makeTelemetrySetup() rejects a contradictory [telemetry] mutual-TLS
setup by throwing, but it is called from ApplicationImp's
member-initializer list. A try/catch in the constructor body cannot
reach a throw from there, and nothing further up the stack caught it
either, so a config mistake reached std::terminate: the default handler
printed a terminate dump and raised SIGABRT, leaving a core file
instead of a startup error.
Catch std::exception around makeApplication() in run(), report the
reason on stderr and return -1, so the failure is a clean non-zero exit
with a message an operator can act on. Only the construction is
wrapped. setup() starts subsystems whose shutdown order is delicate and
is left outside deliberately, because unwinding a half-started
Application would skip the normal stop sequence.
Gate both validation guards on enabled. A node with telemetry switched
off previously refused to start over certificate paths that nothing
would read.
Document both throws on makeTelemetrySetup(), state in
cfg/xrpld-example.cfg and the configuration reference that a partial
mutual-TLS setup is fatal and that the checks apply only when
enabled=1, and add a runbook troubleshooting entry keyed on the two
error messages.
Tests cover both guards with the message asserted so the two are told
apart, both enabled=0 paths, and the default plaintext configuration.
The transitions panel used increase(...[$__rate_interval]). $__rate_interval is
defined as max($__interval + scrape, 4 * scrape), i.e. deliberately one scrape
longer than the step so rate() windows overlap and lose no counter increase.
That overlap is harmless for rate(), but this panel reads the value as a count
of discrete events, and the overlap counts each event in more than one bucket.
Measured against a log-derived ground truth of 106 syncing transitions on
devnet-otel-usw2-01 over 2026-08-11T11:05Z..2026-08-12T23:04Z, the old query
reported 111.3 at a 300s step and 133.7 at a 60s step -- the error grew to +26%
as you zoomed in, because the overlap is a larger fraction of a smaller step.
Switch to $__interval so the buckets tile exactly, and wrap in round() because
increase() extrapolates to the window edges and so reports fractional counts for
an integer counter. The same measurement now gives 106 at 300s, 105 at 60s and
107 at 900s. Every state and both nodes land within a few counts of truth at any
zoom, and the legend Total is now a meaningful figure.
Pin Min step to 1m: the real scrape interval is 60s while the datasource
declares 15s, so without a floor $__interval can fall below one sample.
Draw as bars with 0 decimals -- the value is a discrete count per bucket, and a
line implies interpolation between counts that does not exist.
The Operating Mode Transitions panel queried state_accounting_*_transitions
directly. Those are monotonic counters, so the panel drew a slowly rising line
and a few transitions per hour were invisible against a total in the hundreds.
It also fell off a cliff whenever xrpld restarted and the counters reset to 0,
which reads as missing data rather than a restart.
Wrap each target in increase(...[$__rate_interval]) so each point is the number
of transitions in that bucket and the series survives a counter reset. This is
what the sibling panels on the same row (Operating Mode (Time Share), State
Duration Rate) already do.
Verified against devnet-otel-usw2-01/02 over 2026-08-11T11:01Z..2026-08-12T16:23Z:
the fixed expression reports 107 and 123 syncing transitions, matching the
counter deltas, and stays continuous across the 12:07 restart where the raw
counter dropped 630 -> 1.
Brief mode flaps remain invisible on Operating Mode (State Timeline) because a
~2 s dwell cannot be captured by a 60 s scrape; this panel is the place to read
them.
The troubleshooting step queried `job_count`, which returns no series. The
gauge is registered as `makeGauge("job_count")` but `Application.cpp` passes
`collectorManager_->group("jobq")`, so the exported name carries the `jobq`
segment. The two metric tables in this file were corrected when phase-6
merged forward; this example was missed because it sits outside the tables.
Conflict resolution kept this branch's evolution and re-applied phase-6's
fixes on top of it, rather than taking either side wholesale:
- consensus-health.json: kept the native `span_calls_total` metric name and
the `interval: 15s` and point styling from this branch; added phase-6's
`close_time_correct` PromQL filter and the NetClock axis labels. The
TraceQL boolean-regex filter stays removed and the `byRegexp` overrides
carry over. Panel count unchanged at 27.
- 09-data-collection-reference.md: kept this branch's headings, its more
detailed consensus attribute table (which already types
`consensus_round_id` as int64) and its section numbering, including the
deliberate removal of the SpanNames inventory. Carried over only the
correction that the state-accounting duration gauges are cumulative
microseconds, not seconds.
- telemetry-runbook.md: kept this branch's native metric names
(`span_calls_total`, `span_duration_milliseconds_bucket`); carried the
`rpc.request` -> `rpc.http_request` span-name fix and the `jobq_` segment
on the job-queue depth metric.
- integration-test.sh: kept this branch's `check_otel_metric` form and
carried the `jobq_job_count` correction.
The integration test asserted `rippled_job_count`, which never reports any
series, so that check always failed. `JobQueue` registers the gauge as
`makeGauge("job_count")`, but `Application.cpp` passes it
`collectorManager_->group("jobq")`, so the emitted StatsD name is
`jobq.job_count` and the exported Prometheus name is
`<prefix>_jobq_job_count`.
Corrected the same name in two runbook tables that also dropped the `jobq`
segment. `09-data-collection-reference.md` already had it right, which is why
the two documents disagreed.
Routed here rather than to the phase-10 PR where it was reported: the wrong
name is present in `integration-test.sh` on every branch from phase 6
onward, and this is the branch that introduces the file.
Left alone deliberately:
- `statsd-node-health.json` still queries the old name, but that dashboard is
deleted at phase 7 in favour of `node-health.json`
- `06-implementation-phases.md` names `job_count`, which is accurate as the
code-level makeGauge argument rather than the exported metric name
The integration test's span assertions never actually ran. check_span()
built a Tempo /api/search call with --data-urlencode but no -G, so curl
POSTed the params as a body; Tempo answers 200 and ignores the query, so
every span name looked present. Verified against a live Tempo 2.9.4: the
buggy form returns the store's total trace count for any name, including
"zzz.does.not.exist"; with -G a real name returns 1 and a bogus one 0.
Fixed alongside it: the RPC check asserted "rpc.request", which is never
emitted (ServerHandler.cpp builds "rpc.http_request"). These two had to
change together, since -G turns the bogus name from a silent pass into a
hard failure.
Also in the script: a consensus timeout logged two failures and counted
two, because a post-loop else re-reported what the timeout branch had
already reported; and three unguarded curl calls aborted the whole script
under set -euo pipefail, making the ACCOUNT_ZERO fallback dead code with
no cleanup. Guarded the curls and wired an EXIT trap to the existing
cleanup(). The trap deliberately fires only before the summary, so a
completed run still leaves the stack up as the header documents.
Docs corrections, all re-derived from code:
- span inventory heading 35 -> 38, attribute heading 83 -> 89 rows
(78 unique keys), and the section 6 header table now carries the
missing TxApplySpanNames.h row so its columns sum to the same figures
- two stale paths: ConsensusSpanNames.h is under include/xrpl/consensus/,
TxSpanNames.h under src/xrpld/telemetry/
- consensus_round_id is int64, not string (RCLConsensus.cpp sets
prevLgr.seq() + 1); the runbook's TraceQL examples now use a numeric
literal instead of an unparseable bare <round_id>
- state-accounting duration gauges are cumulative MICROSECONDS, not
seconds (NetworkOPs.cpp declares std::chrono::microseconds and
publishes dur.count() raw)
- sampling_ratio is not a config key; head sampling is fixed at 1.0 and
the shipped collector has no tail sampling, so the caveat was rewritten
- the plan blurb referenced Jaeger; this stack is Tempo
The four job-latency panels on node-health declared milliseconds while
querying `job_running_us` / `job_queued_us`, which record microseconds
(MetricsRegistry records the raw value, and the instrument description
says microseconds). Every reading was therefore a thousand times too
large: the p95 for acceptLedger, 241495us, rendered as "241 sec"
instead of 241ms. job-queue.json already read these same metrics as
microseconds, so the two dashboards disagreed by 1000x on identical
data. Switch node-health to microseconds to match.
Also replace the generic `ops` and `cps` units, which Grafana renders
as the literal "ops/s" and "counts/s", with custom-suffix units naming
what each panel counts -- messages, fetches, calls, mismatches.
Two panels plot more than one quantity on a single axis, which no
single unit can describe. Give each series its own unit through field
overrides: reads per second beside two queue depths on NuDB Read
Pressure, and ledgers beside fetches on Ledger Close Rate, the latter
on a right-hand axis.
State Duration Rate plots a seconds-per-second time share, which can
exceed 1.0 and so is not a percentage; label it as the ratio it is.
The normalised share already exists as its own panel.
Queries are unchanged; the values were already correct.
Alongside, bring the touched panels up to the dashboard guidelines and
hoist the stat panels above the fold.
Grafana renders `unit: "ops"` as the literal string "ops/s", so every
rate panel read as "operations per second" regardless of what it
actually counted. `Ledger Build Rate` showed "0.258 ops/s" where the
value is one ledger every 3.9s -- the number was right, the unit was
meaningless.
Replace the generic units with Grafana custom-suffix units naming the
quantity, following the existing `suffix:/hr` and `si:drops` precedent
in this repo. Nine of these are `stat` panels with no axis, so the unit
string was the only text a reader ever saw.
Also switch the two trusted/untrusted piecharts and the transaction
path piechart from rate() to increase(): a per-slice "per second"
reading is not a share of a total, counts in the window are.
Queries are unchanged apart from those three; the values were already
correct.
Alongside, bring the touched panels up to the dashboard guidelines:
tooltip mode/sort/max-height, 30-minute null spanning, and axis labels
in title case. Hoist the stat panels above the fold on
ledger-operations and rpc-performance.
Panels that a later branch in this chain removes are deliberately left
alone -- fixing them would only add merge conflicts.
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>
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>
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>
