# 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 Establish Phase (4a) :p4f, after p4b, 3d Validation Tests :p4c, after p4f, 4d Buffer & Review :p4e, after p4c, 4d section Phase 5 Documentation & Deploy :p5, after p4, 1w section Phase 6 StatsD Metrics Bridge :p6, after p5, 1w section Phase 7 Native OTel Metrics :p7, after p6, 2w section Phase 8 Log-Trace Correlation :p8, after p7, 1w section Phase 9 (Future) Internal Metric Gap Fill :p9, after p8, 2.5w section Phase 10 (Future) Workload Validation :p10, after p9, 2w section Phase 11 (Future) Third-Party Collection :p11, after p10, 3w ``` --- ## 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 with deterministic cross-node correlation ### 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 | Deterministic transaction trace ID (`trace_id = txHash[0:16]`) | | 3.10 | Performance benchmarks | ### Deterministic Trace ID (Task 3.9) Transaction spans use **deterministic trace IDs** derived from the transaction hash: `trace_id = txHash[0:16]`. All nodes handling the same transaction independently produce spans under the same trace_id. Protobuf `span_id` propagation (Task 3.7) additionally provides parent-child relay ordering when available. See [02-design-decisions.md §2.5.0](./02-design-decisions.md) for the design rationale and [Phase3_taskList.md Task 3.9](./Phase3_taskList.md) for the full implementation spec. ### 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 - [ ] Deterministic trace_id: all nodes produce same trace_id for same transaction - [ ] Protobuf span_id propagation preserves parent-child ordering when available --- ## 6.5 Phase 4: Consensus Tracing (Weeks 7-8) **Objective**: Full observability into consensus rounds ### Tasks | Task | Description | Status | | ---- | ---------------------------------------------- | ------------------ | | 4.1 | Instrument `RCLConsensusAdaptor::startRound()` | ✅ Done (via 4a.2) | | 4.2 | Instrument phase transitions | ✅ Done | | 4.3 | Instrument proposal handling | ✅ Done | | 4.4 | Instrument validation handling | ✅ Done | | 4.5 | Add consensus-specific attributes | ✅ Done | | 4.6 | Correlate with transaction traces | ✅ Done | | 4.7 | Build verification and testing | ✅ Done | | 4.8 | Validation span enrichment (ext. dashboard) | ❌ Not done | **Note**: The original plan doc listed tasks 4.7-4.11 as "Validator list tracing", "Amendment voting tracing", "SHAMap sync tracing", "Multi-validator integration tests", and "Performance validation". These were descoped and replaced by the tasklist's 4.7 (build verification) and 4.8 (validation span enrichment). Validator, amendment, and SHAMap tracing are not implemented. ### Spans Produced | Span Name | Location | Attributes | | --------------------------- | ------------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `consensus.phase.open` | `Consensus.h` | _(none)_ | | `consensus.proposal.send` | `RCLConsensus.cpp` | `consensus_round` | | `consensus.ledger_close` | `RCLConsensus.cpp` | `ledger_seq`, `consensus_mode` | | `consensus.accept` | `RCLConsensus.cpp` | `proposers`, `round_time_ms`, `quorum` | | `consensus.accept.apply` | `RCLConsensus.cpp` | `close_time`, `close_time_correct`, `close_resolution_ms`, `consensus_state`, `proposing`, `round_time_ms`, `ledger_seq`, `parent_close_time`, `close_time_self`, `close_time_vote_bins`, `resolution_direction` | | `consensus.validation.send` | `RCLConsensus.cpp` | `ledger_seq`, `proposing` | ### Exit Criteria - [x] Complete consensus round traces - [x] Phase transitions visible (open, establish, close, accept) - [x] Proposals and validations traced — send and receive; relay deferred to Phase 4b - [x] Close time agreement tracked (per `avCT_CONSENSUS_PCT`) - [x] No impact on consensus timing - [ ] Multi-validator test network validated - [x] Transaction-consensus correlation (Task 4.6) — `tx.included` events in doAccept - [ ] Validation span enrichment (Task 4.8) — not implemented ### 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. - **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` and `RCLConsensus.cpp`. All spans use `SpanGuard` factory methods (`span()`, `hashSpan()`, `linkedSpan()`) with `TraceCategory::Consensus` gating. No macros used — all tracing via direct `SpanGuard` API calls. ### Tasks | Task | Description | Effort | Risk | Status | | ---- | ------------------------------------------------ | ------ | ------ | ------------------------ | | 4a.0 | Prerequisites: extend SpanGuard & Telemetry APIs | 1d | Medium | ✅ Done (no macros) | | 4a.1 | Adaptor `getTelemetry()` method | 0.5d | Low | ⏭️ Skipped (not needed) | | 4a.2 | Switchable round span with deterministic traceID | 2d | High | ✅ Done | | 4a.3 | Span members in `Consensus.h` | 0.5d | Medium | ✅ Done (with deviation) | | 4a.4 | Instrument `phaseEstablish()` | 1d | Medium | ✅ Done | | 4a.5 | Instrument `updateOurPositions()` | 1d | Medium | ✅ Done | | 4a.6 | Instrument `haveConsensus()` (thresholds) | 1d | Medium | ✅ Done | | 4a.7 | Instrument mode changes | 0.5d | Low | ✅ Done | | 4a.8 | Reparent existing spans under round | 0.5d | Low | ✅ Done | | 4a.9 | Build verification and testing | 1d | Low | ✅ Done | **Total Effort**: 9 days ### Spans Produced | Span Name | Location | Key Attributes (actually set) | | ---------------------------- | ------------------ | ----------------------------------------------------------------------------------------------------------------------------- | | `consensus.round` | `RCLConsensus.cpp` | `consensus_round_id`, `consensus_ledger_id`, `ledger_seq`, `consensus_mode`, `trace_strategy` | | `consensus.establish` | `Consensus.h` | `converge_percent`, `establish_count`, `proposers` | | `consensus.update_positions` | `Consensus.h` | `converge_percent`, `proposers`, `have_close_time_consensus`, `close_time_threshold`, `disputes_count`, `avalanche_threshold` | | `consensus.check` | `Consensus.h` | `agree_count`, `disagree_count`, `converge_percent`, `have_close_time_consensus`, `threshold_percent`, `consensus_result` | | `consensus.mode_change` | `RCLConsensus.cpp` | `mode_old`, `mode_new` | ### Exit Criteria - [x] Establish phase internals traced (establish, update_positions, check spans) - [x] Establish phase fully traced — `disputes_count`, `avalanche_threshold`, dispute `yays`/`nays` all implemented - [x] Cross-node correlation works via deterministic trace_id - [x] Strategy switchable via config (`deterministic` / `attribute`) - [x] Consecutive rounds linked via follows-from spans - [x] Build passes with telemetry ON and OFF - [x] 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**: Partially implemented. Send-side injection (proposals and validations) and receive-side extraction (`consensus.{proposal,validation}. receive` spans parented on the sender's context) are wired in Phase 4a. Remaining Phase 4b work: relay spans in `share(RCLCxPeerPos)` and multi-node validation of the propagation path. **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 | Status | | ---- | ----------------------------- | ------------------- | | 5.1 | Operator runbook | Complete | | 5.2 | Grafana dashboards | Complete | | 5.3 | Alert definitions | Deferred — post-MVP | | 5.4 | Collector deployment examples | Complete | | 5.5 | Developer documentation | Complete | | 5.6 | Training materials | Deferred — post-MVP | | 5.7 | Final integration testing | Complete | --- ## 6.7 Phase 6: StatsD Metrics Integration (Week 10) **Objective**: Bridge xrpld's existing `beast::insight` StatsD metrics into the OpenTelemetry collection pipeline, exposing 300+ pre-existing metrics alongside span-derived RED metrics in Prometheus/Grafana. ### Background xrpld has a mature metrics framework (`beast::insight`) that emits StatsD-format metrics over UDP. These metrics cover node health, peer networking, RPC performance, job queue, and overlay traffic — data that **does not** overlap with the span-based instrumentation from Phases 1-5. By adding a StatsD receiver to the OTel Collector, both metric sources converge in Prometheus. ### Metric Inventory | Category | Group | Type | Count | Key Metrics | | --------------- | ------------------ | ------------- | ---------- | ----------------------------------------------------------------------------------------------------------- | | Node State | `State_Accounting` | Gauge | 10 | `*_duration`, `*_transitions` per operating mode | | Ledger | `LedgerMaster` | Gauge | 2 | `Validated_Ledger_Age`, `Published_Ledger_Age` | | Ledger Fetch | — | Counter | 1 | `ledger_fetches` | | Ledger History | `ledger.history` | Counter | 1 | `mismatch` | | RPC | `rpc` | Counter+Event | 3 | `requests`, `time` (histogram), `size` (histogram) | | Job Queue | `jobq` | Gauge+Event | 1 + 2×N | `job_count`, per-job `{name}` and `{name}_q` (emitted with the `jobq_` group prefix, e.g. `jobq_job_count`) | | Peer Finder | `Peer_Finder` | Gauge | 2 | `Active_Inbound_Peers`, `Active_Outbound_Peers` | | Overlay | `Overlay` | Gauge | 1 | `Peer_Disconnects` | | Overlay Traffic | per-category | Gauge | 4×57 = 228 | `Bytes_In/Out`, `Messages_In/Out` per traffic category | | Pathfinding | — | Event | 2 | `pathfind_fast`, `pathfind_full` (histograms) | | I/O | — | Event | 1 | `ios_latency` (histogram) | | Resource Mgr | — | Meter | 2 | `warn`, `drop` (rate counters) | | Caches | per-cache | Gauge | 2×N | `{cache}.size`, `{cache}.hit_rate` | **Total**: ~255+ unique metrics (plus dynamic job-type and cache metrics) ### Tasks | Task | Description | | ---- | --------------------------------------------------------------------------------------------------------------- | | 6.1 | **DEFERRED** Fix Meter wire format (`\|m` → `\|c`) in StatsDCollector.cpp — breaking change, tracked separately | | 6.2 | Add `statsd` receiver to OTel Collector config | | 6.3 | Expose UDP port 8125 in docker-compose.yml | | 6.4 | Add `[insight]` config to integration test node configs | | 6.5 | Create "Node Health" Grafana dashboard (16 panels) | | 6.6 | Create "Network Traffic" Grafana dashboard (10 panels) | | 6.7 | Create "RPC & Pathfinding (StatsD)" Grafana dashboard (8 panels) | | 6.8 | Update integration test to verify StatsD metrics in Prometheus | | 6.9 | Update TESTING.md and telemetry-runbook.md | ### Wire Format Fix (Task 6.1) — DEFERRED The `StatsDMeterImpl` in `StatsDCollector.cpp` sends metrics with `|m` suffix, which is non-standard StatsD. The OTel StatsD receiver silently drops these. Fix: change `|m` to `|c` (counter), which is semantically correct since meters are increment-only counters. Only 2 metrics are affected (`warn`, `drop` in Resource Manager). **Status**: Deferred as a separate change — this is a breaking change for any StatsD backend that previously consumed the custom `|m` type. The Resource Warnings and Resource Drops dashboard panels will show no data until this fix is applied. ### New Grafana Dashboards **Node Health** (`statsd-node-health.json`, uid: `xrpld-statsd-node-health`): - Validated/Published Ledger Age, Operating Mode Duration/Transitions, I/O Latency, Job Queue Depth, Ledger Fetch Rate, Ledger History Mismatches, Key Jobs Execution/Dequeue Time, FullBelowCache Size/Hit Rate, Ledger Publish Gap, State Duration Rate, All Jobs Detail **Network Traffic** (`statsd-network-traffic.json`, uid: `xrpld-statsd-network`): - Active Inbound/Outbound Peers, Peer Disconnects, Total Bytes/Messages In/Out, Transaction/Proposal/Validation Traffic, Top Traffic Categories, Duplicate Traffic, All Traffic Categories Detail **RPC & Pathfinding (StatsD)** (`statsd-rpc-pathfinding.json`, uid: `xrpld-statsd-rpc`): - RPC Request Rate, Response Time p95/p50, Response Size p95/p50, Pathfinding Fast/Full Duration, Resource Warnings/Drops, Response Time Heatmap ### Exit Criteria - [ ] StatsD metrics visible in Prometheus (`curl localhost:9090/api/v1/query?query=ledgermaster_validated_ledger_age`) - [ ] All 3 new Grafana dashboards load without errors - [ ] Integration test verifies at least core StatsD metrics (ledger age, peer counts, RPC requests) - [ ] ~~Meter metrics (`warn`, `drop`) flow correctly after `|m` → `|c` fix~~ — DEFERRED (breaking change, tracked separately; resolved by Phase 7's OTel Counter mapping) --- ## 6.8 Phase 7: Native OTel Metrics Migration (Weeks 11-12) **Objective**: Replace `StatsDCollector` with a native OpenTelemetry Metrics SDK implementation behind the existing `beast::insight::Collector` interface, eliminating the StatsD UDP dependency and unifying traces and metrics into a single OTLP pipeline. ### Motivation: Why Migrate from StatsD to Native OTel Metrics The Phase 6 StatsD bridge was a pragmatic first step, but it retains inherent limitations that native OTel export resolves. #### What We Gain 1. **Unified telemetry pipeline** — Traces and metrics export via the same OTLP/HTTP endpoint to the same OTel Collector. One protocol, one endpoint, one config. Eliminates the split-brain architecture of "OTLP for traces, StatsD UDP for metrics." 2. **Eliminates StatsD UDP limitations** — StatsD is fire-and-forget over UDP with no delivery guarantees, no backpressure, 1472-byte MTU packet fragmentation, and text-based encoding overhead. OTLP uses HTTP/gRPC with retries, binary protobuf encoding, and connection-level flow control. 3. **Fixes the `|m` wire format issue** — The `StatsDMeterImpl` uses non-standard `|m` StatsD type that the OTel StatsD receiver silently drops. Native OTel counters eliminate this problem entirely (Phase 6 Task 6.1 — DEFERRED becomes resolved). 4. **Richer metric semantics** — OTel Metrics SDK supports explicit histogram bucket boundaries, exemplars (linking metrics to traces), resource attributes, and metric views. StatsD has no concept of these. 5. **Removes infrastructure dependency** — No more StatsD receiver needed in the OTel Collector. One less receiver to configure, monitor, and debug. Simplifies the collector YAML. 6. **Metric-to-trace correlation** — OTel metrics and traces share the same resource attributes (service.name, service.instance.id). Grafana can link from a metric spike directly to the traces that caused it — impossible with StatsD-sourced metrics. 7. **Production-grade export** — OTel's `PeriodicMetricReader` provides configurable export intervals, batch sizes, timeout handling, and graceful shutdown — all built into the SDK rather than hand-rolled in `StatsDCollectorImp`. #### What We Lose 1. **StatsD ecosystem compatibility** — Operators using external StatsD-compatible backends (Datadog Agent, Graphite, Telegraph) will need to switch to OTLP-compatible backends or keep `server=statsd` as a fallback. 2. **Simplicity of UDP** — StatsD's UDP fire-and-forget model is dead simple and has zero connection management. OTLP/HTTP requires a TCP connection, TLS negotiation (in production), and retry logic. The OTel SDK handles this, but it's more moving parts. 3. **Slightly higher memory** — OTel SDK maintains internal aggregation state for metrics before export. StatsD just formats and sends strings. Expected overhead: ~1-2 MB additional for metric state. 4. **Dependency on OTel C++ Metrics SDK stability** — The Metrics SDK is GA since 1.0 and on version 1.18.0, but it's less battle-tested than the tracing SDK in the C++ ecosystem. #### Decision The gains (unified pipeline, delivery guarantees, metric-trace correlation, simpler collector config) significantly outweigh the losses. `StatsDCollector` is retained as a fallback via `server=statsd` for operators who need StatsD ecosystem compatibility during the transition period. ### Architecture #### Class Hierarchy (after Phase 7) ``` beast::insight::Collector (abstract interface — unchanged) | +-- StatsDCollector (existing — retained as fallback, deprecated) | +-- StatsDCounterImpl -> StatsD |c over UDP | +-- StatsDGaugeImpl -> StatsD |g over UDP | +-- StatsDMeterImpl -> StatsD |m over UDP (non-standard) | +-- StatsDEventImpl -> StatsD |ms over UDP | +-- StatsDHookImpl -> 1s periodic callback | +-- NullCollector (existing — unchanged, used when disabled) | +-- NullCounterImpl -> no-op | +-- NullGaugeImpl -> no-op | +-- NullMeterImpl -> no-op | +-- NullEventImpl -> no-op | +-- NullHookImpl -> no-op | +-- OTelCollector (NEW — Phase 7) +-- OTelCounterImpl -> otel::Counter +-- OTelGaugeImpl -> otel::ObservableGauge +-- OTelMeterImpl -> otel::Counter +-- OTelEventImpl -> otel::Histogram +-- OTelHookImpl -> 1s periodic callback (same pattern) ``` #### Data Flow (after Phase 7) ```mermaid graph LR subgraph xrpldNode["xrpld Node"] A["Trace Macros
XRPL_TRACE_SPAN"] B["beast::insight
OTelCollector"] end subgraph collector["OTel Collector :4317 / :4318"] direction TB R1["OTLP Receiver
:4317 gRPC | :4318 HTTP"] BP["Batch Processor"] SM["SpanMetrics Connector"] R1 --> BP BP --> SM end subgraph backends["Trace Backends"] D["Tempo"] end subgraph metrics["Metrics Stack"] E["Prometheus :9090
scrapes :8889
span-derived + native OTel metrics"] end subgraph viz["Visualization"] F["Grafana :3000"] end A -->|"OTLP/HTTP :4318
(traces)"| R1 B -->|"OTLP/HTTP :4318
(metrics)"| R1 BP -->|"OTLP/gRPC"| D SM -->|"RED metrics"| E R1 -->|"system metrics
(native OTLP)"| E E --> F D --> F style A fill:#4a90d9,color:#fff,stroke:#2a6db5 style B fill:#d9534f,color:#fff,stroke:#b52d2d style R1 fill:#5cb85c,color:#fff,stroke:#3d8b3d style BP fill:#449d44,color:#fff,stroke:#2d6e2d style SM fill:#449d44,color:#fff,stroke:#2d6e2d style D fill:#f0ad4e,color:#000,stroke:#c78c2e style E fill:#f0ad4e,color:#000,stroke:#c78c2e style F fill:#5bc0de,color:#000,stroke:#3aa8c1 style xrpldNode fill:#1a2633,color:#ccc,stroke:#4a90d9 style collector fill:#1a3320,color:#ccc,stroke:#5cb85c style backends fill:#332a1a,color:#ccc,stroke:#f0ad4e style metrics fill:#332a1a,color:#ccc,stroke:#f0ad4e style viz fill:#1a2d33,color:#ccc,stroke:#5bc0de ``` **Key change**: StatsD receiver removed from collector. Both traces and metrics enter via OTLP receiver on the same port. #### Configuration ```ini # [insight] section — new "otel" server option [insight] server=otel # NEW: uses OTel OTLP metrics exporter prefix=xrpld # metric name prefix (preserved) # Endpoint and auth inherited from [telemetry] section: [telemetry] enabled=1 endpoint=http://localhost:4318/v1/traces ``` The `OTelCollector` reads the OTLP endpoint from `[telemetry]` config (replacing `/v1/traces` with `/v1/metrics` for the metrics exporter). No additional config keys needed. **Backward compatibility**: `server=statsd` continues to work exactly as before. See [Phase7_taskList.md](./Phase7_taskList.md) for detailed per-task breakdown. ### Instrument Type Mapping | beast::insight | OTel Metrics SDK | Rationale | | ---------------------- | -------------------------------- | ---------------------------------------------------------------- | | Counter (int64, `\|c`) | `Counter` | Direct 1:1 mapping | | Gauge (uint64, `\|g`) | `ObservableGauge` | Async callback matches existing Hook polling pattern | | Meter (uint64, `\|m`) | `Counter` | Fixes non-standard wire format; meters are semantically counters | | Event (ms, `\|ms`) | `Histogram` | Duration distributions with explicit bucket boundaries | | Hook (1s callback) | `PeriodicMetricReader` alignment | Same 1s collection interval | ### Tasks | Task | Description | | ---- | ------------------------------------------------------------------------- | | 7.1 | Add OTel Metrics SDK to build deps (conan/cmake) | | 7.2 | Implement `OTelCollector` class (~400-500 lines) | | 7.3 | Update `CollectorManager` — add `server=otel` | | 7.4 | Update OTel Collector YAML (add metrics pipeline, remove StatsD receiver) | | 7.5 | Preserve metric names in Prometheus (naming strategy) | | 7.6 | Update Grafana dashboards (if names change) | | 7.7 | Update integration tests | | 7.8 | Update documentation (runbook, reference docs) | ### Exit Criteria - [ ] All 255+ metrics visible in Prometheus via OTLP pipeline (no StatsD receiver) - [ ] `server=otel` is the default in development docker-compose - [ ] `server=statsd` still works as a fallback - [ ] Existing Grafana dashboards display data correctly - [ ] Integration test passes with OTLP-only metrics pipeline - [ ] No performance regression vs StatsD baseline (< 1% CPU overhead) - [ ] Deferred Task 6.1 (`|m` wire format) no longer relevant --- ## 6.8 Phase 7: Native OTel Metrics Migration (Weeks 11-12) **Objective**: Replace `StatsDCollector` with a native OpenTelemetry Metrics SDK implementation behind the existing `beast::insight::Collector` interface, eliminating the StatsD UDP dependency and unifying traces and metrics into a single OTLP pipeline. ### Motivation: Why Migrate from StatsD to Native OTel Metrics The Phase 6 StatsD bridge was a pragmatic first step, but it retains inherent limitations that native OTel export resolves. #### What We Gain 1. **Unified telemetry pipeline** — Traces and metrics export via the same OTLP/HTTP endpoint to the same OTel Collector. One protocol, one endpoint, one config. Eliminates the split-brain architecture of "OTLP for traces, StatsD UDP for metrics." 2. **Eliminates StatsD UDP limitations** — StatsD is fire-and-forget over UDP with no delivery guarantees, no backpressure, 1472-byte MTU packet fragmentation, and text-based encoding overhead. OTLP uses HTTP/gRPC with retries, binary protobuf encoding, and connection-level flow control. 3. **Fixes the `|m` wire format issue** — The `StatsDMeterImpl` uses non-standard `|m` StatsD type that the OTel StatsD receiver silently drops. Native OTel counters eliminate this problem entirely (Phase 6 Task 6.1 — DEFERRED becomes resolved). 4. **Richer metric semantics** — OTel Metrics SDK supports explicit histogram bucket boundaries, exemplars (linking metrics to traces), resource attributes, and metric views. StatsD has no concept of these. 5. **Removes infrastructure dependency** — No more StatsD receiver needed in the OTel Collector. One less receiver to configure, monitor, and debug. Simplifies the collector YAML. 6. **Metric-to-trace correlation** — OTel metrics and traces share the same resource attributes (service.name, service.instance.id). Grafana can link from a metric spike directly to the traces that caused it — impossible with StatsD-sourced metrics. 7. **Production-grade export** — OTel's `PeriodicMetricReader` provides configurable export intervals, batch sizes, timeout handling, and graceful shutdown — all built into the SDK rather than hand-rolled in `StatsDCollectorImp`. #### What We Lose 1. **StatsD ecosystem compatibility** — Operators using external StatsD-compatible backends (Datadog Agent, Graphite, Telegraph) will need to switch to OTLP-compatible backends or keep `server=statsd` as a fallback. 2. **Simplicity of UDP** — StatsD's UDP fire-and-forget model is dead simple and has zero connection management. OTLP/HTTP requires a TCP connection, TLS negotiation (in production), and retry logic. The OTel SDK handles this, but it's more moving parts. 3. **Slightly higher memory** — OTel SDK maintains internal aggregation state for metrics before export. StatsD just formats and sends strings. Expected overhead: ~1-2 MB additional for metric state. 4. **Dependency on OTel C++ Metrics SDK stability** — The Metrics SDK is GA since 1.0 and on version 1.18.0, but it's less battle-tested than the tracing SDK in the C++ ecosystem. #### Decision The gains (unified pipeline, delivery guarantees, metric-trace correlation, simpler collector config) significantly outweigh the losses. `StatsDCollector` is retained as a fallback via `server=statsd` for operators who need StatsD ecosystem compatibility during the transition period. ### Architecture #### Class Hierarchy (after Phase 7) ``` beast::insight::Collector (abstract interface — unchanged) | +-- StatsDCollector (existing — retained as fallback, deprecated) | +-- StatsDCounterImpl -> StatsD |c over UDP | +-- StatsDGaugeImpl -> StatsD |g over UDP | +-- StatsDMeterImpl -> StatsD |m over UDP (non-standard) | +-- StatsDEventImpl -> StatsD |ms over UDP | +-- StatsDHookImpl -> 1s periodic callback | +-- NullCollector (existing — unchanged, used when disabled) | +-- NullCounterImpl -> no-op | +-- NullGaugeImpl -> no-op | +-- NullMeterImpl -> no-op | +-- NullEventImpl -> no-op | +-- NullHookImpl -> no-op | +-- OTelCollector (NEW — Phase 7) +-- OTelCounterImpl -> otel::Counter +-- OTelGaugeImpl -> otel::ObservableGauge +-- OTelMeterImpl -> otel::Counter +-- OTelEventImpl -> otel::Histogram +-- OTelHookImpl -> 1s periodic callback (same pattern) ``` #### Data Flow (after Phase 7) ```mermaid graph LR subgraph xrpldNode["xrpld Node"] A["Trace Macros
XRPL_TRACE_SPAN"] B["beast::insight
OTelCollector"] end subgraph collector["OTel Collector :4317 / :4318"] direction TB R1["OTLP Receiver
:4317 gRPC | :4318 HTTP"] BP["Batch Processor"] SM["SpanMetrics Connector"] R1 --> BP BP --> SM end subgraph backends["Trace Backends"] D["Jaeger / Tempo"] end subgraph metrics["Metrics Stack"] E["Prometheus :9090
scrapes :8889
span-derived + native OTel metrics"] end subgraph viz["Visualization"] F["Grafana :3000"] end A -->|"OTLP/HTTP :4318
(traces)"| R1 B -->|"OTLP/HTTP :4318
(metrics)"| R1 BP -->|"OTLP/gRPC"| D SM -->|"RED metrics"| E R1 -->|"system metrics
(native OTLP)"| E E --> F D --> F style A fill:#4a90d9,color:#fff,stroke:#2a6db5 style B fill:#d9534f,color:#fff,stroke:#b52d2d style R1 fill:#5cb85c,color:#fff,stroke:#3d8b3d style BP fill:#449d44,color:#fff,stroke:#2d6e2d style SM fill:#449d44,color:#fff,stroke:#2d6e2d style D fill:#f0ad4e,color:#000,stroke:#c78c2e style E fill:#f0ad4e,color:#000,stroke:#c78c2e style F fill:#5bc0de,color:#000,stroke:#3aa8c1 style xrpldNode fill:#1a2633,color:#ccc,stroke:#4a90d9 style collector fill:#1a3320,color:#ccc,stroke:#5cb85c style backends fill:#332a1a,color:#ccc,stroke:#f0ad4e style metrics fill:#332a1a,color:#ccc,stroke:#f0ad4e style viz fill:#1a2d33,color:#ccc,stroke:#5bc0de ``` **Key change**: StatsD receiver removed from collector. Both traces and metrics enter via OTLP receiver on the same port. #### Configuration ```ini # [insight] section — new "otel" server option [insight] server=otel # NEW: uses OTel OTLP metrics exporter prefix=xrpld # metric name prefix (preserved) # Endpoint and auth inherited from [telemetry] section: [telemetry] enabled=1 endpoint=http://localhost:4318/v1/traces ``` The `OTelCollector` reads the OTLP endpoint from `[telemetry]` config (replacing `/v1/traces` with `/v1/metrics` for the metrics exporter). No additional config keys needed. **Backward compatibility**: `server=statsd` continues to work exactly as before. See [Phase7_taskList.md](./Phase7_taskList.md) for detailed per-task breakdown. ### Instrument Type Mapping | beast::insight | OTel Metrics SDK | Rationale | | ---------------------- | -------------------------------- | ---------------------------------------------------------------- | | Counter (int64, `\|c`) | `Counter` | Direct 1:1 mapping | | Gauge (uint64, `\|g`) | `ObservableGauge` | Async callback matches existing Hook polling pattern | | Meter (uint64, `\|m`) | `Counter` | Fixes non-standard wire format; meters are semantically counters | | Event (ms, `\|ms`) | `Histogram` | Duration distributions with explicit bucket boundaries | | Hook (1s callback) | `PeriodicMetricReader` alignment | Same 1s collection interval | ### Tasks | Task | Description | | ---- | ------------------------------------------------------------------------- | | 7.1 | Add OTel Metrics SDK to build deps (conan/cmake) | | 7.2 | Implement `OTelCollector` class (~400-500 lines) | | 7.3 | Update `CollectorManager` — add `server=otel` | | 7.4 | Update OTel Collector YAML (add metrics pipeline, remove StatsD receiver) | | 7.5 | Preserve metric names in Prometheus (naming strategy) | | 7.6 | Update Grafana dashboards (if names change) | | 7.7 | Update integration tests | | 7.8 | Update documentation (runbook, reference docs) | ### Exit Criteria - [ ] All 255+ metrics visible in Prometheus via OTLP pipeline (no StatsD receiver) - [ ] `server=otel` is the default in development docker-compose - [ ] `server=statsd` still works as a fallback - [ ] Existing Grafana dashboards display data correctly - [ ] Integration test passes with OTLP-only metrics pipeline - [ ] No performance regression vs StatsD baseline (< 1% CPU overhead) - [ ] Deferred Task 6.1 (`|m` wire format) no longer relevant --- ## 6.9 Phase 8: Log-Trace Correlation and Centralized Log Ingestion (Week 13) ### Motivation xrpld's `beast::Journal` logs and OpenTelemetry traces are currently two disjoint observability signals. When investigating an issue, operators must manually correlate timestamps between log files and Tempo traces. Phase 8 bridges this gap by injecting trace context (`trace_id`, `span_id`) into every log line emitted within an active span, and ingesting those logs into Grafana Loki via the OTel Collector's filelog receiver. #### Gains 1. **One-click trace-to-log navigation** — Click a trace in Tempo and immediately see the corresponding log lines in Loki, filtered by `trace_id`. 2. **Reverse lookup (log-to-trace)** — Loki derived fields make `trace_id` values clickable links back to Tempo. 3. **Unified observability** — All three pillars (traces, metrics, logs) flow through the same OTel Collector pipeline and are visible in a single Grafana instance. 4. **Zero new dependencies in xrpld** — Uses existing OTel SDK headers (`GetSpan`, `GetContext`) already linked in Phase 1. 5. **Negligible overhead** — The implementation checks the thread-local context value directly, avoiding heap allocation on the no-span path (~15-20ns). On the active-span path, total cost is ~50ns per log call. At typical logging rates, overhead is negligible. #### Losses / Risks 1. **Log format change** — Existing log parsers that rely on a fixed format will need updating to handle the optional `trace_id=... span_id=...` fields. 2. **Loki resource usage** — Log ingestion adds storage and memory overhead to the observability stack (mitigated by retention policies). 3. **Filelog receiver complexity** — The regex parser must be kept in sync with the log format; a format change in `Logs::format()` could break parsing. #### Decision The correlation value far outweighs the risks. The log format change is backward-compatible (fields are appended only when a span is active), and the filelog receiver regex is straightforward to maintain. ### Architecture Phase 8 has two independent sub-phases that can be developed in parallel: - **Phase 8a (code change)**: Modify `Logs::format()` in `src/libxrpl/basics/Log.cpp` to append `trace_id= span_id=` when the current thread has an active OTel span. Guarded by `#ifdef XRPL_ENABLE_TELEMETRY`. - **Phase 8b (infra only)**: Add Loki to the Docker Compose stack, configure the OTel Collector's `filelog` receiver to tail xrpld's log file, parse out structured fields (timestamp, partition, severity, trace_id, span_id, message), and export to Loki via OTLP. Configure Grafana Tempo↔Loki bidirectional linking. #### Trace ID Injection Flow ```mermaid flowchart LR subgraph xrpld["xrpld process"] JLOG["JLOG(j.info())"] Format["Logs::format()"] OTelCtx["OTel Context
(thread-local)"] JLOG --> Format OTelCtx -.->|"GetSpan()→GetContext()"| Format end subgraph output["Log Output"] LogLine["2024-01-15T10:30:45.123Z
LedgerMaster:NFO
trace_id=abc123...
span_id=def456...
Validated ledger 42"] end Format --> LogLine style xrpld fill:#1a237e,stroke:#0d1642,color:#fff style output fill:#1b5e20,stroke:#0d3d14,color:#fff style JLOG fill:#283593,stroke:#1a237e,color:#fff style Format fill:#283593,stroke:#1a237e,color:#fff style OTelCtx fill:#283593,stroke:#1a237e,color:#fff style LogLine fill:#2e7d32,stroke:#1b5e20,color:#fff ``` #### Loki Ingestion Pipeline ```mermaid flowchart LR subgraph collector["OTel Collector"] FR["filelog receiver
tails debug.log"] RP["regex_parser
extracts trace_id,
span_id, severity"] BP["batch processor"] LE["otlp/loki exporter"] FR --> RP --> BP --> LE end LogFile["xrpld
debug.log"] --> FR LE --> Loki["Grafana Loki
:3100"] Loki <-->|"derivedFields ↔
tracesToLogs"| Tempo["Grafana Tempo"] style collector fill:#e65100,stroke:#bf360c,color:#fff style FR fill:#f57c00,stroke:#e65100,color:#fff style RP fill:#f57c00,stroke:#e65100,color:#fff style BP fill:#f57c00,stroke:#e65100,color:#fff style LE fill:#f57c00,stroke:#e65100,color:#fff style LogFile fill:#1a237e,stroke:#0d1642,color:#fff style Loki fill:#4a148c,stroke:#2e0d57,color:#fff style Tempo fill:#4a148c,stroke:#2e0d57,color:#fff ``` ### Tasks | Task | Description | | ---- | ---------------------------------------------- | | 8.1 | Inject trace_id into Logs::format() | | 8.2 | Add Loki to Docker Compose stack | | 8.3 | Add filelog receiver to OTel Collector | | 8.4 | Configure Grafana trace-to-log correlation | | 8.5 | Update integration tests | | 8.6 | Update documentation (runbook, reference docs) | **Parallel work**: Task 8.2 (Loki infra) can run in parallel with Task 8.1 (code change). Tasks 8.3–8.6 are sequential. ### Exit Criteria - [ ] Log lines within active spans contain `trace_id= span_id=` - [ ] Log lines outside spans have no trace context (no empty fields) - [ ] Loki ingests xrpld logs via OTel Collector filelog receiver - [ ] Grafana Tempo → Loki one-click correlation works - [ ] Grafana Loki → Tempo reverse lookup works via derived field - [ ] Integration test verifies trace_id presence in logs - [ ] No performance regression from trace_id injection (< 0.1% overhead) --- ## 6.8.2 Phase 9: Internal Metric Instrumentation Gap Fill (Weeks 14-15) — Future Enhancement > **Status**: Planned, not yet implemented. ### Motivation Phases 1-8 establish trace spans, StatsD metrics bridge, native OTel metrics, and log-trace correlation. However, ~68 metrics that exist inside xrpld's `get_counts`, `server_info`, TxQ, PerfLog, and `CountedObject` systems have **no time-series export path**. These are the metrics that exchanges, payment processors, analytics providers, validators, and researchers need most — NodeStore I/O performance, cache hit rates, per-RPC-method counters, transaction queue depth, fee escalation levels, and live object instance counts. ### Architecture Hybrid approach — two instrumentation strategies based on proximity to existing code: ```mermaid flowchart TB subgraph xrpld["xrpld process"] subgraph existing["Existing beast::insight registrations"] NS["NodeStore I/O
(Database.cpp)"] end subgraph newreg["New OTel MetricsRegistry"] CR["Cache Hit Rates
(async gauge callbacks)"] TQ["TxQ Metrics
(async gauge callbacks)"] PL["PerfLog RPC/Job
(counters + histograms)"] CO["CountedObjects
(async gauge callbacks)"] LF["Load Factors
(async gauge callbacks)"] end end subgraph export["Export Pipelines"] BI["beast::insight
OTelCollector (Phase 7)"] OS["OTel Metrics SDK
PeriodicMetricReader"] end NS --> BI CR --> OS TQ --> OS PL --> OS CO --> OS LF --> OS BI --> OTLP["OTLP/HTTP :4318
/v1/metrics"] OS --> OTLP style xrpld fill:#1a2633,color:#ccc,stroke:#4a90d9 style existing fill:#2a4a6b,color:#fff,stroke:#4a90d9 style newreg fill:#2a4a6b,color:#fff,stroke:#4a90d9 style export fill:#1a3320,color:#ccc,stroke:#5cb85c style NS fill:#4a90d9,color:#fff,stroke:#2a6db5 style CR fill:#5cb85c,color:#fff,stroke:#3d8b3d style TQ fill:#5cb85c,color:#fff,stroke:#3d8b3d style PL fill:#5cb85c,color:#fff,stroke:#3d8b3d style CO fill:#5cb85c,color:#fff,stroke:#3d8b3d style LF fill:#5cb85c,color:#fff,stroke:#3d8b3d style BI fill:#449d44,color:#fff,stroke:#2d6e2d style OS fill:#449d44,color:#fff,stroke:#2d6e2d style OTLP fill:#f0ad4e,color:#000,stroke:#c78c2e ``` - **beast::insight extensions** (blue): NodeStore I/O metrics added near existing `Database.cpp` registrations — exported via Phase 7's `OTelCollector`. - **OTel MetricsRegistry** (green): New centralized class using `ObservableGauge` async callbacks for cache, TxQ, PerfLog, CountedObjects, and load factors — polled at 10s intervals by `PeriodicMetricReader`. ### Third-Party Consumer Context | Consumer Category | Key Metrics They Need From Phase 9 | | ---------------------- | --------------------------------------------------------------- | | Exchanges | Fee escalation levels, TxQ depth, settlement latency | | Payment Processors | Load factors, io_latency, transaction throughput | | Analytics Providers | NodeStore I/O, cache hit rates, counted objects | | Validators / Operators | Per-job execution times, PerfLog RPC counters, consensus timing | | Academic Researchers | Consensus performance time-series, fee market dynamics | | Institutional Custody | Server health scores, reserve calculations, node availability | ### Tasks | Task | Description | | ---- | ----------------------------------------- | | 9.1 | NodeStore I/O metrics | | 9.2 | Cache hit rate metrics + MetricsRegistry | | 9.3 | TxQ metrics | | 9.4 | PerfLog per-RPC metrics | | 9.5 | PerfLog per-job metrics | | 9.6 | Counted object instance metrics | | 9.7 | Fee escalation & load factor metrics | | 9.7a | push_metrics.py parity gauges | | 9.8 | New Grafana dashboards (2 new, 2 updated) | | 9.9 | Update documentation | | 9.10 | Integration tests | See [Phase9_taskList.md](./Phase9_taskList.md) for detailed per-task breakdown. ### Exit Criteria - [ ] All ~68 new metrics visible in Prometheus via OTLP pipeline - [ ] `MetricsRegistry` class registers/deregisters cleanly with OTel SDK - [ ] 2 new Grafana dashboards operational (Fee Market, Job Queue) - [ ] No performance regression (< 0.5% CPU overhead from new callbacks) - [ ] Documentation updated with full new metric inventory --- ## 6.8.3 Phase 10: Synthetic Workload Generation & Telemetry Validation (Weeks 16-17) > **Status**: In progress. ### Motivation Before the telemetry stack (Phases 1-9) can be considered production-ready, we need automated proof that all spans, attributes, metrics, Grafana dashboards, and log-trace correlation work correctly under realistic load. This phase establishes a reusable CI-integrated validation suite and performance benchmark baseline. ### Architecture The validation uses a **2-node** validator cluster running as local processes alongside a Docker Compose telemetry stack (Collector, Tempo, Prometheus, Grafana). Two nodes are sufficient for consensus rounds and peer-to-peer span validation while minimizing CI resource usage. ```mermaid flowchart LR subgraph harness["2-Node Validator Cluster (local processes)"] direction TB V1["Validator 1"] ~~~ V2["Validator 2"] end subgraph telemetry["Docker Compose Telemetry Stack"] direction TB COL["OTel Collector
(OTLP + StatsD)"] JAE["Tempo
(trace search)"] PROM["Prometheus
(metrics)"] GRAF["Grafana
(dashboards)"] end subgraph generators["Workload Generators"] RPC["RPC Load Generator
(configurable RPS,
command distribution)"] TX["Transaction Submitter
(10 tx types via
WebSocket command API)"] end subgraph validation["Validation Suite"] SV["Span Validator
(Tempo API)"] MV["Metric Validator
(Prometheus API,
all 26 metrics required)"] DV["Dashboard Validator
(Grafana API)"] BM["Benchmark Suite
(CPU, memory, latency
ON vs OFF comparison)"] end generators --> harness harness --> telemetry telemetry --> validation style harness fill:#1a2633,color:#ccc,stroke:#4a90d9 style telemetry fill:#1a2633,color:#ccc,stroke:#4a90d9 style generators fill:#1a3320,color:#ccc,stroke:#5cb85c style validation fill:#332a1a,color:#ccc,stroke:#f0ad4e style V1 fill:#4a90d9,color:#fff,stroke:#2a6db5 style V2 fill:#4a90d9,color:#fff,stroke:#2a6db5 style COL fill:#4a90d9,color:#fff,stroke:#2a6db5 style JAE fill:#4a90d9,color:#fff,stroke:#2a6db5 style PROM fill:#4a90d9,color:#fff,stroke:#2a6db5 style GRAF fill:#4a90d9,color:#fff,stroke:#2a6db5 style RPC fill:#5cb85c,color:#fff,stroke:#3d8b3d style TX fill:#5cb85c,color:#fff,stroke:#3d8b3d style SV fill:#f0ad4e,color:#000,stroke:#c78c2e style MV fill:#f0ad4e,color:#000,stroke:#c78c2e style DV fill:#f0ad4e,color:#000,stroke:#c78c2e style BM fill:#f0ad4e,color:#000,stroke:#c78c2e ``` ### Key Implementation Details - **Transaction submitter and RPC load generator** both use xrpld's native WebSocket command format (`{"command": ...}`) — not JSON-RPC format. Response data lives inside `"result"` with `"status"` at the top level. - **Node config** requires `[signing_support] true` for server-side signing, and `[ips]` (not `[ips_fixed]`) to ensure peer connections count in `peer_finder_active_*` metrics. - **Metric validation** uses the Prometheus `/api/v1/series` endpoint (not instant queries) to avoid false negatives from stale StatsD gauges. Every metric in `expected_metrics.json` must have > 0 series. - **StatsD gauge fix**: `StatsDGaugeImpl` initializes `m_dirty = true` so all gauges emit their initial value on first flush. Without this, gauges starting at 0 that never change (e.g. `jobq_job_count`) would be invisible in Prometheus. - **I/O latency fix**: `io_latency_sampler` emits unconditionally on first sample, then applies the 10 ms threshold. This ensures `ios_latency` is registered in Prometheus even in low-load CI environments. - **tx.receive span**: Sets default attributes (`xrpl.tx.suppressed = false`, `xrpl.tx.status = "new"`) on span creation so they are always present. The suppressed/bad code paths override these when applicable. ### Tasks | Task | Description | | ---- | -------------------------------------- | | 10.1 | Multi-node test harness (5 validators) | | 10.2 | RPC load generator | | 10.3 | Transaction submitter (6+ tx types) | | 10.4 | Telemetry validation suite | | 10.5 | Performance benchmark suite | | 10.6 | CI integration | | 10.7 | Documentation | See [Phase10_taskList.md](./Phase10_taskList.md) for detailed per-task breakdown. ### Validation Check Inventory (71 Checks) The validation suite (`validate_telemetry.py`) runs exactly 71 checks, broken down as: - **1 service registration** — `xrpld` exists in Tempo - **17 span existence** — `rpc.request`, `rpc.process`, `rpc.ws_message`, `rpc.command.*`, `tx.process`, `tx.receive`, `tx.apply`, `consensus.proposal.send`, `consensus.ledger_close`, `consensus.accept`, `consensus.validation.send`, `consensus.accept.apply`, `ledger.build`, `ledger.validate`, `ledger.store`, `peer.proposal.receive`, `peer.validation.receive` - **14 span attribute** — required attributes on the 14 spans that define them (22 unique attributes total) - **2 span hierarchies** — `rpc.process` -> `rpc.command.*`, `ledger.build` -> `tx.apply` (1 skipped: `rpc.request` -> `rpc.process`, cross-thread) - **1 span duration bounds** — all spans > 0 and < 60 s - **26 metric existence** — 4 SpanMetrics (`span_calls_total`, `span_duration_milliseconds_{bucket,count,sum}`), 6 StatsD gauges (`ledgermaster_validated_ledger_age`, `published_ledger_age`, `state_accounting_full_duration`, `peer_finder_active_{inbound,outbound}_peers`, `jobq_job_count`), 2 StatsD counters (`rpc_requests_total`, `ledger_fetches_total`), 3 StatsD histograms (`rpc_time`, `rpc_size`, `ios_latency`), 4 overlay traffic (`total_bytes_{in,out}`, `total_messages_{in,out}`), 7 Phase 9 OTLP (`nodestore_state`, `cache_metrics`, `txq_metrics`, `rpc_method_{started,finished}_total`, `object_count`, `load_factor_metrics`) - **10 dashboard loads** — `rpc-performance`, `transaction-overview`, `consensus-health`, `ledger-operations`, `peer-network`, `node-health`, `network-traffic`, `rpc-pathfinding`, `overlay-traffic-detail`, `ledger-data-sync` See [Phase10_taskList.md](./Phase10_taskList.md) for the full numbered check-by-check enumeration. ### Current Status **Working** (71/71 checks pass in CI): All 17 spans, 26 metrics, 10 dashboards, 14 attribute checks, 2 hierarchies, and duration bounds validated. **Not implemented or not available in CI**: 1. `rpc.request` -> `rpc.process` parent-child hierarchy — skipped (cross-thread context propagation) 2. Log-trace correlation validation (Loki) — not included in checks 3. Full 255+ StatsD metric coverage — only 26 representative metrics validated 4. Sustained load / backpressure testing — not implemented 5. `docs/telemetry-runbook.md` updates — not done 6. `09-data-collection-reference.md` "Validation" section — not done 7. **Automated cross-CI baseline persistence** — the regression gate reads a committed baseline; baseline updates flow through a manual PR refresh, not an artifact promoted from `develop` (FU-2). ### Exit Criteria - [x] 2-node validator cluster starts and reaches consensus - [x] Validation suite confirms all required spans, attributes, and metrics (71/71 checks) - [x] All 10 Grafana dashboards render data - [ ] Benchmark shows < 3% CPU overhead, < 5MB memory overhead - [x] CI workflow runs validation on telemetry branch changes - [x] OTel-driven regression gate: captures per-span/per-RPC/per-job timings from Prometheus and compares against a committed baseline --- ## 6.8.4 Phase 11: Third-Party Data Collection Pipelines (Weeks 18-20) — Future Enhancement > **Status**: Planned, not yet implemented. ### Motivation xrpld has no native Prometheus/OTLP metrics export for data accessible only via JSON-RPC (`server_info`, `get_counts`, `fee`, `peers`, `validators`, `feature`). Every external consumer — exchanges, payment processors, analytics providers, validators, compliance firms, DeFi protocols, researchers, custodians, and CBDC platforms — must build custom JSON-RPC polling and conversion pipelines. This phase centralizes that work into a reusable custom OTel Collector receiver. ### Architecture ```mermaid flowchart LR subgraph receiver["Custom OTel Collector Receiver (Go)"] direction TB SI["server_info
collector"] GC["get_counts
collector"] FE["fee
collector"] PE["peers
collector"] VA["validators
collector"] DX["DEX/AMM
collector
(optional)"] end xrpld["xrpld
Admin RPC
:5005"] -->|"JSON-RPC
poll every 30s"| receiver receiver -->|"xrpl_* metrics"| PROM["Prometheus
:9090"] receiver -->|"OTLP export"| OTLP["Any OTLP-
compatible
backend"] PROM --> GF["Grafana
4 new dashboards"] PROM --> AL["Prometheus
Alerting Rules"] style receiver fill:#1a3320,color:#ccc,stroke:#5cb85c style SI fill:#5cb85c,color:#fff,stroke:#3d8b3d style GC fill:#5cb85c,color:#fff,stroke:#3d8b3d style FE fill:#5cb85c,color:#fff,stroke:#3d8b3d style PE fill:#5cb85c,color:#fff,stroke:#3d8b3d style VA fill:#5cb85c,color:#fff,stroke:#3d8b3d style DX fill:#449d44,color:#fff,stroke:#2d6e2d style xrpld fill:#4a90d9,color:#fff,stroke:#2a6db5 style PROM fill:#f0ad4e,color:#000,stroke:#c78c2e style OTLP fill:#f0ad4e,color:#000,stroke:#c78c2e style GF fill:#5bc0de,color:#000,stroke:#3aa8c1 style AL fill:#d9534f,color:#fff,stroke:#b52d2d ``` ### Third-Party Consumer Gap Analysis | Consumer Category | Data Unlocked by Phase 11 | | ---------------------- | ------------------------------------------------------------ | | Exchanges | Real-time fee estimates, TxQ capacity, server health scores | | Payment Processors | Settlement latency percentiles, corridor health | | Analytics Providers | Validator metrics, network topology, amendment voting status | | DeFi / AMM | AMM pool TVL, DEX order book depth, trade volumes | | Validators / Operators | Per-peer latency, version distribution, UNL health, alerting | | Compliance | Transaction volume trends, network growth metrics | | Academic Researchers | Consensus performance time-series, decentralization metrics | | CBDC / Tokenization | Token supply tracking, trust line adoption, freeze status | | Institutional Custody | Multi-sig status, escrow tracking, reserve calculations | | Wallet Providers | Server health for node selection, fee prediction data | ### Tasks | Task | Description | | ----- | ------------------------------------- | | 11.1 | OTel Collector receiver scaffold (Go) | | 11.2 | server_info / server_state collector | | 11.3 | get_counts collector | | 11.4 | Peer topology collector | | 11.5 | Validator & amendment collector | | 11.6 | Fee & TxQ collector | | 11.7 | DEX & AMM collector (optional) | | 11.8 | Prometheus alerting rules | | 11.9 | New Grafana dashboards (4) | | 11.10 | Integration with Phase 10 validation | | 11.11 | Documentation | See [Phase11_taskList.md](./Phase11_taskList.md) for detailed per-task breakdown. ### Exit Criteria - [ ] Custom OTel Collector receiver exports all `xrpl_*` metrics to Prometheus - [ ] 4 new Grafana dashboards operational (Validator Health, Network Topology, Fee Market, DEX/AMM) - [ ] Prometheus alerting rules fire correctly for simulated failures - [ ] Receiver handles xrpld restart/unavailability gracefully - [ ] Go receiver has unit tests with >80% coverage --- ## 6.9 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 | --- ## 6.10 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 | --- ## 6.11 Quick Wins and Crawl-Walk-Run Strategy > **TxQ** = Transaction Queue This section outlines a prioritized approach to maximize ROI with minimal initial investment. ### 6.11.1 Crawl-Walk-Run Overview
```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[Establish Phase
& Cross-Node Correlation] ~~~ r3[StatsD Integration] ~~~ 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 ```
**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, establish-phase gap fill, cross-node correlation, StatsD integration, 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. ### 6.11.2 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 | ### 6.11.3 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 ### 6.11.4 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 ### 6.11.5 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~~ — descoped - ~~Amendment voting tracing~~ — descoped - ~~SHAMap sync tracing~~ — descoped - Full end-to-end traces (client → RPC → TX → consensus → ledger) — partial (tx-consensus correlation not yet done) **Code Changes**: ~100 lines across 3 consensus files **Why Do This Last**: - Highest complexity (consensus is critical path) - Validator, amendment, and SHAMap components were descoped (lower priority) - Requires thorough testing - Lower relative value (consensus issues are rarer) ### 6.11.6 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] ``` --- ## 6.12 Definition of Done > **TxQ** = Transaction Queue | **HA** = High Availability Clear, measurable criteria for each phase. ### 6.12.1 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. ### 6.12.2 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. ### 6.12.3 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 | | Deterministic TraceID | Same trace_id on all nodes for same tx | Multi-node test: query by txHash[0:16] returns all spans | | Relay Ordering | Protobuf span_id propagation creates parent-child | Tempo trace tree shows relay chain | | Graceful Degradation | Old peer drops trace_context | Spans still grouped by deterministic trace_id | | 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 with deterministic trace_id correlation, parent-child ordering via protobuf propagation, and performance within bounds. ### 6.12.4 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. ### 6.12.5 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. ### 6.12.6 Success Metrics Summary | Phase | Primary Metric | Secondary Metric | Deadline | Status | | -------- | ------------------------------------------------------------------ | --------------------------- | -------------- | ------------------ | | Phase 1 | SDK compiles and runs | Zero overhead when disabled | End of Week 2 | Active | | Phase 2 | 100% RPC coverage | <1ms latency overhead | End of Week 4 | Active | | Phase 3 | Cross-node traces work | <5% throughput impact | End of Week 6 | Active | | Phase 4 | Consensus fully traced | No consensus timing impact | End of Week 8 | Active | | Phase 5 | Production deployment | Operators trained | End of Week 9 | Active | | Phase 6 | StatsD metrics in Prometheus | 3 dashboards operational | End of Week 10 | Active | | Phase 7 | All metrics via OTLP | No StatsD dependency | End of Week 12 | Active | | Phase 8 | trace_id in logs + Loki | Tempo↔Loki correlation | End of Week 13 | Active | | Phase 9 | 68+ new internal metrics in Prom | 2 new dashboards | End of Week 15 | Future Enhancement | | Phase 10 | Full telemetry stack validated; OTel-sourced regression gate in CI | < 3% CPU overhead proven | End of Week 17 | Future Enhancement | | Phase 11 | Third-party metrics via receiver | 4 new dashboards + alerting | End of Week 20 | Future Enhancement | --- ## 6.13 Recommended Implementation Order Based on ROI analysis, implement in this exact order: ```mermaid flowchart TB subgraph week1["Week 1"] t1[1. OpenTelemetry SDK
Conan/CMake integration] t2[2. Telemetry interface
SpanGuard, config] end subgraph week2["Week 2"] t3[3. RPC ServerHandler
instrumentation] t4[4. Basic Tempo setup
for testing] end subgraph week3["Week 3"] t5[5. Transaction submit
tracing] t6[6. Grafana dashboard
v1] end subgraph week4["Week 4"] t7[7. Protobuf context
extension] t8[8. PeerImp tx.relay
instrumentation] end subgraph week5["Week 5"] t9[9. Multi-node
integration tests] t10[10. Performance
benchmarks] end subgraph week6_8["Weeks 6-8"] t11[11. Consensus
instrumentation] t12[12. Full integration
testing] end subgraph week9["Week 9"] t13[13. Production
deployment] t14[14. Documentation
& 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. --- --- ## Appendix: External Dashboard Parity > Cross-phase plan for reaching parity with the community [xrpl-validator-dashboard](https://github.com/realgrapedrop/xrpl-validator-dashboard). Previously a standalone design spec; merged here so the phase plan is self-contained. > **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 xrpld'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 xrpld 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()` | `"xrpld-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 `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**: `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 window1h_; // events in last 1 hour std::deque 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 | | ------------------ | ------------------- | ------ | ------------------------------------------------- | | `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 | | -------------- | -------------------------- | ------ | ------------------------------------------ | | `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., "xrpld-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 | | ---------------- | -------------------- | ------ | ----------------------------------------- | | `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 | | ---------------- | ------------------------------- | ------ | ------------------------------------------------ | | `state_tracking` | `state_value` | int64 | 0-7 numeric encoding matching external dashboard | | | `time_in_current_state_seconds` | double | `now - lastModeChangeTime` | **State value encoding**: xrpld'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 | | ---------------- | --------------- | ----- | ---------------------------------------- | | `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 | | ----------------------------- | -------------------------------- | --------------------- | | `ledgers_closed_total` | `onAccept()` in consensus | RCLConsensus.cpp | | `validations_sent_total` | `validate()` in consensus | RCLConsensus.cpp | | `validations_checked_total` | Network validation received | LedgerMaster.cpp | | `validation_agreements_total` | ValidationTracker reconciliation | ValidationTracker.cpp | | `validation_missed_total` | ValidationTracker reconciliation | ValidationTracker.cpp | | `state_changes_total` | `setMode()` in NetworkOPs | NetworkOPs.cpp | | `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 | | ---------------------- | ------------------- | ------ | --------------------------- | | `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: `validator-health.json` | Panel | Type | PromQL | | -------------------------- | ---------- | -------------------------------------------------------- | | Agreement % (1h) | stat | `validation_agreement{metric="agreement_pct_1h"}` | | Agreement % (24h) | stat | `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(validations_sent_total[5m]) * 60` | | Validations Checked Rate | stat | `rate(validations_checked_total[5m]) * 60` | | Amendment Blocked | stat | `validator_health{metric="amendment_blocked"}` | | UNL Expiry (days) | stat | `validator_health{metric="unl_expiry_days"}` | | Validation Quorum | stat | `validator_health{metric="validation_quorum"}` | | State Value Timeline | timeseries | `state_tracking{metric="state_value"}` | | Time in Current State | stat | `state_tracking{metric="time_in_current_state_seconds"}` | | State Changes Rate | stat | `rate(state_changes_total[1h])` | | Ledgers Closed Rate | stat | `rate(ledgers_closed_total[5m]) * 60` | **Dashboard conventions**: `$node` template variable for `service_instance_id` filtering, dark theme, matching existing panel sizes and color schemes. --- **Task 9.12: Peer Quality Dashboard** New Grafana dashboard: `peer-quality.json` | Panel | Type | PromQL | | ---------------------- | ---------- | -------------------------------------------------------- | | P90 Peer Latency | timeseries | `peer_quality{metric="peer_latency_p90_ms"}` | | Insane/Diverged Peers | stat | `peer_quality{metric="peers_insane_count"}` | | Higher Version Peers % | stat | `peer_quality{metric="peers_higher_version_pct"}` | | Upgrade Recommended | stat | `peer_quality{metric="upgrade_recommended"}` | | Resource Disconnects | timeseries | `overlay_peer_disconnects_charges` | | Inbound vs Outbound | bargauge | `peer_finder_active_inbound_peers`, `..._outbound_peers` | --- **Task 9.13: Ledger Economy Dashboard Panels** Add a "Ledger Economy" row to the existing `node-health.json` dashboard: | Panel | Type | PromQL | | -------------------- | ---------- | --------------------------------------------- | | Base Fee (drops) | stat | `ledger_economy{metric="base_fee_xrp"}` | | Reserve Base (drops) | stat | `ledger_economy{metric="reserve_base_xrp"}` | | Reserve Inc (drops) | stat | `ledger_economy{metric="reserve_inc_xrp"}` | | Ledger Age | stat | `ledger_economy{metric="ledger_age_seconds"}` | | Transaction Rate | timeseries | `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 | | -------------------------------------------------- | | `validation_agreement{metric="agreement_pct_1h"}` | | `validation_agreement{metric="agreement_pct_24h"}` | | `validator_health{metric="amendment_blocked"}` | | `validator_health{metric="unl_expiry_days"}` | | `peer_quality{metric="peer_latency_p90_ms"}` | | `peer_quality{metric="peers_insane_count"}` | | `ledger_economy{metric="base_fee_xrp"}` | | `ledger_economy{metric="transaction_rate"}` | | `state_tracking{metric="state_value"}` | | `ledgers_closed_total` | | `validations_sent_total` | | `state_changes_total` | | `storage_detail{metric="nudb_bytes"}` | **New dashboard load checks (~3)**: | Dashboard | | ----------------------- | | `validator-health` | | `peer-quality` | | `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% | `validation_agreement{metric="agreement_pct_24h"} < 90` | 30s | | Not Proposing | `state_tracking{metric="state_value"} < 6` | 10s | | Unhealthy State | `state_tracking{metric="state_value"} < 4` | 10s | | Amendment Blocked | `validator_health{metric="amendment_blocked"} == 1` | 1m | | UNL Expiring | `validator_health{metric="unl_expiry_days"} < 14` | 1h | | High IO Latency | `histogram_quantile(0.95, ios_latency_bucket) > 50` | 1m | | High Load Factor | `load_factor_metrics{metric="load_factor"} > 1000` | 1m | | Peer Count Critical | `server_info{metric="peers"} < 5` | 1m | **Network Group** (3 rules, eval interval 10s): | Rule | Condition | For | | ------------------------- | ----------------------------------------------------------- | --- | | Peer Drop >10% | `delta(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(jq_trans_overflow_total[5m]) > 0` | 1m | | Upgrade Recommended | `peer_quality{metric="peers_higher_version_pct"} > 60` | 1m | | TX Rate Drop | Transaction rate dropped > 50% in 5m window | 5m | | Stale Ledger | `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. _Previous: [Configuration Reference](./05-configuration-reference.md)_ | _Next: [Observability Backends](./07-observability-backends.md)_ | _Back to: [Overview](./OpenTelemetryPlan.md)_