. \
--output-folder . \
--build missing \
--settings build_type=Debug \
-o telemetry=True \
-o tests=True \
-o xrpld=True \
--lockfile=""
```
> **Note**: The first build with telemetry may take longer as `opentelemetry-cpp`
> and its transitive dependencies are compiled from source.
#### Call CMake
The Conan-generated toolchain file sets `telemetry=ON` automatically.
No additional CMake flags are needed beyond the standard ones.
```bash
cmake .. -G Ninja \
-DCMAKE_TOOLCHAIN_FILE:FILEPATH=build/generators/conan_toolchain.cmake \
-DCMAKE_BUILD_TYPE=Debug \
-Dtests=ON -Dxrpld=ON
```
You should see in the CMake output:
```
-- OpenTelemetry tracing enabled
```
#### Build
```bash
cmake --build . --parallel $(nproc)
```
### Building without telemetry
Omit the `-o telemetry=True` option (or pass `-o telemetry=False`).
The `opentelemetry-cpp` dependency will not be downloaded,
the `XRPL_ENABLE_TELEMETRY` preprocessor define will not be set,
and all tracing macros will compile to no-ops.
The resulting binary is identical to one built before telemetry support was added.
## Runtime Configuration
Add a `[telemetry]` section to your `xrpld.cfg` file:
```ini
[telemetry]
enabled=1
service_name=rippled
endpoint=http://localhost:4318/v1/traces
sampling_ratio=1.0
trace_rpc=1
trace_transactions=1
trace_consensus=1
trace_peer=0
```
### Configuration options
| Option | Type | Default | Description |
| --------------------- | ------ | --------------------------------- | -------------------------------------------------- |
| `enabled` | int | `0` | Enable (`1`) or disable (`0`) telemetry at runtime |
| `service_name` | string | `rippled` | Service name reported in traces |
| `service_instance_id` | string | node public key | Unique instance identifier |
| `exporter` | string | `otlp_http` | Exporter type |
| `endpoint` | string | `http://localhost:4318/v1/traces` | OTLP/HTTP collector endpoint |
| `use_tls` | int | `0` | Enable TLS for the exporter connection |
| `tls_ca_cert` | string | (empty) | Path to CA certificate for TLS |
| `sampling_ratio` | double | `1.0` | Fraction of traces to sample (`0.0` to `1.0`) |
| `batch_size` | uint32 | `512` | Maximum spans per export batch |
| `batch_delay_ms` | uint32 | `5000` | Maximum delay (ms) before flushing a batch |
| `max_queue_size` | uint32 | `2048` | Maximum spans queued in memory |
| `trace_rpc` | int | `1` | Enable RPC request tracing |
| `trace_transactions` | int | `1` | Enable transaction lifecycle tracing |
| `trace_consensus` | int | `1` | Enable consensus round tracing |
| `trace_peer` | int | `0` | Enable peer message tracing (high volume) |
| `trace_ledger` | int | `1` | Enable ledger close tracing |
## Observability Stack
A Docker Compose stack is provided in `docker/telemetry/` with three services:
| Service | Port | Purpose |
| ------------------ | ---------------------------------------------- | --------------------------------------------------- |
| **OTel Collector** | `4317` (gRPC), `4318` (HTTP), `13133` (health) | Receives OTLP spans, batches, and forwards to Tempo |
| **Tempo** | `3200` (HTTP API) | Trace storage backend |
| **Grafana** | `3000` | Dashboards (Tempo pre-configured as datasource) |
### Start the stack
```bash
docker compose -f docker/telemetry/docker-compose.yml up -d
```
### Verify the stack
```bash
# Collector health
curl http://localhost:13133
# Grafana (Explore -> Tempo for traces)
open http://localhost:3000
```
### View traces in Grafana Explore
1. Open `http://localhost:3000` in a browser.
2. Navigate to **Explore** and select the **Tempo** datasource.
3. Use **Search** or **TraceQL** to find traces by service name (e.g. `rippled`).
4. Click into any trace to see the span tree and attributes.
Traced RPC operations produce a span hierarchy like:
```
rpc.request
└── rpc.command.server_info (xrpl.rpc.command=server_info, xrpl.rpc.status=success)
```
Each span includes attributes:
- `xrpl.rpc.command` — the RPC method name
- `xrpl.rpc.version` — API version
- `xrpl.rpc.role``admin` or `user`
- `xrpl.rpc.status``success` or `error`
## Running Tests
Unit tests run with the telemetry-enabled build regardless of whether the
observability stack is running. When no collector is available, the exporter
silently drops spans with no impact on test results.
```bash
# Run all RPC tests
./xrpld --unittest=RPCCall,ServerInfo,AccountTx,LedgerRPC,Transaction --unittest-jobs $(nproc)
# Run the full test suite
./xrpld --unittest --unittest-jobs $(nproc)
```
To generate traces during manual testing, start rippled in standalone mode:
```bash
./xrpld --conf /path/to/xrpld.cfg --standalone --start
```
Then send RPC requests:
```bash
curl -s -X POST http://127.0.0.1:5005/ \
-H "Content-Type: application/json" \
-d '{"method":"server_info","params":[{}]}'
```
## Troubleshooting
### No traces appear in Grafana
1. Confirm the OTel Collector is running: `docker compose -f docker/telemetry/docker-compose.yml ps`
2. Check collector logs for errors: `docker compose -f docker/telemetry/docker-compose.yml logs otel-collector`
3. Confirm `[telemetry] enabled=1` is set in the rippled config.
4. Confirm `endpoint` points to the correct collector address (`http://localhost:4318/v1/traces`).
5. Wait for the batch delay to elapse (default `5000` ms) before checking Grafana Explore.
### Conan lockfile error
If you see `ERROR: Requirement 'opentelemetry-cpp/1.18.0' not in lockfile 'requires'`,
the lockfile was generated without the telemetry dependency.
Pass `--lockfile=""` to bypass the lockfile, or regenerate it with telemetry enabled.
### CMake target not found
If CMake reports that `opentelemetry-cpp` targets are not found,
ensure you ran `conan install` with `-o telemetry=True` and that the
Conan-generated toolchain file is being used.
The Conan package provides a single umbrella target
`opentelemetry-cpp::opentelemetry-cpp` (not individual component targets).
## Architecture
### Key files
| File | Purpose |
| ---------------------------------------------- | ----------------------------------------------------------- |
| `include/xrpl/telemetry/Telemetry.h` | Abstract telemetry interface and `Setup` struct |
| `include/xrpl/telemetry/SpanGuard.h` | RAII span guard (activates scope, ends span on destruction) |
| `src/libxrpl/telemetry/Telemetry.cpp` | OTel-backed implementation (`TelemetryImpl`) |
| `src/libxrpl/telemetry/TelemetryConfig.cpp` | Config parser (`setup_Telemetry()`) |
| `src/libxrpl/telemetry/NullTelemetry.cpp` | No-op implementation (used when disabled) |
| `src/xrpld/telemetry/TracingInstrumentation.h` | Convenience macros (`XRPL_TRACE_RPC`, etc.) |
| `src/xrpld/rpc/detail/ServerHandler.cpp` | RPC entry point instrumentation |
| `src/xrpld/rpc/detail/RPCHandler.cpp` | Per-command instrumentation |
| `docker/telemetry/docker-compose.yml` | Observability stack (Collector + Tempo + Grafana) |
| `docker/telemetry/otel-collector-config.yaml` | OTel Collector pipeline configuration |
### Conditional compilation
All OpenTelemetry SDK headers are guarded behind `#ifdef XRPL_ENABLE_TELEMETRY`.
The instrumentation macros in `TracingInstrumentation.h` compile to `((void)0)` when
the define is absent.
At runtime, if `enabled=0` is set in config (or the section is omitted), a
`NullTelemetry` implementation is used that returns no-op spans.
This two-layer approach ensures zero overhead when telemetry is not wanted.

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# External Dashboard Parity — Design Spec
> **Date**: 2026-03-30
> **Status**: Draft
> **Source**: [realgrapedrop/xrpl-validator-dashboard](https://github.com/realgrapedrop/xrpl-validator-dashboard)
> **Jira Epic**: RIPD-5060
## Summary
Integrate 29 missing metrics, 18 alert rules, and enriched span attributes from the community `xrpl-validator-dashboard` into rippled's native OpenTelemetry instrumentation. Changes are distributed across phases 2, 3, 4, 6, 7, 9, 10, and 11 of the OTel PR chain.
## Gap Analysis
### Coverage Breakdown (86 external metrics)
| Status | Count | Notes |
| ------------------ | ----- | ------------------------------------------------------------- |
| Already covered | 30 | peer_count, load_factor, io_latency, uptime, overlay traffic |
| Partially covered | 3 | state_value encoding, NuDB granularity, validation_quorum |
| Missing | 29 | Validation agreement, ledger economy, peer quality, UNL health |
| N/A (external) | 24 | Monitor health, realtime duplicates, system metrics |
### Missing Metrics by Category
| Category | Metrics | Count |
| ----------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----- |
| Validation Agreement | `validations_sent_total`, `validations_checked_total`, `validation_agreements_total`, `validation_missed_total`, `validation_agreement_pct_1h/24h`, `validation_agreements_1h/24h`, `validation_missed_1h/24h`, `validation_event` | 11 |
| Ledger Economy | `ledgers_closed_total`, `ledger_age_seconds`, `base_fee_xrp`, `reserve_base_xrp`, `reserve_inc_xrp`, `transaction_rate` | 6 |
| State Tracking | `time_in_current_state_seconds`, `state_changes_total`, `validator_state_info` | 3 |
| Peer Quality | `peers_insane`, `peer_latency_p90_ms` | 2 |
| Validator Health | `amendment_blocked`, `unl_expiry_days` | 2 |
| Upgrade Awareness | `peers_higher_version_pct`, `upgrade_recommended` | 2 |
| Storage / Other | `ledger_nudb_bytes`, `jq_trans_overflow_total`, `initial_sync_duration_seconds` | 3 |
### Alert Rules (18 total, from external dashboard)
| Group | Count | Rules |
| ----------- | ----- | ---------------------------------------------------------------------------------------------------- |
| Critical | 8 | Agreement <90%, not proposing, unhealthy state, amendment blocked, UNL expiring, IO latency, load factor, peer count <5 |
| Network | 3 | Peer drop >10%/30%, P90 latency + disconnect correlation |
| Performance | 7 | CPU >80%, memory >90%, disk >85%, job queue overflow, upgrade recommended, tx rate drop, stale ledger |
---
## Branch-to-Change Mapping
### Phase 2 — `pratik/otel-phase2-rpc-tracing`
> **Ref**: Adds to existing Phase 2 task list. Consumed by Phase 7 (MetricsRegistry) and Phase 10 (validation checks).
**Task 2.8: RPC Span Attribute Enrichment**
Add node-level health context to every `rpc.command.*` span so operators can correlate RPC behavior with node state.
New span attributes on `rpc.command.*`:
| Attribute | Type | Source | Value Example |
| ----------------------------- | ------ | ---------------------------------- | ------------------------ |
| `xrpl.node.amendment_blocked` | bool | `app_.getOPs().isAmendmentBlocked()` | `true` |
| `xrpl.node.server_state` | string | `app_.getOPs().strOperatingMode()` | `"full"`, `"syncing"` |
**File**: `src/xrpld/rpc/detail/RPCHandler.cpp` (in the `rpc.command.*` span creation block, after existing setAttribute calls)
**Rationale**: RPC is the operator's primary interaction point. When a node is amendment-blocked or degraded, every RPC response is suspect. Tagging spans with this state enables Jaeger queries like `{name=~"rpc.command.*"} | xrpl.node.amendment_blocked = true` to find all RPCs served during a blocked period.
**Exit Criteria**:
- [ ] `rpc.command.server_info` spans carry `xrpl.node.amendment_blocked` and `xrpl.node.server_state` attributes
- [ ] No measurable latency impact (attribute values are cached atomics, not computed per-call)
---
### Phase 3 — `pratik/otel-phase3-tx-tracing`
> **Ref**: Adds to existing Phase 3 task list. Consumed by Phase 10 (validation checks).
**Task 3.7: Transaction Span Peer Version Attribute**
Add the relaying peer's rippled version to transaction receive spans to enable version-mismatch correlation.
New span attribute on `tx.receive`:
| Attribute | Type | Source | Value Example |
| ------------------- | ------ | ------------------- | ------------------ |
| `xrpl.peer.version` | string | `peer->getVersion()` | `"rippled-2.4.0"` |
**File**: `src/xrpld/overlay/detail/PeerImp.cpp` (in the `tx.receive` span block, after existing `xrpl.peer.id` setAttribute)
**Rationale**: Transaction relay is where version mismatches cause subtle serialization or validation bugs. Tracing "this tx came from a v2.3.0 peer" helps diagnose compatibility issues during network upgrades.
**Exit Criteria**:
- [ ] `tx.receive` spans carry `xrpl.peer.version` attribute with a non-empty version string
- [ ] Attribute is omitted (not empty-string) when `getVersion()` returns empty
---
### Phase 4 — `pratik/otel-phase4-consensus-tracing`
> **Ref**: Adds to existing Phase 4 task list. Provides the span-level foundation that Phase 7 (ValidationTracker) builds upon. Consumed by Phase 10 (validation checks).
**Task 4.8: Consensus Validation Span Enrichment**
Add ledger hash and validation type to validation spans on both send and receive paths. This enables trace-level agreement analysis — filter by ledger hash to see which validators agreed.
New span attributes on `consensus.validation.send`:
| Attribute | Type | Source | Value Example |
| ---------------------------- | ------ | --------------------------------------- | -------------------------- |
| `xrpl.validation.ledger_hash` | string | Ledger hash from `validate()` call args | `"A1B2C3..."` (64-char hex) |
| `xrpl.validation.full` | bool | Whether this is a full validation | `true` |
New span attributes on `peer.validation.receive`:
| Attribute | Type | Source | Value Example |
| --------------------------------- | ------ | --------------------------------------- | -------------------------- |
| `xrpl.peer.validation.ledger_hash` | string | From deserialized STValidation object | `"A1B2C3..."` (64-char hex) |
| `xrpl.peer.validation.full` | bool | From STValidation flags | `true` |
New span attributes on `consensus.accept`:
| Attribute | Type | Source | Value Example |
| ------------------------------------ | ----- | -------------------------------------------- | ------------- |
| `xrpl.consensus.validation_quorum` | int64 | `app_.validators().quorum()` | `28` |
| `xrpl.consensus.proposers_validated` | int64 | `result.proposers` from consensus result | `35` |
**Files**:
- `src/xrpld/app/consensus/RCLConsensus.cpp` (validation.send and accept spans)
- `src/xrpld/overlay/detail/PeerImp.cpp` (peer.validation.receive span)
**Rationale**: The external dashboard's most valuable feature is validation agreement tracking. By recording the ledger hash on both outgoing and incoming validation spans, we create the raw data for agreement analysis at the trace level. Phase 7's ValidationTracker builds the metric-level aggregation on top of this.
**Exit Criteria**:
- [ ] `consensus.validation.send` spans carry `xrpl.validation.ledger_hash` and `xrpl.validation.full`
- [ ] `peer.validation.receive` spans carry `xrpl.peer.validation.ledger_hash` and `xrpl.peer.validation.full`
- [ ] `consensus.accept` spans carry `xrpl.consensus.validation_quorum` and `xrpl.consensus.proposers_validated`
- [ ] Ledger hash attributes match between send and receive for the same ledger
---
### Phase 6 — `pratik/otel-phase6-statsd`
> **Ref**: Adds to existing Phase 6 scope. No separate task list file exists for Phase 6 per project convention.
**Addition: Bridge `peerDisconnectsCharges_` metric**
The overlay already tracks resource-limit disconnects via `OverlayImpl::Stats::peerDisconnectsCharges_` (a `beast::insight::Gauge`). This metric is registered but not included in the StatsD bridge mapping.
**What to do**:
- Ensure `rippled_Overlay_Peer_Disconnects_Charges` appears in the StatsD-to-Prometheus metric name mapping
- Verify the metric appears in Prometheus after StatsD bridge is active
**File**: `src/xrpld/overlay/detail/OverlayImpl.cpp`
**Prometheus name**: `rippled_Overlay_Peer_Disconnects_Charges`
---
### Phase 7 — `pratik/otel-phase7-native-metrics`
> **Ref**: Adds to existing Phase 7 task list. This is the largest addition. Depends on Phase 4 span attributes for validation tracking context. Consumed by Phase 9 (dashboards), Phase 10 (validation), Phase 11 (alerts).
**Task 7.8: ValidationTracker — Validation Agreement Computation**
The most valuable missing component. A stateful class that tracks whether our validator's validations agree with network consensus, maintaining rolling 1h and 24h windows.
**Architecture**:
```
consensus.validation.send ─────> ValidationTracker ──────> MetricsRegistry
(records our validation (reconciles after (exports agreement
for ledger X) 8s grace period) gauges every 10s)
ledger.validate ───────────────> ValidationTracker
(records which ledger (marks ledger X as
network validated) agreed or missed)
```
**Design**:
```cpp
/// Tracks validation agreement between this node and network consensus.
///
/// ValidationTracker
/// ├── recordOurValidation(ledgerHash, ledgerSeq) // called when we send
/// ├── recordNetworkValidation(ledgerHash, seq) // called on ledger validate
/// ├── reconcile() // called periodically (timer)
/// ├── agreementPct1h() -> double // 0.0-100.0
/// ├── agreementPct24h() -> double
/// ├── agreements1h() -> uint64_t
/// ├── missed1h() -> uint64_t
/// ├── agreements24h() -> uint64_t
/// ├── missed24h() -> uint64_t
/// ├── totalAgreements() -> uint64_t
/// ├── totalMissed() -> uint64_t
/// ├── totalValidationsSent() -> uint64_t
/// └── totalValidationsChecked() -> uint64_t // all network validations seen
class ValidationTracker
{
// Ring buffer of pending ledger events (max 1000)
struct LedgerEvent {
uint256 ledgerHash;
LedgerIndex seq;
TimePoint closeTime;
bool weValidated = false; // did we send a validation for this ledger?
bool networkValidated = false; // did network validate this ledger?
bool reconciled = false; // has 8s grace period elapsed?
bool agreed = false; // after reconciliation: did we agree?
};
// Sliding window deques for pre-computed window stats
struct WindowEvent {
TimePoint time;
bool agreed;
};
std::deque<WindowEvent> window1h_; // events in last 1 hour
std::deque<WindowEvent> window24h_; // events in last 24 hours
// Reconciliation: 8s grace period after ledger close.
// If our validation hasn't arrived by then, mark as missed.
// 5-minute late repair: if a late validation arrives, correct the miss.
static constexpr auto kGracePeriod = std::chrono::seconds(8);
static constexpr auto kLateRepairWindow = std::chrono::minutes(5);
};
```
**Recording sites** (modifications to consensus code from Phase 7 branch):
| Hook Point | File | What to Record |
| --- | --- | --- |
| `validate()` in `doAccept()` | RCLConsensus.cpp | `tracker.recordOurValidation(ledgerHash, seq)` |
| `onValidation()` callback | RCLValidations path | `tracker.recordNetworkValidation(...)` — increment `validationsChecked` |
| LedgerMaster fully-validated | LedgerMaster.cpp | `tracker.recordNetworkValidation(validatedHash, seq)` |
**Key new files**:
- `src/xrpld/telemetry/ValidationTracker.h`
- `src/xrpld/telemetry/detail/ValidationTracker.cpp`
**Key modified files**:
- `src/xrpld/telemetry/MetricsRegistry.h` (add ValidationTracker member)
- `src/xrpld/telemetry/MetricsRegistry.cpp` (add gauge callback reading from tracker)
- `src/xrpld/app/consensus/RCLConsensus.cpp` (add recording hooks)
- `src/xrpld/app/ledger/detail/LedgerMaster.cpp` (add recording hook)
**Exit Criteria**:
- [ ] `ValidationTracker` correctly tracks agreement with 8s grace period
- [ ] 5-minute late repair corrects false-positive misses
- [ ] Thread-safe (atomics + mutex for window deques)
- [ ] Rolling windows correctly evict stale entries
- [ ] Unit tests for: normal agreement, missed validation, late repair, window eviction
---
**Task 7.9: Validator Health Observable Gauges**
New MetricsRegistry observable gauge for amendment, UNL, and quorum health.
| Gauge Name | Label `metric=` | Type | Source |
| ------------------------- | ----------------------- | ------- | ----------------------------------------- |
| `rippled_validator_health` | `amendment_blocked` | int64 | `app_.getOPs().isAmendmentBlocked()` → 0/1 |
| | `unl_blocked` | int64 | `app_.getOPs().isUNLBlocked()` → 0/1 |
| | `unl_expiry_days` | double | `app_.validators().expires()` → days until expiry |
| | `validation_quorum` | int64 | `app_.validators().quorum()` |
**File**: `src/xrpld/telemetry/MetricsRegistry.cpp` (new gauge callback in `registerAsyncGauges()`)
**Exit Criteria**:
- [ ] All 4 label values emitted every 10s
- [ ] `unl_expiry_days` is negative when expired, positive when active
- [ ] Values visible in Prometheus
---
**Task 7.10: Peer Quality Observable Gauges**
New MetricsRegistry observable gauge for peer health aggregates.
| Gauge Name | Label `metric=` | Type | Source |
| ----------------------- | ------------------------- | ------- | ---------------------------------------------- |
| `rippled_peer_quality` | `peer_latency_p90_ms` | double | Iterate peers, compute P90 from `latency_` |
| | `peers_insane_count` | int64 | Count peers with `tracking_ == diverged` |
| | `peers_higher_version_pct` | double | Compare `getVersion()` to own version |
| | `upgrade_recommended` | int64 | 1 if `peers_higher_version_pct > 60%` |
**Implementation note**: The callback iterates `app_.overlay().foreach(...)` to collect per-peer latency and version data. This runs every 10s on the metrics reader thread — acceptable overhead for ~50-200 peers.
**File**: `src/xrpld/telemetry/MetricsRegistry.cpp`
**Exit Criteria**:
- [ ] P90 latency computed correctly (sort peer latencies, pick 90th percentile)
- [ ] Insane count matches `peers` RPC output
- [ ] Version comparison handles format variations (e.g., "rippled-2.4.0-rc1")
- [ ] Values visible in Prometheus
---
**Task 7.11: Ledger Economy Observable Gauges**
New MetricsRegistry observable gauge for fee and ledger metrics.
| Gauge Name | Label `metric=` | Type | Source |
| ------------------------ | ---------------------- | ------- | ----------------------------------------------- |
| `rippled_ledger_economy` | `base_fee_xrp` | double | `app_.getFeeTrack().getBaseFee()` → drops |
| | `reserve_base_xrp` | double | From validated ledger fee settings |
| | `reserve_inc_xrp` | double | From validated ledger fee settings |
| | `ledger_age_seconds` | double | `now - lastValidatedCloseTime` |
| | `transaction_rate` | double | Derived: tx count delta / time delta |
**File**: `src/xrpld/telemetry/MetricsRegistry.cpp`
**Exit Criteria**:
- [ ] Fee values match `server_info` RPC output
- [ ] `ledger_age_seconds` increases monotonically between ledger closes, resets on close
- [ ] `transaction_rate` is smoothed (rolling average, not instantaneous)
---
**Task 7.12: State Tracking Observable Gauges**
New MetricsRegistry observable gauge for node state duration.
| Gauge Name | Label `metric=` | Type | Source |
| ------------------------- | -------------------------------- | ------- | ---------------------------------------------- |
| `rippled_state_tracking` | `state_value` | int64 | 0-7 numeric encoding matching external dashboard |
| | `time_in_current_state_seconds` | double | `now - lastModeChangeTime` |
**State value encoding**:
rippled's `OperatingMode` enum maps 0-4 (DISCONNECTED through FULL). The external dashboard extends this to 0-6 by combining operating mode with consensus participation:
| Value | State | Source |
| ----- | ------------ | ---------------------------------------------------------------- |
| 0 | disconnected | `OperatingMode::DISCONNECTED` |
| 1 | connected | `OperatingMode::CONNECTED` |
| 2 | syncing | `OperatingMode::SYNCING` |
| 3 | tracking | `OperatingMode::TRACKING` |
| 4 | full | `OperatingMode::FULL` and not validating |
| 5 | validating | `OperatingMode::FULL` and `mConsensus.validating()` is true |
| 6 | proposing | `OperatingMode::FULL` and consensus mode is `proposing` |
**Note**: Values 5-6 require checking both `OperatingMode` and `ConsensusMode`. The callback should derive these from `app_.getOPs().getOperatingMode()` combined with `mConsensus.mode()`. If operating mode is FULL and consensus is proposing → 6; if FULL and validating → 5; otherwise use the raw OperatingMode enum value.
**File**: `src/xrpld/telemetry/MetricsRegistry.cpp`
**Exit Criteria**:
- [ ] `state_value` matches external dashboard encoding
- [ ] `time_in_current_state_seconds` resets on mode change
---
**Task 7.13: Storage Detail Observable Gauge**
| Gauge Name | Label `metric=` | Type | Source |
| -------------------------- | ---------------- | ----- | ----------------------------------------- |
| `rippled_storage_detail` | `nudb_bytes` | int64 | NuDB backend file size (filesystem stat) |
**File**: `src/xrpld/telemetry/MetricsRegistry.cpp`
**Exit Criteria**:
- [ ] NuDB file size reported in bytes
- [ ] Gracefully returns 0 if NuDB not configured
---
**Task 7.14: New Synchronous Counters**
New counters incremented at event sites. Declared in MetricsRegistry, recording sites added in consensus/overlay/network code.
| Counter Name | Increment Site | Source File |
| -------------------------------------- | --------------------------------- | ---------------------- |
| `rippled_ledgers_closed_total` | `onAccept()` in consensus | RCLConsensus.cpp |
| `rippled_validations_sent_total` | `validate()` in consensus | RCLConsensus.cpp |
| `rippled_validations_checked_total` | Network validation received | LedgerMaster.cpp |
| `rippled_validation_agreements_total` | ValidationTracker reconciliation | ValidationTracker.cpp |
| `rippled_validation_missed_total` | ValidationTracker reconciliation | ValidationTracker.cpp |
| `rippled_state_changes_total` | `setMode()` in NetworkOPs | NetworkOPs.cpp |
| `rippled_jq_trans_overflow_total` | Job queue overflow path | JobQueue.cpp |
**Key modified files**:
- `src/xrpld/telemetry/MetricsRegistry.h/.cpp` (counter declarations)
- `src/xrpld/app/consensus/RCLConsensus.cpp` (recording: ledgers_closed, validations_sent)
- `src/xrpld/app/ledger/detail/LedgerMaster.cpp` (recording: validations_checked)
- `src/xrpld/app/misc/NetworkOPs.cpp` (recording: state_changes)
**Exit Criteria**:
- [ ] All 7 counters monotonically increase during normal operation
- [ ] Counter values match expected rates (e.g., ledgers_closed ≈ 1 per 3-5s)
- [ ] Values visible in Prometheus
---
**Task 7.15: Validation Agreement Observable Gauge**
Reads from the `ValidationTracker` (Task 7.8) to export rolling window stats.
| Gauge Name | Label `metric=` | Type | Source |
| --------------------------------- | -------------------------- | ------ | ------------------------------- |
| `rippled_validation_agreement` | `agreement_pct_1h` | double | `tracker.agreementPct1h()` |
| | `agreements_1h` | int64 | `tracker.agreements1h()` |
| | `missed_1h` | int64 | `tracker.missed1h()` |
| | `agreement_pct_24h` | double | `tracker.agreementPct24h()` |
| | `agreements_24h` | int64 | `tracker.agreements24h()` |
| | `missed_24h` | int64 | `tracker.missed24h()` |
**File**: `src/xrpld/telemetry/MetricsRegistry.cpp`
**Exit Criteria**:
- [ ] Agreement percentages in range [0.0, 100.0]
- [ ] Window stats match manual count from validation counters
- [ ] Percentages stabilize after 1h/24h of operation
---
### Phase 9 — `pratik/otel-phase9-metric-gap-fill`
> **Ref**: Adds to existing Phase 9 task list. Depends on Phase 7 gauges/counters. Consumed by Phase 10 (dashboard load checks).
**Task 9.11: Validator Health Dashboard**
New Grafana dashboard: `rippled-validator-health.json`
| Panel | Type | PromQL |
| --------------------------- | ---------- | -------------------------------------------------------------------- |
| Agreement % (1h) | stat | `rippled_validation_agreement{metric="agreement_pct_1h"}` |
| Agreement % (24h) | stat | `rippled_validation_agreement{metric="agreement_pct_24h"}` |
| Agreements vs Missed (1h) | bargauge | `agreements_1h` and `missed_1h` side by side |
| Agreements vs Missed (24h) | bargauge | `agreements_24h` and `missed_24h` side by side |
| Validation Rate | stat | `rate(rippled_validations_sent_total[5m]) * 60` |
| Validations Checked Rate | stat | `rate(rippled_validations_checked_total[5m]) * 60` |
| Amendment Blocked | stat | `rippled_validator_health{metric="amendment_blocked"}` |
| UNL Expiry (days) | stat | `rippled_validator_health{metric="unl_expiry_days"}` |
| Validation Quorum | stat | `rippled_validator_health{metric="validation_quorum"}` |
| State Value Timeline | timeseries | `rippled_state_tracking{metric="state_value"}` |
| Time in Current State | stat | `rippled_state_tracking{metric="time_in_current_state_seconds"}` |
| State Changes Rate | stat | `rate(rippled_state_changes_total[1h])` |
| Ledgers Closed Rate | stat | `rate(rippled_ledgers_closed_total[5m]) * 60` |
**Dashboard conventions**: `$node` template variable for `exported_instance` filtering, dark theme, matching existing panel sizes and color schemes.
---
**Task 9.12: Peer Quality Dashboard**
New Grafana dashboard: `rippled-peer-quality.json`
| Panel | Type | PromQL |
| --------------------------- | ---------- | --------------------------------------------------------------------- |
| P90 Peer Latency | timeseries | `rippled_peer_quality{metric="peer_latency_p90_ms"}` |
| Insane/Diverged Peers | stat | `rippled_peer_quality{metric="peers_insane_count"}` |
| Higher Version Peers % | stat | `rippled_peer_quality{metric="peers_higher_version_pct"}` |
| Upgrade Recommended | stat | `rippled_peer_quality{metric="upgrade_recommended"}` |
| Resource Disconnects | timeseries | `rippled_Overlay_Peer_Disconnects_Charges` |
| Inbound vs Outbound | bargauge | `rippled_Peer_Finder_Active_Inbound_Peers`, `..._Outbound_Peers` |
---
**Task 9.13: Ledger Economy Dashboard Panels**
Add a "Ledger Economy" row to the existing `system-node-health.json` dashboard:
| Panel | Type | PromQL |
| --------------------- | ---------- | -------------------------------------------------------------- |
| Base Fee (drops) | stat | `rippled_ledger_economy{metric="base_fee_xrp"}` |
| Reserve Base (drops) | stat | `rippled_ledger_economy{metric="reserve_base_xrp"}` |
| Reserve Inc (drops) | stat | `rippled_ledger_economy{metric="reserve_inc_xrp"}` |
| Ledger Age | stat | `rippled_ledger_economy{metric="ledger_age_seconds"}` |
| Transaction Rate | timeseries | `rippled_ledger_economy{metric="transaction_rate"}` |
---
### Phase 10 — `pratik/otel-phase10-workload-validation`
> **Ref**: Adds to existing Phase 10 task list. Validates all additions from Phases 2-9.
**Task 10.6: External Dashboard Parity Validation Checks**
Add checks to `validate_telemetry.py` for all new span attributes and metrics.
**New span attribute checks (~8)**:
| Span Name | New Attribute |
| --------------------------- | ------------------------------------ |
| `rpc.command.server_info` | `xrpl.node.amendment_blocked` |
| `rpc.command.server_info` | `xrpl.node.server_state` |
| `tx.receive` | `xrpl.peer.version` |
| `consensus.validation.send` | `xrpl.validation.ledger_hash` |
| `consensus.validation.send` | `xrpl.validation.full` |
| `peer.validation.receive` | `xrpl.peer.validation.ledger_hash` |
| `consensus.accept` | `xrpl.consensus.validation_quorum` |
| `consensus.accept` | `xrpl.consensus.proposers_validated` |
**New metric existence checks (~13)**:
| Metric Name |
| ------------------------------------------------------------- |
| `rippled_validation_agreement{metric="agreement_pct_1h"}` |
| `rippled_validation_agreement{metric="agreement_pct_24h"}` |
| `rippled_validator_health{metric="amendment_blocked"}` |
| `rippled_validator_health{metric="unl_expiry_days"}` |
| `rippled_peer_quality{metric="peer_latency_p90_ms"}` |
| `rippled_peer_quality{metric="peers_insane_count"}` |
| `rippled_ledger_economy{metric="base_fee_xrp"}` |
| `rippled_ledger_economy{metric="transaction_rate"}` |
| `rippled_state_tracking{metric="state_value"}` |
| `rippled_ledgers_closed_total` |
| `rippled_validations_sent_total` |
| `rippled_state_changes_total` |
| `rippled_storage_detail{metric="nudb_bytes"}` |
**New dashboard load checks (~3)**:
| Dashboard |
| --------------------------- |
| `rippled-validator-health` |
| `rippled-peer-quality` |
| `system-node-health` (updated) |
**New metric value sanity checks (~4)**:
| Check | Condition |
| -------------------------------------------------------- | -------------------- |
| `validation_agreement_pct_1h` | in [0, 100] |
| `unl_expiry_days` | > 0 (not expired) |
| `peer_latency_p90_ms` | > 0 (peers exist) |
| `state_value` | in [0, 7] |
**Total new checks: ~28** (bringing total from 73 to ~101)
---
### Phase 11 — (future branch)
> **Ref**: Adds to existing Phase 11 task list. Depends on Phase 7 metrics and Phase 9 dashboards.
**Task 11.9: Alert Rules from External Dashboard**
Port 18 alert rules from the external `xrpl-validator-dashboard` to Grafana alerting provisioning.
**Critical Group** (8 rules, eval interval 10s):
| Rule | Condition | For |
| ------------------------- | ----------------------------------------------------------------- | ---- |
| Agreement Below 90% | `rippled_validation_agreement{metric="agreement_pct_24h"} < 90` | 30s |
| Not Proposing | `rippled_state_tracking{metric="state_value"} < 6` | 10s |
| Unhealthy State | `rippled_state_tracking{metric="state_value"} < 4` | 10s |
| Amendment Blocked | `rippled_validator_health{metric="amendment_blocked"} == 1` | 1m |
| UNL Expiring | `rippled_validator_health{metric="unl_expiry_days"} < 14` | 1h |
| High IO Latency | `histogram_quantile(0.95, rippled_ios_latency_bucket) > 50` | 1m |
| High Load Factor | `rippled_load_factor_metrics{metric="load_factor"} > 1000` | 1m |
| Peer Count Critical | `rippled_server_info{metric="peers"} < 5` | 1m |
**Network Group** (3 rules, eval interval 10s):
| Rule | Condition | For |
| ---------------------- | --------------------------------------------------------------------- | ---- |
| Peer Drop >10% | `delta(rippled_server_info{metric="peers"}[30s]) / ... * 100 < -10` | 30s |
| Peer Drop >30% | Same formula, threshold -30 | 30s |
| P90 Latency + Disconnects | `peer_latency_p90_ms > 500 AND rate(disconnects) > 0` | 2m |
**Performance Group** (7 rules, eval interval 10s):
| Rule | Condition | For |
| -------------------- | ------------------------------------------------------------ | ---- |
| CPU High | Per-core CPU > 80% | 2m |
| Memory Critical | Memory usage > 90% | 1m |
| Disk Warning | Disk usage > 85% | 2m |
| Job Queue Overflow | `rate(rippled_jq_trans_overflow_total[5m]) > 0` | 1m |
| Upgrade Recommended | `rippled_peer_quality{metric="peers_higher_version_pct"} > 60` | 1m |
| TX Rate Drop | Transaction rate dropped > 50% in 5m window | 5m |
| Stale Ledger | `rippled_ledger_economy{metric="ledger_age_seconds"} > 30` | 1m |
**Notification channels**: Template configs for Email/SMTP, Discord, Slack, PagerDuty.
**Files**:
- `docker/telemetry/grafana/alerting/alert-rules.yaml` (new or extend existing)
- `docker/telemetry/grafana/alerting/contact-points.yaml`
- `docker/telemetry/grafana/alerting/notification-policies.yaml`
---
**Task 11.10: Dual-Datasource Architecture Documentation**
Document the external dashboard's "fast path" pattern as a future optimization for real-time panels:
- **Pattern**: A lightweight Prometheus scrape endpoint (separate from OTLP pipeline) that polls critical metrics every 2-5s, bypassing the 10s OTLP metric reader interval and Prometheus scrape interval.
- **Use case**: Real-time state panels (server state, ledger age, peer count) where 10-15s latency is too slow.
- **Decision**: Document as a future option, not implement now. Current 10s interval is acceptable for v1.
**File**: `OpenTelemetryPlan/Phase11_taskList.md` (documentation task, no code)
---
## Documentation Updates
### `docs/telemetry-runbook.md` (on Phase 9 branch)
Add new sections after "Phase 9: OTel Metrics Alerting Rules":
1. **Validator Health Monitoring** — explains agreement tracking, amendment blocked, UNL expiry, with example PromQL queries
2. **Peer Quality Monitoring** — explains P90 latency, insane peers, version awareness
3. **Ledger Economy Monitoring** — explains fee/reserve gauges, transaction rate, ledger age
4. **Validation Agreement Explained** — operator-facing explanation of the reconciliation algorithm (8s grace, 5m late repair), what "missed" means, and when to worry
### `OpenTelemetryPlan/09-data-collection-reference.md` (on Phase 9 branch)
Add new metric tables in a "Phase 7+: External Dashboard Parity" section covering all 29 new metrics with their gauge names, label values, types, and sources.
---
## Cross-Phase Dependency Chain
```
Phase 2 (span attrs: amendment_blocked, server_state)
Phase 3 (span attrs: peer.version)
Phase 4 (span attrs: validation.ledger_hash, validation.full, quorum)
Phase 6 (StatsD bridge: peerDisconnectsCharges)
├── all above rebase into ──>
Phase 7 (ValidationTracker + 7 gauges + 7 counters + agreement gauge)
Phase 9 (3 dashboards + ledger economy panels + runbook + data-collection-ref)
Phase 10 (28 new validation checks in validate_telemetry.py)
Phase 11 (18 alert rules + dual-datasource docs)
```
## Rebase Strategy
After committing changes to each branch (starting from Phase 2):
1. Commit on `pratik/otel-phase2-rpc-tracing`
2. Rebase `phase3` onto `phase2`, resolve conflicts (task list files only — low risk)
3. Commit on `phase3`, rebase `phase4` onto `phase3`
4. Continue through chain: 4 → 5 → 5b → 6 → 7 → 8 → 9 → 10
5. Force-push-with-lease all affected branches
Since these are documentation-only changes (task list .md files), merge conflicts should be minimal — each file is unique to its branch.

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# rippled Telemetry Operator Runbook
## Overview
rippled supports OpenTelemetry distributed tracing to provide visibility into RPC requests, transaction processing, and consensus rounds.
## Quick Start
### 1. Start the observability stack
```bash
docker compose -f docker/telemetry/docker-compose.yml up -d
```
This starts:
- **OTel Collector** on ports 4317 (gRPC) and 4318 (HTTP)
- **Jaeger** UI on http://localhost:16686
- **Prometheus** on http://localhost:9090
- **Grafana** on http://localhost:3000
### 2. Enable telemetry in rippled
Add to your `xrpld.cfg`:
```ini
[telemetry]
enabled=1
endpoint=http://localhost:4318/v1/traces
```
### 3. Build with telemetry support
```bash
conan install . --build=missing -o telemetry=True
cmake --preset default -Dtelemetry=ON
cmake --build --preset default
```
## Configuration Reference
| Option | Default | Description |
| -------------------- | --------------------------------- | ----------------------------------------- |
| `enabled` | `0` | Master switch for telemetry |
| `endpoint` | `http://localhost:4318/v1/traces` | OTLP/HTTP endpoint |
| `exporter` | `otlp_http` | Exporter type |
| `sampling_ratio` | `1.0` | Head-based sampling ratio (0.01.0) |
| `trace_rpc` | `1` | Enable RPC request tracing |
| `trace_transactions` | `1` | Enable transaction tracing |
| `trace_consensus` | `1` | Enable consensus tracing |
| `trace_peer` | `0` | Enable peer message tracing (high volume) |
| `trace_ledger` | `1` | Enable ledger tracing |
| `batch_size` | `512` | Max spans per batch export |
| `batch_delay_ms` | `5000` | Delay between batch exports |
| `max_queue_size` | `2048` | Max spans queued before dropping |
| `use_tls` | `0` | Use TLS for exporter connection |
| `tls_ca_cert` | (empty) | Path to CA certificate bundle |
## Span Reference
All spans instrumented in rippled, grouped by subsystem:
### RPC Spans (Phase 2)
| Span Name | Source File | Attributes | Description |
| -------------------- | --------------------- | ------------------------------------------------------- | -------------------------------------------------- |
| `rpc.request` | ServerHandler.cpp:271 | — | Top-level HTTP RPC request |
| `rpc.process` | ServerHandler.cpp:573 | — | RPC processing (child of rpc.request) |
| `rpc.ws_message` | ServerHandler.cpp:384 | — | WebSocket RPC message |
| `rpc.command.<name>` | RPCHandler.cpp:161 | `xrpl.rpc.command`, `xrpl.rpc.version`, `xrpl.rpc.role` | Per-command span (e.g., `rpc.command.server_info`) |
### Transaction Spans (Phase 3)
| Span Name | Source File | Attributes | Description |
| ------------ | ------------------- | ----------------------------------------------- | ------------------------------------- |
| `tx.process` | NetworkOPs.cpp:1227 | `xrpl.tx.hash`, `xrpl.tx.local`, `xrpl.tx.path` | Transaction submission and processing |
| `tx.receive` | PeerImp.cpp:1273 | `xrpl.peer.id` | Transaction received from peer relay |
### Consensus Spans (Phase 4)
| Span Name | Source File | Attributes | Description |
| --------------------------- | -------------------- | ----------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------ |
| `consensus.proposal.send` | RCLConsensus.cpp:177 | `xrpl.consensus.round` | Consensus proposal broadcast |
| `consensus.ledger_close` | RCLConsensus.cpp:282 | `xrpl.consensus.ledger.seq`, `xrpl.consensus.mode` | Ledger close event |
| `consensus.accept` | RCLConsensus.cpp:395 | `xrpl.consensus.proposers`, `xrpl.consensus.round_time_ms` | Ledger accepted by consensus |
| `consensus.validation.send` | RCLConsensus.cpp:753 | `xrpl.consensus.ledger.seq`, `xrpl.consensus.proposing` | Validation sent after accept |
| `consensus.accept.apply` | RCLConsensus.cpp:453 | `xrpl.consensus.close_time`, `close_time_correct`, `close_resolution_ms`, `state`, `proposing`, `round_time_ms`, `ledger.seq` | Ledger application with close time details |
#### Close Time Queries (Tempo TraceQL)
```
# Find rounds where validators disagreed on close time
{name="consensus.accept.apply"} | xrpl.consensus.close_time_correct = false
# Find consensus failures (moved_on)
{name="consensus.accept.apply"} | xrpl.consensus.state = "moved_on"
# Find slow ledger applications (>5s)
{name="consensus.accept.apply"} | duration > 5s
# Find specific ledger's consensus details
{name="consensus.accept.apply"} | xrpl.consensus.ledger.seq = 92345678
```
## Prometheus Metrics (Spanmetrics)
The OTel Collector's spanmetrics connector automatically derives RED (Rate, Errors, Duration) metrics from every span. No custom metrics code is needed in rippled.
### Generated Metric Names
| Prometheus Metric | Type | Description |
| -------------------------------------------------- | --------- | ---------------------------- |
| `traces_span_metrics_calls_total` | Counter | Total span invocations |
| `traces_span_metrics_duration_milliseconds_bucket` | Histogram | Latency distribution buckets |
| `traces_span_metrics_duration_milliseconds_count` | Histogram | Latency observation count |
| `traces_span_metrics_duration_milliseconds_sum` | Histogram | Cumulative latency |
### Metric Labels
Every metric carries these standard labels:
| Label | Source | Example |
| -------------- | ------------------ | ---------------------------------------- |
| `span_name` | Span name | `rpc.command.server_info` |
| `status_code` | Span status | `STATUS_CODE_UNSET`, `STATUS_CODE_ERROR` |
| `service_name` | Resource attribute | `rippled` |
| `span_kind` | Span kind | `SPAN_KIND_INTERNAL` |
Additionally, span attributes configured as dimensions in the collector become metric labels (dots → underscores):
| Span Attribute | Metric Label | Applies To |
| --------------------- | --------------------- | ------------------------------ |
| `xrpl.rpc.command` | `xrpl_rpc_command` | `rpc.command.*` spans |
| `xrpl.rpc.status` | `xrpl_rpc_status` | `rpc.command.*` spans |
| `xrpl.consensus.mode` | `xrpl_consensus_mode` | `consensus.ledger_close` spans |
| `xrpl.tx.local` | `xrpl_tx_local` | `tx.process` spans |
### Histogram Buckets
Configured in `otel-collector-config.yaml`:
```
1ms, 5ms, 10ms, 25ms, 50ms, 100ms, 250ms, 500ms, 1s, 5s
```
## Grafana Dashboards
Three dashboards are pre-provisioned in `docker/telemetry/grafana/dashboards/`:
### RPC Performance (`rippled-rpc-perf`)
| Panel | Type | PromQL | Labels Used |
| --------------------------- | ---------- | -------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------- |
| RPC Request Rate by Command | timeseries | `sum by (xrpl_rpc_command) (rate(traces_span_metrics_calls_total{span_name=~"rpc.command.*"}[5m]))` | `xrpl_rpc_command` |
| RPC Latency p95 by Command | timeseries | `histogram_quantile(0.95, sum by (le, xrpl_rpc_command) (rate(traces_span_metrics_duration_milliseconds_bucket{span_name=~"rpc.command.*"}[5m])))` | `xrpl_rpc_command` |
| RPC Error Rate | bargauge | Error spans / total spans × 100, grouped by `xrpl_rpc_command` | `xrpl_rpc_command`, `status_code` |
| RPC Latency Heatmap | heatmap | `sum(increase(traces_span_metrics_duration_milliseconds_bucket{span_name=~"rpc.command.*"}[5m])) by (le)` | `le` (bucket boundaries) |
### Transaction Overview (`rippled-transactions`)
| Panel | Type | PromQL | Labels Used |
| --------------------------------- | ---------- | -------------------------------------------------------------------------------------------- | --------------- |
| Transaction Processing Rate | timeseries | `rate(traces_span_metrics_calls_total{span_name="tx.process"}[5m])` and `tx.receive` | `span_name` |
| Transaction Processing Latency | timeseries | `histogram_quantile(0.95 / 0.50, ... {span_name="tx.process"})` | — |
| Transaction Path Distribution | piechart | `sum by (xrpl_tx_local) (rate(traces_span_metrics_calls_total{span_name="tx.process"}[5m]))` | `xrpl_tx_local` |
| Transaction Receive vs Suppressed | timeseries | `rate(traces_span_metrics_calls_total{span_name="tx.receive"}[5m])` | — |
### Consensus Health (`rippled-consensus`)
| Panel | Type | PromQL | Labels Used |
| ----------------------------- | ---------- | ---------------------------------------------------------------------------------- | ----------- |
| Consensus Round Duration | timeseries | `histogram_quantile(0.95 / 0.50, ... {span_name="consensus.accept"})` | — |
| Consensus Proposals Sent Rate | timeseries | `rate(traces_span_metrics_calls_total{span_name="consensus.proposal.send"}[5m])` | — |
| Ledger Close Duration | timeseries | `histogram_quantile(0.95, ... {span_name="consensus.ledger_close"})` | — |
| Validation Send Rate | stat | `rate(traces_span_metrics_calls_total{span_name="consensus.validation.send"}[5m])` | — |
| Ledger Apply Duration | timeseries | `histogram_quantile(0.95 / 0.50, ... {span_name="consensus.accept.apply"})` | — |
| Close Time Agreement | timeseries | `rate(traces_span_metrics_calls_total{span_name="consensus.accept.apply"}[5m])` | — |
### Span → Metric → Dashboard Summary
| Span Name | Prometheus Metric Filter | Grafana Dashboard |
| --------------------------- | ----------------------------------------- | --------------------------------------------- |
| `rpc.request` | `{span_name="rpc.request"}` | — (available but not paneled) |
| `rpc.process` | `{span_name="rpc.process"}` | — (available but not paneled) |
| `rpc.command.*` | `{span_name=~"rpc.command.*"}` | RPC Performance (all 4 panels) |
| `tx.process` | `{span_name="tx.process"}` | Transaction Overview (3 panels) |
| `tx.receive` | `{span_name="tx.receive"}` | Transaction Overview (2 panels) |
| `consensus.accept` | `{span_name="consensus.accept"}` | Consensus Health (Round Duration) |
| `consensus.proposal.send` | `{span_name="consensus.proposal.send"}` | Consensus Health (Proposals Rate) |
| `consensus.ledger_close` | `{span_name="consensus.ledger_close"}` | Consensus Health (Close Duration) |
| `consensus.validation.send` | `{span_name="consensus.validation.send"}` | Consensus Health (Validation Rate) |
| `consensus.accept.apply` | `{span_name="consensus.accept.apply"}` | Consensus Health (Apply Duration, Close Time) |
## Troubleshooting
### No traces appearing in Jaeger
1. Check rippled logs for `Telemetry starting` message
2. Verify `enabled=1` in the `[telemetry]` config section
3. Test collector connectivity: `curl -v http://localhost:4318/v1/traces`
4. Check collector logs: `docker compose logs otel-collector`
### High memory usage
- Reduce `sampling_ratio` (e.g., `0.1` for 10% sampling)
- Reduce `max_queue_size` and `batch_size`
- Disable high-volume trace categories: `trace_peer=0`
### Collector connection failures
- Verify endpoint URL matches collector address
- Check firewall rules for ports 4317/4318
- If using TLS, verify certificate path with `tls_ca_cert`
## Performance Tuning
| Scenario | Recommendation |
| ------------------------ | ------------------------------------------------- |
| Production mainnet | `sampling_ratio=0.01`, `trace_peer=0` |
| Testnet/devnet | `sampling_ratio=1.0` (full tracing) |
| Debugging specific issue | `sampling_ratio=1.0` temporarily |
| High-throughput node | Increase `batch_size=1024`, `max_queue_size=4096` |
## Disabling Telemetry
Set `enabled=0` in config (runtime disable) or build without the flag:
```bash
cmake --preset default -Dtelemetry=OFF
```
When telemetry is compiled out, all trace macros expand to no-ops with zero overhead.

View File

@@ -311,7 +311,7 @@ template <class T>
bool
set(T& target, T const& defaultValue, std::string const& name, Section const& section)
{
bool const found_and_valid = set<T>(target, name, section);
bool found_and_valid = set<T>(target, name, section);
if (!found_and_valid)
target = defaultValue;
return found_and_valid;

View File

@@ -34,7 +34,7 @@ public:
{
// Insert ourselves at the front of the lock-free linked list
CountedObjects& instance = CountedObjects::getInstance();
Counter* head = nullptr;
Counter* head;
do
{

View File

@@ -93,7 +93,7 @@ class DecayWindow
public:
using time_point = typename Clock::time_point;
explicit DecayWindow(time_point now) : when_(now)
explicit DecayWindow(time_point now) : value_(0), when_(now)
{
}
@@ -125,7 +125,7 @@ private:
when_ = now;
}
double value_{0};
double value_;
time_point when_;
};

View File

@@ -84,8 +84,7 @@ public:
template <class TT>
requires std::convertible_to<TT*, T*>
SharedIntrusive(
SharedIntrusive<TT>&& rhs); // NOLINT(cppcoreguidelines-rvalue-reference-param-not-moved)
SharedIntrusive(SharedIntrusive<TT>&& rhs);
SharedIntrusive&
operator=(SharedIntrusive const& rhs);
@@ -107,8 +106,7 @@ public:
template <class TT>
requires std::convertible_to<TT*, T*>
SharedIntrusive&
operator=(
SharedIntrusive<TT>&& rhs); // NOLINT(cppcoreguidelines-rvalue-reference-param-not-moved)
operator=(SharedIntrusive<TT>&& rhs);
/** Adopt the raw pointer. The strong reference may or may not be
incremented, depending on the TAdoptTag
@@ -316,8 +314,7 @@ public:
template <class TT>
requires std::convertible_to<TT*, T*>
SharedWeakUnion(
SharedIntrusive<TT>&& rhs); // NOLINT(cppcoreguidelines-rvalue-reference-param-not-moved)
SharedWeakUnion(SharedIntrusive<TT>&& rhs);
SharedWeakUnion&
operator=(SharedWeakUnion const& rhs);
@@ -330,8 +327,7 @@ public:
template <class TT>
requires std::convertible_to<TT*, T*>
SharedWeakUnion&
operator=(
SharedIntrusive<TT>&& rhs); // NOLINT(cppcoreguidelines-rvalue-reference-param-not-moved)
operator=(SharedIntrusive<TT>&& rhs);
~SharedWeakUnion();

View File

@@ -68,7 +68,9 @@ SharedIntrusive<T>::operator=(SharedIntrusive const& rhs)
template <class T>
template <class TT>
requires std::convertible_to<TT*, T*>
// clang-format off
requires std::convertible_to<TT*, T*>
// clang-format on
SharedIntrusive<T>&
SharedIntrusive<T>::operator=(SharedIntrusive<TT> const& rhs)
{
@@ -99,7 +101,9 @@ SharedIntrusive<T>::operator=(SharedIntrusive&& rhs)
template <class T>
template <class TT>
requires std::convertible_to<TT*, T*>
// clang-format off
requires std::convertible_to<TT*, T*>
// clang-format on
SharedIntrusive<T>&
SharedIntrusive<T>::operator=(SharedIntrusive<TT>&& rhs)
{
@@ -303,7 +307,9 @@ WeakIntrusive<T>::WeakIntrusive(SharedIntrusive<T> const& rhs) : ptr_{rhs.unsafe
template <class T>
template <class TT>
requires std::convertible_to<TT*, T*>
// clang-format off
requires std::convertible_to<TT*, T*>
// clang-format on
WeakIntrusive<T>&
WeakIntrusive<T>::operator=(SharedIntrusive<TT> const& rhs)
{
@@ -448,7 +454,9 @@ SharedWeakUnion<T>::operator=(SharedWeakUnion const& rhs)
template <class T>
template <class TT>
requires std::convertible_to<TT*, T*>
// clang-format off
requires std::convertible_to<TT*, T*>
// clang-format on
SharedWeakUnion<T>&
SharedWeakUnion<T>::operator=(SharedIntrusive<TT> const& rhs)
{
@@ -462,7 +470,9 @@ SharedWeakUnion<T>::operator=(SharedIntrusive<TT> const& rhs)
template <class T>
template <class TT>
requires std::convertible_to<TT*, T*>
// clang-format off
requires std::convertible_to<TT*, T*>
// clang-format on
SharedWeakUnion<T>&
SharedWeakUnion<T>::operator=(SharedIntrusive<TT>&& rhs)
{

View File

@@ -448,7 +448,7 @@ inline void
partialDestructorFinished(T** o)
{
T& self = **o;
IntrusiveRefCounts::RefCountPair const p =
IntrusiveRefCounts::RefCountPair p =
self.refCounts.fetch_or(IntrusiveRefCounts::partialDestroyFinishedMask);
XRPL_ASSERT(
(!p.partialDestroyFinishedBit && p.partialDestroyStartedBit && !p.strong),

View File

@@ -1,73 +0,0 @@
#pragma once
#include <xrpl/beast/utility/Journal.h>
#include <chrono>
#include <cstdint>
#include <string_view>
namespace xrpl {
// cSpell:ignore ptmalloc
// -----------------------------------------------------------------------------
// Allocator interaction note:
// - This facility invokes glibc's malloc_trim(0) on Linux/glibc to request that
// ptmalloc return free heap pages to the OS.
// - If an alternative allocator (e.g. jemalloc or tcmalloc) is linked or
// preloaded (LD_PRELOAD), calling glibc's malloc_trim typically has no effect
// on the *active* heap. The call is harmless but may not reclaim memory
// because those allocators manage their own arenas.
// - Only glibc sbrk/arena space is eligible for trimming; large mmap-backed
// allocations are usually returned to the OS on free regardless of trimming.
// - Call at known reclamation points (e.g., after cache sweeps / online delete)
// and consider rate limiting to avoid churn.
// -----------------------------------------------------------------------------
struct MallocTrimReport
{
bool supported{false};
int trimResult{-1};
std::int64_t rssBeforeKB{-1};
std::int64_t rssAfterKB{-1};
std::chrono::microseconds durationUs{-1};
std::int64_t minfltDelta{-1};
std::int64_t majfltDelta{-1};
[[nodiscard]] std::int64_t
deltaKB() const noexcept
{
if (rssBeforeKB < 0 || rssAfterKB < 0)
return 0;
return rssAfterKB - rssBeforeKB;
}
};
/**
* @brief Attempt to return freed memory to the operating system.
*
* On Linux with glibc malloc, this issues ::malloc_trim(0), which may release
* free space from ptmalloc arenas back to the kernel. On other platforms, or if
* a different allocator is in use, this function is a no-op and the report will
* indicate that trimming is unsupported or had no effect.
*
* @param tag Identifier for logging/debugging purposes.
* @param journal Journal for diagnostic logging.
* @return Report containing before/after metrics and the trim result.
*
* @note If an alternative allocator (jemalloc/tcmalloc) is linked or preloaded,
* calling glibc's malloc_trim may have no effect on the active heap. The
* call is harmless but typically does not reclaim memory under those
* allocators.
*
* @note Only memory served from glibc's sbrk/arena heaps is eligible for trim.
* Large allocations satisfied via mmap are usually returned on free
* independently of trimming.
*
* @note Intended for use after operations that free significant memory (e.g.,
* cache sweeps, ledger cleanup, online delete). Consider rate limiting.
*/
MallocTrimReport
mallocTrim(std::string_view tag, beast::Journal journal);
} // namespace xrpl

View File

@@ -73,12 +73,12 @@ struct MantissaRange
enum mantissa_scale { small, large };
explicit constexpr MantissaRange(mantissa_scale scale_)
: min(getMin(scale_)), log(logTen(min).value_or(-1)), scale(scale_)
: min(getMin(scale_)), max(min * 10 - 1), log(logTen(min).value_or(-1)), scale(scale_)
{
}
rep min;
rep max{min * 10 - 1};
rep max;
int log;
mantissa_scale scale;

View File

@@ -91,10 +91,10 @@ class SlabAllocator
std::uint8_t*
allocate() noexcept
{
std::uint8_t* ret = nullptr; // NOLINT(misc-const-correctness)
std::uint8_t* ret;
{
std::lock_guard const l(m_);
std::lock_guard l(m_);
ret = l_;
@@ -123,7 +123,7 @@ class SlabAllocator
{
XRPL_ASSERT(own(ptr), "xrpl::SlabAllocator::SlabBlock::deallocate : own input");
std::lock_guard const l(m_);
std::lock_guard l(m_);
// Use memcpy to avoid unaligned UB
// (will optimize to equivalent code)
@@ -210,13 +210,16 @@ public:
// No slab can satisfy our request, so we attempt to allocate a new
// one here:
std::size_t const size = slabSize_;
std::size_t size = slabSize_;
// We want to allocate the memory at a 2 MiB boundary, to make it
// possible to use hugepage mappings on Linux:
auto buf = boost::alignment::aligned_alloc(megabytes(std::size_t(2)), size);
// clang-format off
if (!buf) [[unlikely]]
return nullptr;
// clang-format on
#if BOOST_OS_LINUX
// When allocating large blocks, attempt to leverage Linux's

View File

@@ -66,12 +66,12 @@ strUnHex(std::size_t strSize, Iterator begin, Iterator end)
while (iter != end)
{
int const cHigh = digitLookupTable[*iter++];
int cHigh = digitLookupTable[*iter++];
if (cHigh < 0)
return {};
int const cLow = digitLookupTable[*iter++];
int cLow = digitLookupTable[*iter++];
if (cLow < 0)
return {};

View File

@@ -182,7 +182,8 @@ private:
: hook(collector->make_hook(handler))
, size(collector->make_gauge(prefix, "size"))
, hit_rate(collector->make_gauge(prefix, "hit_rate"))
, hits(0)
, misses(0)
{
}
@@ -190,8 +191,8 @@ private:
beast::insight::Gauge size;
beast::insight::Gauge hit_rate;
std::size_t hits{0};
std::size_t misses{0};
std::size_t hits;
std::size_t misses;
};
class KeyOnlyEntry
@@ -293,10 +294,10 @@ private:
clock_type::duration const m_target_age;
// Number of items cached
int m_cache_count{0};
int m_cache_count;
cache_type m_cache; // Hold strong reference to recent objects
std::uint64_t m_hits{0};
std::uint64_t m_misses{0};
std::uint64_t m_hits;
std::uint64_t m_misses;
};
} // namespace xrpl

View File

@@ -36,7 +36,9 @@ inline TaggedCache<
, m_name(name)
, m_target_size(size)
, m_target_age(expiration)
, m_cache_count(0)
, m_hits(0)
, m_misses(0)
{
}

View File

@@ -212,7 +212,7 @@ private:
while (in != sv.end())
{
std::uint32_t accum = {};
for (std::uint32_t const shift : {4u, 0u, 12u, 8u, 20u, 16u, 28u, 24u})
for (std::uint32_t shift : {4u, 0u, 12u, 8u, 20u, 16u, 28u, 24u})
{
if (auto const result = hexCharToUInt(*in++, shift, accum);
result != ParseResult::okay)
@@ -335,13 +335,11 @@ public:
operator=(std::uint64_t uHost)
{
*this = beast::zero;
// NOLINTBEGIN(cppcoreguidelines-pro-type-member-init)
union
{
unsigned u[2];
std::uint64_t ul;
};
// NOLINTEND(cppcoreguidelines-pro-type-member-init)
// Put in least significant bits.
ul = boost::endian::native_to_big(uHost);
data_[WIDTH - 2] = u[0];
@@ -446,7 +444,7 @@ public:
for (int i = WIDTH; i--;)
{
std::uint64_t const n = carry + boost::endian::big_to_native(data_[i]) +
std::uint64_t n = carry + boost::endian::big_to_native(data_[i]) +
boost::endian::big_to_native(b.data_[i]);
data_[i] = boost::endian::native_to_big(static_cast<std::uint32_t>(n));
@@ -623,7 +621,7 @@ template <>
inline std::size_t
extract(uint256 const& key)
{
std::size_t result = 0;
std::size_t result;
// Use memcpy to avoid unaligned UB
// (will optimize to equivalent code)
std::memcpy(&result, key.data(), sizeof(std::size_t));

View File

@@ -54,7 +54,7 @@ Throw(Args&&... args)
E e(std::forward<Args>(args)...);
LogThrow(std::string("Throwing exception of type " + beast::type_name<E>() + ": ") + e.what());
throw std::move(e);
throw e;
}
/** Called when faulty logic causes a broken invariant. */

View File

@@ -32,7 +32,7 @@ make_seed_pair() noexcept
// state_t& operator=(state_t const&) = delete;
};
static state_t state;
std::lock_guard const lock(state.mutex);
std::lock_guard lock(state.mutex);
return {state.dist(state.gen), state.dist(state.gen)};
}

View File

@@ -14,13 +14,11 @@ namespace xrpl {
#ifndef __INTELLISENSE__
static_assert(
// NOLINTNEXTLINE(misc-redundant-expression)
std::is_integral<beast::xor_shift_engine::result_type>::value &&
std::is_unsigned<beast::xor_shift_engine::result_type>::value,
"The Ripple default PRNG engine must return an unsigned integral type.");
static_assert(
// NOLINTNEXTLINE(misc-redundant-expression)
std::numeric_limits<beast::xor_shift_engine::result_type>::max() >=
std::numeric_limits<std::uint64_t>::max(),
"The Ripple default PRNG engine return must be at least 64 bits wide.");
@@ -58,9 +56,9 @@ default_prng()
// The thread-specific PRNGs:
thread_local beast::xor_shift_engine engine = [] {
std::uint64_t seed = 0;
std::uint64_t seed;
{
std::lock_guard const lk(m);
std::lock_guard lk(m);
std::uniform_int_distribution<std::uint64_t> distribution{1};
seed = distribution(seeder);
}

View File

@@ -23,15 +23,15 @@ private:
std::recursive_mutex m_mutex;
std::condition_variable_any m_cond;
std::size_t m_count{1};
std::size_t m_count;
duration const m_period;
boost::asio::io_context& m_ios;
boost::asio::basic_waitable_timer<std::chrono::steady_clock> m_timer;
bool m_cancel{false};
bool m_cancel;
public:
io_latency_probe(duration const& period, boost::asio::io_context& ios)
: m_period(period), m_ios(ios), m_timer(m_ios)
: m_count(1), m_period(period), m_ios(ios), m_timer(m_ios), m_cancel(false)
{
}
@@ -83,7 +83,7 @@ public:
void
sample_one(Handler&& handler)
{
std::lock_guard const lock(m_mutex);
std::lock_guard lock(m_mutex);
if (m_cancel)
throw std::logic_error("io_latency_probe is canceled");
boost::asio::post(
@@ -98,7 +98,7 @@ public:
void
sample(Handler&& handler)
{
std::lock_guard const lock(m_mutex);
std::lock_guard lock(m_mutex);
if (m_cancel)
throw std::logic_error("io_latency_probe is canceled");
boost::asio::post(
@@ -122,14 +122,14 @@ private:
void
addref()
{
std::lock_guard const lock(m_mutex);
std::lock_guard lock(m_mutex);
++m_count;
}
void
release()
{
std::lock_guard const lock(m_mutex);
std::lock_guard lock(m_mutex);
if (--m_count == 0)
m_cond.notify_all();
}
@@ -192,7 +192,7 @@ private:
m_handler(elapsed);
{
std::lock_guard const lock(m_probe->m_mutex);
std::lock_guard lock(m_probe->m_mutex);
if (m_probe->m_cancel)
return;
}

View File

@@ -16,4 +16,4 @@ template <
class Allocator = std::allocator<std::pair<Key const, T>>>
using aged_map = detail::aged_ordered_container<false, true, Key, T, Clock, Compare, Allocator>;
} // namespace beast
}

View File

@@ -16,4 +16,4 @@ template <
class Allocator = std::allocator<std::pair<Key const, T>>>
using aged_multimap = detail::aged_ordered_container<true, true, Key, T, Clock, Compare, Allocator>;
} // namespace beast
}

View File

@@ -15,4 +15,4 @@ template <
class Allocator = std::allocator<Key>>
using aged_multiset =
detail::aged_ordered_container<true, false, Key, void, Clock, Compare, Allocator>;
} // namespace beast
}

View File

@@ -15,4 +15,4 @@ template <
class Allocator = std::allocator<Key>>
using aged_set = detail::aged_ordered_container<false, false, Key, void, Clock, Compare, Allocator>;
} // namespace beast
}

View File

@@ -17,4 +17,4 @@ template <
class Allocator = std::allocator<std::pair<Key const, T>>>
using aged_unordered_map =
detail::aged_unordered_container<false, true, Key, T, Clock, Hash, KeyEqual, Allocator>;
} // namespace beast
}

View File

@@ -17,4 +17,4 @@ template <
class Allocator = std::allocator<std::pair<Key const, T>>>
using aged_unordered_multimap =
detail::aged_unordered_container<true, true, Key, T, Clock, Hash, KeyEqual, Allocator>;
} // namespace beast
}

View File

@@ -17,4 +17,4 @@ template <
using aged_unordered_multiset =
detail::aged_unordered_container<true, false, Key, void, Clock, Hash, KeyEqual, Allocator>;
} // namespace beast
}

View File

@@ -16,4 +16,4 @@ template <
class Allocator = std::allocator<Key>>
using aged_unordered_set =
detail::aged_unordered_container<false, false, Key, void, Clock, Hash, KeyEqual, Allocator>;
} // namespace beast
}

View File

@@ -262,9 +262,7 @@ private:
{
}
config_t(
config_t&& other, // NOLINT(cppcoreguidelines-rvalue-reference-param-not-moved)
Allocator const& alloc)
config_t(config_t&& other, Allocator const& alloc)
: KeyValueCompare(std::move(other.key_compare()))
, beast::detail::empty_base_optimization<ElementAllocator>(alloc)
, clock(other.clock)
@@ -554,10 +552,7 @@ public:
aged_ordered_container(aged_ordered_container&& other);
aged_ordered_container(
// NOLINTNEXTLINE(cppcoreguidelines-rvalue-reference-param-not-moved)
aged_ordered_container&& other,
Allocator const& alloc);
aged_ordered_container(aged_ordered_container&& other, Allocator const& alloc);
aged_ordered_container(std::initializer_list<value_type> init, clock_type& clock);
@@ -1295,7 +1290,7 @@ aged_ordered_container<IsMulti, IsMap, Key, T, Clock, Compare, Allocator>::aged_
template <bool IsMulti, bool IsMap, class Key, class T, class Clock, class Compare, class Allocator>
aged_ordered_container<IsMulti, IsMap, Key, T, Clock, Compare, Allocator>::aged_ordered_container(
aged_ordered_container&& other, // NOLINT(cppcoreguidelines-rvalue-reference-param-not-moved)
aged_ordered_container&& other,
Allocator const& alloc)
: m_config(std::move(other.m_config), alloc)
#if BOOST_VERSION >= 108000

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@@ -318,9 +318,7 @@ private:
{
}
config_t(
config_t&& other, // NOLINT(cppcoreguidelines-rvalue-reference-param-not-moved)
Allocator const& alloc)
config_t(config_t&& other, Allocator const& alloc)
: ValueHash(std::move(other.hash_function()))
, KeyValueEqual(std::move(other.key_eq()))
, beast::detail::empty_base_optimization<ElementAllocator>(alloc)
@@ -776,10 +774,7 @@ public:
aged_unordered_container(aged_unordered_container&& other);
aged_unordered_container(
// NOLINTNEXTLINE(cppcoreguidelines-rvalue-reference-param-not-moved)
aged_unordered_container&& other,
Allocator const& alloc);
aged_unordered_container(aged_unordered_container&& other, Allocator const& alloc);
aged_unordered_container(std::initializer_list<value_type> init, clock_type& clock);
@@ -1843,10 +1838,7 @@ template <
class KeyEqual,
class Allocator>
aged_unordered_container<IsMulti, IsMap, Key, T, Clock, Hash, KeyEqual, Allocator>::
aged_unordered_container(
// NOLINTNEXTLINE(cppcoreguidelines-rvalue-reference-param-not-moved)
aged_unordered_container&& other,
Allocator const& alloc)
aged_unordered_container(aged_unordered_container&& other, Allocator const& alloc)
: m_config(std::move(other.m_config), alloc)
, m_buck(alloc)
, m_cont(m_buck, std::cref(m_config.value_hash()), std::cref(m_config.key_value_equal()))

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@@ -449,7 +449,7 @@ public:
iterator
erase(iterator pos) noexcept
{
Node const* node = &*pos;
Node* node = &*pos;
++pos;
node->m_next->m_prev = node->m_prev;
node->m_prev->m_next = node->m_next;

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@@ -187,7 +187,7 @@ public:
bool
push_front(Node* node)
{
bool first = false;
bool first;
Node* old_head = m_head.load(std::memory_order_relaxed);
do
{
@@ -211,7 +211,7 @@ public:
pop_front()
{
Node* node = m_head.load();
Node* new_head = nullptr;
Node* new_head;
do
{
if (node == &m_end)

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@@ -23,7 +23,7 @@ private:
// A 64-byte buffer should to be big enough for us
static constexpr std::size_t INTERNAL_BUFFER_SIZE = 64;
alignas(64) std::array<std::uint8_t, INTERNAL_BUFFER_SIZE> buffer_{};
alignas(64) std::array<std::uint8_t, INTERNAL_BUFFER_SIZE> buffer_;
std::span<std::uint8_t> readBuffer_;
std::span<std::uint8_t> writeBuffer_;

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@@ -114,7 +114,7 @@ enable_yield_to::spawn(F0&& f, FN&&... fn)
boost::context::fixedsize_stack(2 * 1024 * 1024),
[&](yield_context yield) {
f(yield);
std::lock_guard const lock{m_};
std::lock_guard lock{m_};
if (--running_ == 0)
cv_.notify_all();
},

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@@ -35,10 +35,10 @@ private:
class tests_t : public detail::const_container<std::vector<test>>
{
private:
std::size_t failed_{0};
std::size_t failed_;
public:
tests_t()
tests_t() : failed_(0)
{
}
@@ -167,12 +167,12 @@ public:
class results : public detail::const_container<std::vector<suite_results>>
{
private:
std::size_t m_cases{0};
std::size_t total_{0};
std::size_t failed_{0};
std::size_t m_cases;
std::size_t total_;
std::size_t failed_;
public:
results()
results() : m_cases(0), total_(0), failed_(0)
{
}

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@@ -228,7 +228,7 @@ template <class>
void
runner::testcase(std::string const& name)
{
std::lock_guard const lock(mutex_);
std::lock_guard lock(mutex_);
// Name may not be empty
BOOST_ASSERT(default_ || !name.empty());
// Forgot to call pass or fail
@@ -244,7 +244,7 @@ template <class>
void
runner::pass()
{
std::lock_guard const lock(mutex_);
std::lock_guard lock(mutex_);
if (default_)
testcase("");
on_pass();
@@ -255,7 +255,7 @@ template <class>
void
runner::fail(std::string const& reason)
{
std::lock_guard const lock(mutex_);
std::lock_guard lock(mutex_);
if (default_)
testcase("");
on_fail(reason);
@@ -267,7 +267,7 @@ template <class>
void
runner::log(std::string const& s)
{
std::lock_guard const lock(mutex_);
std::lock_guard lock(mutex_);
if (default_)
testcase("");
on_log(s);

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@@ -300,7 +300,7 @@ private:
static suite**
p_this_suite()
{
static suite* pts = nullptr; // NOLINT(misc-const-correctness)
static suite* pts = nullptr;
return &pts;
}

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@@ -311,7 +311,7 @@ private:
std::string const m_name;
std::recursive_mutex lock_;
Item item_;
Source* parent_{nullptr};
Source* parent_;
List<Item> children_;
public:

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@@ -28,7 +28,7 @@ struct Zero
namespace {
static constexpr Zero zero{};
} // namespace
}
/** Default implementation of signum calls the method on the class. */
template <typename T>

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@@ -37,7 +37,7 @@ public:
}
private:
result_type s_[2]{};
result_type s_[2];
static result_type
murmurhash3(result_type x);

View File

@@ -56,7 +56,7 @@ private:
// a lock. This removes a small timing window that occurs if the
// waiting thread is handling a spurious wakeup when closureCount_
// drops to zero.
std::lock_guard const lock{mutex_};
std::lock_guard lock{mutex_};
// Update closureCount_. Notify if stopping and closureCount_ == 0.
if ((--closureCount_ == 0) && waitForClosures_)
@@ -92,9 +92,7 @@ private:
++counter_;
}
Substitute(
ClosureCounter& counter,
Closure&& closure) // NOLINT(cppcoreguidelines-rvalue-reference-param-not-moved)
Substitute(ClosureCounter& counter, Closure&& closure)
: counter_(counter), closure_(std::forward<Closure>(closure))
{
++counter_;
@@ -170,7 +168,7 @@ public:
{
std::optional<Substitute<Closure>> ret;
std::lock_guard const lock{mutex_};
std::lock_guard lock{mutex_};
if (!waitForClosures_)
ret.emplace(*this, std::forward<Closure>(closure));
@@ -193,7 +191,7 @@ public:
bool
joined() const
{
std::lock_guard const lock{mutex_};
std::lock_guard lock{mutex_};
return waitForClosures_;
}
};

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@@ -7,6 +7,7 @@ JobQueue::Coro::Coro(Coro_create_t, JobQueue& jq, JobType type, std::string cons
: jq_(jq)
, type_(type)
, name_(name)
, running_(false)
, coro_(
// Stack size of 1MB wasn't sufficient for deep calls. ASAN tests flagged the issue. Hence
// increasing the size to 1.5MB.

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@@ -16,7 +16,7 @@ namespace xrpl {
namespace perf {
class PerfLog;
} // namespace perf
}
class Logs;
struct Coro_create_t
@@ -45,7 +45,7 @@ public:
JobQueue& jq_;
JobType type_;
std::string name_;
bool running_{false};
bool running_;
std::mutex mutex_;
std::mutex mutex_run_;
std::condition_variable cv_;
@@ -224,7 +224,7 @@ private:
beast::Journal m_journal;
mutable std::mutex m_mutex;
std::uint64_t m_lastJob{0};
std::uint64_t m_lastJob;
std::set<Job> m_jobSet;
JobCounter jobCounter_;
std::atomic_bool stopping_{false};
@@ -233,7 +233,7 @@ private:
JobTypeData m_invalidJobData;
// The number of jobs currently in processTask()
int m_processCount{0};
int m_processCount;
// The number of suspended coroutines
int nSuspend_ = 0;

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@@ -19,13 +19,13 @@ public:
JobTypeInfo const& info;
/* The number of jobs waiting */
int waiting{0};
int waiting;
/* The number presently running */
int running{0};
int running;
/* And the number we deferred executing because of job limits */
int deferred{0};
int deferred;
/* Notification callbacks */
beast::insight::Event dequeue;
@@ -35,8 +35,12 @@ public:
JobTypeInfo const& info_,
beast::insight::Collector::ptr const& collector,
Logs& logs) noexcept
: m_load(logs.journal("LoadMonitor")), m_collector(collector), info(info_)
: m_load(logs.journal("LoadMonitor"))
, m_collector(collector)
, info(info_)
, waiting(0)
, running(0)
, deferred(0)
{
m_load.setTargetLatency(info.getAverageLatency(), info.getPeakLatency());

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@@ -24,7 +24,7 @@ private:
std::chrono::milliseconds{0})
{
using namespace std::chrono_literals;
int const maxLimit = std::numeric_limits<int>::max();
int maxLimit = std::numeric_limits<int>::max();
auto add = [this](
JobType jt,

View File

@@ -36,10 +36,10 @@ public:
{
Stats();
std::uint64_t count{0};
std::uint64_t count;
std::chrono::milliseconds latencyAvg;
std::chrono::milliseconds latencyPeak;
bool isOverloaded{false};
bool isOverloaded;
};
Stats
@@ -54,8 +54,8 @@ private:
std::mutex mutex_;
std::uint64_t mCounts{0};
int mLatencyEvents{0};
std::uint64_t mCounts;
int mLatencyEvents;
std::chrono::milliseconds mLatencyMSAvg;
std::chrono::milliseconds mLatencyMSPeak;
std::chrono::milliseconds mTargetLatencyAvg;

View File

@@ -67,7 +67,7 @@ public:
bool
contains(PublicKey const& nodeId)
{
std::lock_guard const lock(this->mutex_);
std::lock_guard lock(this->mutex_);
return table_.find({nodeId}) != table_.end();
}
@@ -92,7 +92,7 @@ public:
private:
beast::Journal mutable journal_;
std::mutex mutable mutex_;
DatabaseCon* connection_{};
DatabaseCon* connection_;
std::unordered_set<PeerReservation, beast::uhash<>, KeyEqual> table_;
};

View File

@@ -14,7 +14,7 @@
namespace beast {
class Journal;
} // namespace beast
}
namespace xrpl {
class Application;

View File

@@ -11,13 +11,16 @@ namespace xrpl {
// Forward declarations
namespace NodeStore {
class Database;
} // namespace NodeStore
}
namespace Resource {
class Manager;
} // namespace Resource
}
namespace perf {
class PerfLog;
} // namespace perf
}
namespace telemetry {
class Telemetry;
}
// This is temporary until we migrate all code to use ServiceRegistry.
class Application;
@@ -218,6 +221,9 @@ public:
virtual perf::PerfLog&
getPerfLog() = 0;
virtual telemetry::Telemetry&
getTelemetry() = 0;
// Configuration and state
virtual bool
isStopping() const = 0;

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@@ -5,7 +5,7 @@
namespace xrpl {
enum class StartUpType { Fresh, Normal, Load, LoadFile, Replay, Network };
enum class StartUpType { FRESH, NORMAL, LOAD, LOAD_FILE, REPLAY, NETWORK };
inline std::ostream&
operator<<(std::ostream& os, StartUpType const& type)

View File

@@ -13,7 +13,7 @@ namespace xrpl {
namespace perf {
class PerfLog;
} // namespace perf
}
/**
* `Workers` is effectively a thread pool. The constructor takes a "callback"
@@ -183,8 +183,8 @@ private:
std::thread thread_;
std::mutex mutex_;
std::condition_variable wakeup_;
int wakeCount_{0}; // how many times to un-pause
bool shouldExit_{false};
int wakeCount_; // how many times to un-pause
bool shouldExit_;
};
private:
@@ -197,9 +197,9 @@ private:
std::string m_threadNames; // The name to give each thread
std::condition_variable m_cv; // signaled when all threads paused
std::mutex m_mut;
bool m_allPaused{true};
bool m_allPaused;
semaphore m_semaphore; // each pending task is 1 resource
int m_numberOfThreads{0}; // how many we want active now
int m_numberOfThreads; // how many we want active now
std::atomic<int> m_activeCount; // to know when all are paused
std::atomic<int> m_pauseCount; // how many threads need to pause now
std::atomic<int> m_runningTaskCount; // how many calls to processTask() active

View File

@@ -55,7 +55,7 @@ public:
void
notify()
{
std::lock_guard const lock{m_mutex};
std::lock_guard lock{m_mutex};
++m_count;
m_cond.notify_one();
}

View File

@@ -103,9 +103,9 @@ private:
public:
explicit ErrorInfo() = default;
Token token_{};
Token token_;
std::string message_;
Location extra_{};
Location extra_;
};
using Errors = std::deque<ErrorInfo>;
@@ -173,11 +173,11 @@ private:
Nodes nodes_;
Errors errors_;
std::string document_;
Location begin_{};
Location end_{};
Location current_{};
Location lastValueEnd_{};
Value* lastValue_{};
Location begin_;
Location end_;
Location current_;
Location lastValueEnd_;
Value* lastValue_;
};
template <class BufferSequence>

View File

@@ -641,7 +641,7 @@ public:
SelfType
operator++(int)
{
SelfType const temp(*this);
SelfType temp(*this);
++*this;
return temp;
}
@@ -649,7 +649,7 @@ public:
SelfType
operator--(int)
{
SelfType const temp(*this);
SelfType temp(*this);
--*this;
return temp;
}

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