The microsecond ladder's first edge was 100us, which sat ABOVE the mass of
every instrument using it. Measured on devnet: 99.3% of job_queued_us
samples, 92.5% of job_running_us and 90.4% of getobject_lookup_us fell in
that first bucket. histogram_quantile then interpolated inside bucket 0 and
returned `quantile / fraction_in_bucket_0 x first_edge` -- p75/p95/p99 of
job_queued_us read 75.52/95.66/99.69us against a prediction of
75.53/95.67/99.70. Three-decimal agreement: those panels were reporting
arithmetic on the bucket edge, not latency.
The fix was already half-written. kSubMillisecondBoundaries had been parked
in MetricsRegistry.cpp as [[maybe_unused]] with a comment noting exactly this
problem for nodestore reads. Its edges are now folded into kMicrosecondBuckets
rather than deleted, so the parked intent is carried forward: 1..1000us
resolution where the mass is, upper edges unchanged so multi-second stalls
stay measurable.
Also moves the GetObject count and charge ladders into HistogramBuckets.h, so
all five ladders have one owner and one set of invariant tests (29 now).
Adds check_bucket_parity.py, wired into the existing OTel naming workflow.
The C++ millisecond ladder and the collector's spanmetrics ladder are
specified to agree over their shared range; they were identical when shipped,
then the collector side alone was extended and nothing noticed for eleven
phases. The check asserts containment rather than equality, because jobs
outlive spans -- jobq_updatepaths averages ~60s, which no span approaches, so
demanding equality would force a ceiling that censors it. Verified it rejects
a missing collector edge, a bogus in-range edge, and a return to the 5s
ceiling.
ledger-data-sync's "Job Queue Wait p95 By Type" moves off the beast
jobq_*_q_milliseconds pair onto job_queued_us filtered by job_type. Those
beast metrics are ms-quantised at the source (Event rounds up to a whole
millisecond), so 94-100% of their samples sat in the first bucket and no
ladder change could fix them. Note the label values are camelCase
(job_type="ledgerData"), not the lowercase metric-name fragments.
Both histogram-fed alert thresholds re-validated and left unchanged, with the
measured basis recorded so neither gets tuned against the old artefact: only
0.0022% of job_queued_us samples exceed the 1s threshold, and every edge
bracketing the 1000ms ios_latency threshold survived the ladder change.
Docs: the rpc_size "known issue -- tracked separately" notes in the runbook
and 09-data-collection-reference are now resolved notes, the stale 10-edge
span_duration bucket list is corrected to the collector's real 20, and the
runbook gains a "Reading A Histogram Percentile" section covering both
saturation traps and the expected discontinuity after a ladder change.
This is the change that actually lifts the 5 s ceiling. Until now the
millisecond ladder and the Unit type existed but nothing consumed them.
Telemetry.cpp registered ONE histogram view: instrument name pattern "*",
unit exactly "ms", boundaries {1, 5, ..., 1000, 5000}. Verified against the
installed SDK, "*" matches every name and "ms" matches exactly, so that view
governed every beast::insight Event -- all 54 of them, whatever they measure.
Measured on devnet: 24.9% of rpc_size samples and 100% of jobq_updatepaths
samples fell above 5000. A quantile landing in the `+Inf` bucket reads back
as the second-highest edge, so those p95s reported a flat 5000 rather than a
measurement, and the 1 s to 5 s span was a single four-second-wide bucket
that any quantile inside it had to interpolate across.
Replaces it with one view per unit, keyed on the unit an instrument declares:
- `ms` gets kMillisecondBuckets: every representable edge of the collector's
spanmetrics ladder, plus 60 s and 120 s. The extensions are deliberate --
jobq_updatepaths was measured averaging 59,956 ms, which no span
approaches, so parity alone would still censor it.
- `By` gets kByteBuckets, placed from the measured response distribution
(mean 2131 B, half under 1 kB, tail mean bounded at 7538 B).
OTelEventImpl now derives its declared unit AND its description from unit()
instead of hardcoding "Duration in ms"/"ms", so rpc_size exports as
rpc_size_bytes on the byte ladder. rpc-pathfinding's "RPC Response Size"
panel follows the rename; its unit was already decbytes and is now truthful.
Also corrects Phase7_taskList.md, which still specified the 5000 ladder as
"matching SpanMetrics". That was true when written and became false when the
collector ladder was extended on its own -- implementing the plan as written
reproduced the bug, so the spec is where the defect had come to live. The
edges now have exactly one owner and the plan points at it.
Use `rgb(15, 122, 102)` instead of `rgb(25, 158, 112)`: the brighter step drew
too much attention for a background band.
This is the darkest teal that still separates from the JMeter grey by a readable
margin -- normal-vision dE 15.6 against a floor of 15, CVD dE 12.3 against a
target of 8, and at least 3:1 on the dark surface. Dimmer steps fail: rgb(25,
100, 90) lands at dE 9.5, and a grey-derived rgb(25, 70, 70) at dE 5.8, which is
indistinguishable from the JMeter grey even with full colour vision.
Both checks selected on {job="xrpld"}. Loki's OTLP ingestion promotes
service.name to the label `service_name` and keeps a `job` attribute as
structured metadata, which a stream selector cannot match, so the selector
returned zero streams whatever had been ingested. The collector config and
TESTING.md already say to select on `service_name`.
Invert the cross-reference. Picking an arbitrary trace from Tempo and
expecting it in Loki fails even when correlation works, because a log line
carries a trace_id only when emitted inside a sampled span and most spans
log nothing at `warning` level. Start from a logged trace_id instead and
resolve it in Tempo, which is the invariant worth asserting, and try every
id found so one unexported trace does not fail the check.
Bound the log queries in time. Nothing here set start/end, so every query
relied on Loki's one-hour default and returned nothing when re-run later to
investigate a result.
The driver split changed the existing perf-run regions from grey to violet,
which was not asked for. Restore `rgb(70, 70, 70)` on `Perf Runs (JMeter)` so
every region that rendered before keeps its colour; `Perf Runs (Locust)` stays
aqua, since it is new.
Grey separates from aqua well (dE 22.8 deutan, 25.9 tritan, 26.1 normal), but it
sits at 1.98:1 against the dark-theme surface, below the 3:1 floor, so its region
edges read faint there. Noted in the runbook.
A single "Annotate perf-iac runs" layer matched only `perf-iac`, so a Locust
load window was indistinguishable from a JMeter one. perf-iac now tags every
region with its load driver, so each driver can have its own layer and colour.
- Replace that layer with `Perf Runs (JMeter)` and `Perf Runs (Locust)`, each
matching ["perf-iac", "<driver>"] with matchAny:false, on 12 dashboards.
- job-queue, ledger-data-sync and log-derived-insights had an empty annotations
list and drew no perf regions at all; they now carry the builtIn layer plus
both driver layers.
- Grafana tag matching is a superset AND with no negation, so a generic
`perf-iac` layer also matches every driver region. Keeping one alongside the
driver layers would draw each load window twice, so it is replaced, not kept.
- Document the layers in the telemetry runbook, including two rendering limits:
annotations draw only on timeseries, state-timeline and candlestick panels,
and the shaded fill is 10% opacity so the region edges carry the colour.
- Add `jmeter` to the cspell dictionary; the hook rejects the bare word.
beast::insight instruments are created during ApplicationImp's member-init
list, and opentelemetry-cpp 1.28 never rebinds an already-vended Meter, so an
instrument created before the MeterProvider is published records nothing for
the rest of the process. Observable instruments carry the opposite constraint:
registering one arms the SDK reader thread, and its callbacks run hook handlers
that read services which do not exist that early.
Publish the provider in Telemetry's constructor, ahead of every producer, and
defer only the observables. Collector gains onCollectionReady() and
onCollectionStopping(); OTelCollector arms and disarms its gauges in response.
StatsDCollector starts its polling thread in its own constructor and had the
same hazard, so it uses the pair to gate that thread.
The metrics resource carries service.instance.id and is immutable once built,
so the node public key is resolved in Main.cpp, where a config error can still
be reported, and passed to makeApplication(). getNodeIdentity() remains
authoritative; both paths now share readNodeIdentity(), so telemetry cannot
report a key the node has abandoned.
An explicit ~ApplicationImp stops observing and stops telemetry, covering the
setup() failure paths that never reach run(). Telemetry::stop() is once-only
and no longer clears another instance's global pointer. The histogram view's
meter selector now matches the meter actually in use, so its bucket boundaries
apply for the first time.
Node identity reached the OTel resource only as service.instance.id, which is
config-overridable and carries a deployment-chosen label rather than the node's
own identity. Add xrpl.node.id, set unconditionally from the node public key
(base58, TokenType::NodePublic), so traces and metrics share a stable per-node
key independent of [telemetry] service_instance_id.
Set on the tracer resource via Telemetry::setNodeId(), called from
ApplicationImp::setup() once nodeIdentity_ is known, and on the MetricsRegistry
resource via an added start() parameter. The beast::insight meter provider is
built in TelemetryImpl's constructor, before the wallet DB exists, so its
resource cannot carry the value; that path is left for later and the attribute
is omitted rather than stamped blank.
Also drops the transform/spanidentity collector processor added in
4a361a496d: per-node identity belongs on the resource, not copied onto every
span.
Consensus spans share one deterministic, ledger-derived trace_id, so a
single trace holds spans from every node and the resource-level node id is
not a reliable per-span discriminator in stored traces.
Add transform/spanidentity to both collector configs, copying
service.instance.id onto every span as service_instance_id so TraceQL can
filter per node with the same value the $node dashboard variable already
uses on the metrics side. Wired into the traces pipeline locally and into
traces/store (after tail_sampling) on the Grafana Cloud variant.
The transitions panel used increase(...[$__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.
This branch had already made the same corrections independently, and in
richer form, so the resolution keeps this branch's version nearly throughout:
- 09-data-collection-reference.md: this branch already documents the
state-accounting gauges as cumulative **microseconds** with an explanatory
callout, and already names `jobq_job_count` with its `jobq` group. Kept.
- telemetry-runbook.md: already carries `jobq_job_count` in both tables. Kept,
along with this branch's larger additions.
- OpenTelemetryPlan.md: kept this branch's rewritten section 9 blurb, which
describes the inventory without hardcoding counts and so cannot drift.
- consensus-health.json: kept this branch's rewrite. It deliberately removed
the four TraceQL close-time detail panels and renamed the agreement panel;
the incoming side would have resurrected them. Panel count unchanged at 26.
- integration-test.sh: this branch's unprefixed native metric names were kept,
but it still asserted `job_count`, so the `jobq_job_count` correction was
carried over. That check would otherwise always fail.
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 file_storage extension was added to otel-collector-config.yaml, which
every stack mounts. That made the extension mandatory: the collector image
runs as 10001:10001 and ships no writable directory, so any stack without a
prepared volume would fail to start rather than merely lose offsets. The
workload-validation stack mounts this same config and has no such volume.
Offset persistence is only useful where logs outlive a restart. The workload
harness creates a fresh log directory per run, so it has nothing to resume
from. Move the extension, the receiver's storage reference and the extended
service.extensions list into otel-collector-filestorage.yaml, layered as a
second --config by the developer stack alone. The base config keeps
start_at: beginning, which is what actually fixes the reported defect, and
stays self-sufficient for every other stack.
Verified against the pinned collector image: the base config validates and
runs on its own with no volume mounted and still ingests a line written
before startup; base plus overlay validates, preserves the base receiver's
operators through the merge, and re-ingests that line zero times on a second
run against the same volume.
Conflict resolutions:
- docker/telemetry/xrpld-telemetry.cfg: relocation conflict. phase-9 had
already moved [insight] to the end of the file with server=otel, so the
incoming block was dropped rather than inserted. Keeping both would have
produced two [insight] sections, which merge last-wins into a single
effective section, silently reviving the bug this branch just fixed.
phase-9's per-branch service_instance_id=xrpld-devnet is preserved.
- OpenTelemetryPlan/06-implementation-phases.md: kept both corrections.
phase-9's "Tempo" is right (no Jaeger anywhere in the stack) and
phase-8's "active, sampled span" is right: Log.cpp:328 injects only
when spanCtx.IsValid() && spanCtx.IsSampled().
- OpenTelemetryPlan/09-data-collection-reference.md and
docs/telemetry-runbook.md: kept phase-9's structured-metadata LogQL.
The collector's filelog regex_parser already extracts partition,
severity, trace_id and span_id, so phase-8's inline regexp forms are
redundant, and a line filter matches the literal text in a message body.
The generated node config carried two [insight] blocks. Duplicate ini
sections do not replace one another: parseIniFile emplaces the section
name (a no-op when it already exists) and appends the lines to the same
vector, then Section::append writes each key with insert_or_assign. The
effective section was therefore server=statsd with the first block's
endpoint and service_instance_id surviving but unused.
CollectorManager selects StatsDCollector for that value, so the nodes
emitted beast::insight metrics over UDP to 8125, which has no receiver
in the collector pipeline and no published port. The script's own check
asserts that 8125 is not listening, and its insight metric assertions
fail on zero series.
Keep only the server=otel block so the config matches what the script
verifies.
This branch removes the collector's StatsD receiver and un-publishes
8125/udp, but xrpld-telemetry.cfg still selected server=statsd, so the
sample config sent beast::insight metrics over UDP to a port nothing
listens on. Phase7_taskList.md:132 lists this switch as required work.
Select server=otel and replace address= with the OTLP metrics endpoint.
Document that endpoint and prefix are informational only, since
OTelCollector records on the global MeterProvider that [telemetry]
configures and formatName() applies no prefix, and note that beast
instruments are not exported yet because the collector is constructed
before the MeterProvider is registered.
Six findings from the review of #6494 survived independent verification.
Each was checked against the branch tip, and where behaviour was in
question, against a live collector and Loki rather than from the
reviewer's claim or from documentation alone.
Plan-doc section numbering. 06-implementation-phases.md used "## 6.9"
twice: for the new Phase 8 section and for the pre-existing Risk
Assessment. Three references already pointed at 6.8.1 and none at 6.9,
and the later phases are numbered 6.8.2 through 6.8.4, so Phase 8
becomes 6.8.1 and the sequence is monotonic. Renumbering to 6.10, as
suggested on the PR, would have collided with Success Metrics.
filelog read position. The receiver relied on the upstream default
start_at=end, which skips everything a node wrote before the first poll
and reads nothing at all from a log that has stopped being written to.
Read from the beginning instead, paired with a file_storage extension so
a restart resumes at the last offset rather than re-ingesting the file.
The collector image runs as 10001:10001 and ships no writable directory,
and a fresh named volume is root-owned, so a one-shot init service
prepares the volume first. It reuses an image the stack already pulls,
adding no new dependency.
Loki log stream label. The job resource attribute did not become a Loki
index label, so the documented {job="xrpld"} queries matched nothing.
Verified against grafana/loki:3.4.2 with its default config: only
service_name and deployment_environment are indexed, and job arrives as
structured metadata, which a stream selector cannot match. Dropped the
attribute and moved the twelve queries this branch introduced to
{service_name="xrpld"}. Three further occurrences in
07-observability-backends.md originate on the phase-1a branch and are
left for a commit there.
Trace ids on unsampled spans. Logs::format emitted trace_id and span_id
whenever the span context was valid. A span dropped by the
ParentBasedSampler still carries its parent's ids, so log lines
advertised traces that were never exported and the log-to-trace link
resolved to nothing. Require the sampled flag as well, and correct the
task list and the documentation that promised the fields unconditionally.
The remaining two findings were refuted. The reported risk of signing
material reaching Loki does not hold: Logs::format already scrubs seven
sensitive fields, and there is a single write path to the log file, so
every JLOG site is covered. The suggestion to add internalLink to the
Loki derived field is not applicable, because that key is not part of
Grafana's schema.
All five TraceQL panels on this dashboard returned nothing, and did so
without any visible error: they filtered on
span.close_time_correct=~"$close_time_correct", but close_time_correct is
a boolean attribute (RCLConsensus.cpp:601 passes a raw bool), and Tempo
restricts the regex operator to string operands, so the spanset resolved
to false. With the variable defaulting to All the clause rendered as
=~".*", so the panels were empty out of the box and looked exactly like a
node with no consensus activity.
Note this is the opposite of PromQL, where an absent or empty label does
match ".*" — which is why the 17 Prometheus panels on this same board were
unaffected and the dashboard appeared healthy.
Dropped the clause from all six queries, matching phases 9 and 10 where it
is already gone. The $close_time_correct variable now filters the
Prometheus "Close Time Agreement" panel instead, which already grouped by
that label but never filtered on it, so the control stays useful rather
than becoming dead UI.
Two defects were masked behind the empty panels and are fixed too:
- "Close Time: Raw Proposals" and "Close Time: Effective / Quantized"
carried unit dateTimeFromNow over close_time_self/close_time, which are
NetClock seconds (Ripple epoch), while Grafana's dateTime formatters
expect a millisecond Unix epoch — every point would have rendered as
roughly 1970. They now plot as plain numbers with the axis labelled
"NetClock Seconds (Ripple Epoch)", and the descriptions give the
946684800 offset for converting to Unix time.
- "Close Time Vote Bins & Resolution" matched its unit and axis overrides
byName against "Vote Bins" and "Resolution", which are not field names;
TraceQL select() yields close_time_vote_bins and close_resolution_ms, so
neither override applied. Switched to byRegexp so the match holds
whichever scope prefix Grafana emits.
No panel was added or removed: the (type, title) multiset is unchanged at
22. resolution_direction keeps its regex filter, which is correct there —
it is set from a std::string whose values are exactly the variable's
increased/decreased/unchanged.
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 setting was flagged in review as unauthenticated admin access. It is
deliberate, and it matches the sibling stack in docker-compose.yml, which
carries the same two variables and the same published port with its intent
in comments. This copy had none, so the reasoning lived only in a review
thread and was rediscovered as a finding each time the file was looked at.
Viewer would break the harness rather than harden it: the validation suite
drives the Grafana API against this instance to confirm each dashboard
provisions and loads, and the dashboards and datasources come from the
read-only mounts on the same service.
Two defects reported against the harness, both confirmed.
The TPS field was computed with `bc` at scale=2, and bc omits the leading
zero: it prints ".25", not "0.25". A bare ".25" is not valid JSON, and this
was the normal case rather than an edge case — ledgers close every few
seconds, so ledger-advance over elapsed-seconds is well under 1 for any
realistic window. It survived earlier checks because those piped the file
through jq, which accepts the malformed form; Python's json rejects the whole
file. awk's %.2f always pads, so the field is now produced with awk. Audited
the other numeric fields at the same time: CPU average and memory peak
already used awk, and the p99, sample count and consensus mean are integers,
so TPS was the only one affected.
Separately, a failing attribute fetch was reported under the span's own check
name, which had already recorded the trace as found. That produced two
entries for one name, one passing and one failing, inflating the check total
and blaming the trace-existence check for a failure in a later network call.
The fetch now carries its own error handling and reports under
`span.attrs.<span>`, matching where its successful counterpart reports. It
moved into a helper rather than growing `validate_spans`, which was already
well over the line limit.
Three consecutive validation runs timed out at Step 3 with nodes stuck at
"unreachable", and the reason was not recoverable from the logs. The node
logs showed the failing nodes stopping at an identical point, immediately
after JobQueue initialisation and before the debug log is opened, with no
error text at all. The harness knew each node's pid and never used it, so a
crashed node was indistinguishable from a slow one.
The readiness loop now checks whether each node process is still alive and
fails as soon as one is not, instead of waiting out the remaining window and
burying the cause under two minutes of progress output. Liveness is not a
bare `kill -0`: an exited-but-unreaped child keeps its pid, so a zombie
answers `kill -0` and reads as alive for the whole window, which is exactly
how a crashed node came to look like a slow one.
On failure each stopped node reports its wait status and the tail of its
stdout. The status is the discriminator that was missing: 137 for a SIGKILL,
139 for a segfault, 134 for an abort, anything below 128 for a deliberate
exit. stdout is printed inline rather than left to the artifact upload,
because a node that dies before its debug log opens writes nothing else and
a cancelled run uploads nothing at all.
This is instrumentation, not a fix. The failure is not attributable to the
recent changes on this branch: the first red run touched only the two Python
files used at Steps 4 and 5, both of which run after this gate, and the same
harness passed 5/5 twice before that.
Run with no arguments the script iterated an empty list, found no
violations and printed "OK: 0 dashboard(s) passed" with exit 0 -- a clean
bill of health for reading no files, indistinguishable from a real pass.
A bare run now defaults to every dashboard beside the script, and a run
that still ends up with nothing to check exits 2 rather than reporting
success. Passing paths explicitly behaves as before.
