The eight panels added for the GetObject and job-queue metrics did not
follow the conventions the rest of the dashboards use.
- Descriptions go from seven sections to the ten used by the other 159
panels, adding Keywords, Computation boundary and References. The
existing diagnostic guidance is kept; only the format changed.
- Six glossary entries added for the terms those References link to
(concurrency limit, deferred job, handler label, NodeStore lookup
hit/miss, resource charge), so no link is dead.
- displayName becomes `${series} ${xrpl_ident}`, the form 122 of 143
panels use. This needs the label_join wrapper that builds xrpl_ident,
which these queries lacked, so it is added to ten targets; without it
the legend would render an unresolved label.
- Legend blocks now match each dashboard's own convention rather than
being split three-with and four-without across the new panels.
Job Queue Wait Time and Job Execution Time dropped job_type from their
aggregation, so every queue collapsed into one line and the legend could
not say which queue was slow. Both now split by type, capped with topk
to stay readable, matching the per-type panel already on that dashboard.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Resolved five files. In each case both sides had content worth keeping,
so nothing was taken wholesale:
- MetricsRegistry.cpp: kept the incoming `handler` label on the job
instruments and re-applied this branch's `queuedDurUs >= 0` guard,
which the incoming side does not have.
- telemetry-runbook.md: took the incoming gauge table, which adds the
three per-job-type rows, and re-applied this branch's corrected
`jobq_job_count` name.
- 09-data-collection-reference.md: kept this branch's validation
inventory (newer counts, extra Config File column) and inserted the
incoming call-site and per-job-type gauge rows plus their explanation.
- node-health.json: merged structurally rather than by text. This
branch's panels are authoritative; only the two incoming job-queue
panels were appended, below the existing layout. The
`Validated Ledger Seq` panels added directly in Grafana are preserved.
- job-queue.json, ledger-data-sync.json: panel sets were identical, so
took the incoming side for its `$handler` variable, the handler filter
on existing queries, and the new panels. Verified no panel was lost.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Slowness on the peer object-fetch path could be observed but not
attributed. Job duration metrics carry only `job_type`, and both
`RcvGetLedger` and `RcvGetObjByHash` report as `ledgerRequest`, so a
queue-wait spike could not be traced to a handler. Nothing measured
NodeStore cost, request size, or the differential charge.
Latency now decomposes into three additive parts, each separately
measurable:
end-to-end = queue wait + NodeStore lookup + everything else
- `handler` label on job_queued_total/_started_total/_finished_total and
job_queued_us/job_running_us. The value is sanitised: a name passes
through only if non-empty and all ASCII letters, else "other". Two job
names embed a ledger sequence, so a raw label would mint one series
per ledger; the rule bounds the domain at 43 names plus "other".
- getobject_lookup_us, _request_objects, _lookups_total{result},
_rejected_total{reason} and _charge, recorded at their call sites.
All three histograms get explicit bucket views: the SDK default stops
at 10,000, which every one of them exceeds.
- Per-job-type waiting/running/deferred gauges for the 35 non-special
job types. `deferred` is the leading indicator, since addJob never
rejects -- it defers, so backpressure otherwise shows up only as
latency after the fact.
`JobQueue::collect()` snapshots the counters under the queue lock and
publishes gauges after releasing it. Writing them while holding the lock
would invert a lock order against the collector's own lock, which the
collector's flush thread already holds when it calls this hook.
Tests assert exact values, including that the charge is priced on the
requested count rather than the capped iteration count.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Add current_ledger_seq / current_ledger_hash to the tx.process, tx.receive,
and txq.enqueue span-reference rows, correct the txq.enqueue parent note
(parents to tx.process on the submission path via explicit context; a root on
the open-ledger rebuild path), and add a "Correlating a transaction to the
ledger it was worked on" recipe joining the txID-keyed tx/txq spans to the
ledger trace via current_ledger_seq.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Add a "Protocol Span Flow" section to the telemetry operator runbook: 8
Mermaid diagrams that map every OTel span onto the real xrpld control flow
and XRPL protocol order (verified against code and docs/consensus.md), for
use as the canonical key when linking the span hierarchy.
- Master overview, client/peer ingress, shared apply pipeline, consensus
round, accept/build/finalize, and pathfinding/ledger-acquire side flows.
- Every node/branch is labelled with the span that represents that state or
transition (or explicit "(no span)"); drops/abandons are marked terminal.
- Shows real loops, retries, recovery, and drop branches: multi-round
consensus settling (avalanche threshold rounds + MovedOn/Expired retry with
wrong-ledger recovery), 3-pass tx apply retry, TxQ cross-ledger retry,
quorum-gated async validation with abandoned-ledger, ingress backpressure
drops, and cross-node context propagation.
- Adds a divergence table noting where OTel span parenting does not match the
real protocol flow (deterministic/hash trace-id roots, JtAccept/JtUpdatePf
job hand-offs, sequential peer->consensus receive stages).
Replace the stale planning-era diagram in OpenTelemetryPlan/08-appendix.md
(which named spans that were never built) with a pointer to the runbook.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The check-rename CI gate requires all prose/comment references to use the
new naming. Fix the four remaining occurrences ("Ripple epoch",
"rippled's doAccept") introduced by this branch's dashboard/glossary
commits. Comment- and doc-only; no behavior change.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
P95 of second-scale spans was a meaningless interpolation. The spanmetrics
histogram topped out at [.. 1s, 5s], so consensus.round (~3.9s) and
consensus.establish (~1.9s) all fell into one 1s-5s bucket and
histogram_quantile interpolated linearly across that 4s-wide gap — the
"Build vs Close" / "Ledger Close Duration" panels' P95 read ~4800ms purely
as an artifact (verified: sum/count avg = 3824ms). ledger.acquire was worse:
~17% of samples exceeded the 5s ceiling, so its p95/p99 were unmeasurable.
Add 2s, 3s, 4s (resolve the 1-5s pile-up) and 10s, 30s (give the
ledger.acquire catch-up tail a measurable home). All ten existing boundaries
are preserved and the list stays strictly ascending (the connector
binary-searches buckets and silently misbuckets otherwise). Pin unit=ms so a
future collector default-unit flip can't rename the metric to _seconds.
Buckets chosen from the live mainnet distribution, not guessed. Native
beast::insight histograms (ms-scale RPC/IO timers in Telemetry.cpp) are 100%
under 5s, so they keep the original buckets — this is collector-only.
Applies on collector restart (cumulative series reset once, handled by
rate()). Runbook and regression-threshold bucket notes updated to match.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Add a scope tag to every panel keyword — (per node), (network-wide),
(network event), or (cluster-wide) — so a reader can tell whether a term
describes this server's own state, a protocol-shared fact, or a
network-wide consensus process the node participates in. Add a matching
'Scope:' line to each glossary entry.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Add a Keywords definition-list and a References link line to 178 Grafana
panel descriptions across all 14 dashboards, defining the XRPL/rippled
domain terms each panel uses (tiers 1-9: ledger, consensus, transaction
pipeline, fees/queue, node state, peer/overlay, storage, validator,
RPC/pathfinding). Cross-cutting chart terms and job-queue internals are
intentionally excluded.
Add docs/telemetry-glossary.md (86 terms, 9 categories) as the deeper
reference, linked from each panel's References line and from the runbook.
Keywords are injected only where a term appears in that panel's prose
(matched over description text, not source-file citations).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The "Ledger Close Duration" panel measured the consensus.ledger_close span
duration, which only wraps the sub-millisecond onClose() prologue — not the
ledger close. Repoint it to the consensus.round span (full round, open to
accept) so it reflects actual close time (~3-5s on mainnet). The consensus_mode
filter is preserved (consensus.round carries that attribute, verified live).
The sibling rate panels (Consensus Mode Over Time, Accept vs Close Rate,
Validation vs Close Rate) keep using consensus.ledger_close: a rate of that
span is a valid per-close event counter, only its duration was wrong.
Runbook updated to match.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The "ledger close time" was mis-derived and partly un-queryable:
- Build vs Close Duration derived close time from the consensus.ledger_close
span, which only wraps the onClose() prologue (~0.8ms live) — not the close.
Repoint the close series to consensus.round (full round, live P95 ~4.8s).
- The network close-time value (close_time) lived only as a span attribute,
un-queryable in Prometheus and unfit as a spanmetrics label (monotonic
timestamp -> unbounded cardinality). Expose it as last_close_time on the
existing server_info observable gauge (native gauge, no new instrument).
- Add a "Ledger Close Interval & Age" panel to ledger-operations and
node-health: interval = 1/rate(ledgers_closed_total) (counter-based,
scrape-independent); age = time() - (last_close_time + epoch_offset).
A gauge delta is deliberately NOT used for the interval — a timestamp gauge's
delta aliases to the scrape period, not the close cadence (verified live).
Guardrail comments in both collector configs record why close_time must never
become a spanmetrics dimension. Docs (09-reference) and the operator runbook
updated to match.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
These inbound peer-message entry points (kConsumer) used span(), which
inherits whatever span is active on the peer thread — including a leaked
tx.receive scope — so validations/proposals were wrongly nested under
unrelated transaction traces. rootSpan() starts a fresh trace root.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
detached() strips the thread-local OTel Scope so a guard can be safely
moved to and destroyed on another thread; it pops the Scope on the origin
thread and moves the span into a scope-less guard. rootSpan() starts a span
as a fresh trace root (kIsRootSpanKey) so inbound entry points never inherit
an ambient span left active on the thread.
Impl now holds an optional<Scope> (nullopt for detached guards). Updated the
SpanGuard class docs and docs/build/telemetry.md with the cross-thread rules.
The unit test lands on phase2 where the telemetry test module exists.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Document the three perf-iac filter template variables (xrpl_work_item,
xrpl_branch, xrpl_node_role) in the telemetry runbook and the data-collection
reference: what they filter, their example values, and that perf-iac stamps
them as resource attributes from its own alloy pipeline (absent outside
perf comparison runs, so the filters default to All). Also record perf as a
network value.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Dashboard audit against the live datasource surfaced two broken panel queries
and applied UX polish across all 14 dashboards.
- node-health "Job Queue Depth": job_count -> jobq_job_count. The JobQueue
collector is wrapped in group("jobq") (Application.cpp), so the registered
job_count gauge is emitted with the jobq_ prefix; the panel queried the
unprefixed name and returned nothing.
- network-traffic "Overlay Traffic by Category" + "All Traffic Categories":
topk(N, rate({__name__=~".*_bytes_in"}[...])) errors on Mimir ("vector
cannot contain metrics with the same labelset") because rate() drops
__name__ and the many counters collapse. Replaced with an enumerated
label_replace form that re-attaches __name__ per metric, preserving the
{{__name__}} legend and per-series display-name overrides.
- All 14 dashboards: refresh set to 10s.
- peer-quality: each panel full screen width.
- validator-health: at most two panels per row (row headers preserved).
- docs: telemetry-runbook and 06-implementation-phases updated for the
jobq_ prefix and the network-traffic query pattern.
Verified end-to-end against a local mainnet xrpld node feeding the local
stack: jobq_job_count returns data (old job_count empty), both network-traffic
exprs execute (old form reproduces the labelset error), and panels render
through the Grafana proxy. All 14 pass validate_dashboards.py.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Replace the TxQ Accept Status piechart on the Transaction Overview
dashboard with a state-timeline showing each node's applied fraction of
TxQ accepts (applied / applied+failed) over time, colored by threshold
(green >=0.9, yellow >=0.7, red below). Remove the now-orphaned
txq_status template variable (the piechart was its only consumer) and
document the panel in the telemetry runbook.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The spanmetrics connector had no namespace, so it emitted traces_span_metrics_*
metric names by default. The span dashboards and docs are renamed to query
span_* names; this is only correct if the connector emits them too, so add
namespace: "span" to the spanmetrics connector. Both sides change together:
renaming the dashboards without the namespace (or vice versa) would break the
pipeline. Matches the phase9 collector config.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The phase7 OTelCollector::formatName lowercases and strips names, emitting
snake_case metrics with no xrpld_ prefix. The native Grafana dashboards and
the telemetry docs still queried the old xrpld_CamelCase names, so they were
broken against their own pipeline. Rename every metric name to match what the
code emits: drop the xrpld_ prefix and lowercase the remainder. The two job
histograms also drop the redundant 'duration' word (job_queued_us,
job_running_us) to match the phase9 forms. Add havetxset to the cspell
dictionary since the lowercased metric name no longer word-splits.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
