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.
beast::insight::Event documents itself as carrying "a millisecond time, or
other integral value", but both backends assumed the first case: the OTel
bridge declared every instrument with unit `ms` and StatsD tagged every
sample `|ms`. One Event does not measure time -- ServerHandler's "size"
records the serialized RPC response length -- so it exported as
rpc_size_milliseconds and inherited the millisecond bucket ladder. A quarter
of its samples landed above that ladder's top edge, and since Prometheus
returns the second-highest edge for a quantile in the `+Inf` bucket, its p95
panel showed a flat 5.00 kB rather than a measurement.
Adds beast::insight::Unit (Millis, Bytes) plus otelUnitCode(), carried on
EventImpl and selectable at makeEvent(). Naming the unit at creation is what
lets a backend pick the export unit and, through it, the bucket ladder.
- Collector gains a virtual makeEvent(name, Unit) whose default delegates to
the millisecond overload, so a collector that cannot act on a unit keeps
working unchanged. NullCollector and the Groups wrapper override it.
- The Groups override matters most: call sites reach a collector through a
Group, so forwarding only the prefixed name would silently drop the unit.
A test covers that hop specifically.
- Event gains notify(std::uint64_t) for non-duration samples, replacing
ServerHandler's `Event::value_type{response.size()}` -- wrapping a byte
count in a std::chrono::milliseconds compiles but reads as a duration to
everything downstream.
- EventImpl::value_type stays std::chrono::milliseconds. Widening it would
change the wire value of every existing StatsD timer, and metrics needing
finer resolution use the OTel-native microsecond instruments.
The StatsD collector deliberately keeps emitting `|ms`: that path is retired
here (its UDP port is commented out of the compose file and the integration
test fails if anything listens on 8125), so changing its wire format would
alter a legacy contract with no consumer and no way to verify it.
The exported name does not change yet -- OTelEventImpl still hardcodes its
unit. That follows with the unit-keyed histogram views.
The bucket edges for the OTel histograms lived as file-local `namespace {}`
constants, unreachable from any test, and they drifted from the collector's
spanmetrics ladder they were specified to match. The millisecond ladder
stayed capped at 5 s after the collector side was extended to 30 s, so any
quantile above 5 s read back as a flat 5000 -- Prometheus returns the
second-highest edge for a quantile in the `+Inf` bucket, which looks like a
measurement rather than an error.
Adds include/xrpl/telemetry/HistogramBuckets.h as the single owner of the
ladders, with a constexpr validator plus static_asserts so a descending or
duplicated edge cannot compile, and gtest coverage that pins the floor and
ceiling against the measured distributions:
- kMillisecondBuckets carries every representable collector edge and extends
to 120 s, because the updatepaths job type averages ~60 s and a 30 s
ceiling would censor it exactly as 5 s does today. Sub-millisecond
collector edges are omitted: beast::insight::Event rounds durations up to
whole milliseconds, so they would collect nothing.
- kByteBuckets is new, for Events whose samples are sizes rather than
durations. Edges follow the measured RPC response distribution (mean
2131 B, half under 1 kB, tail mean bounded at 7538 B) rather than a guess,
so the resolution sits between 512 B and 64 kB.
No behaviour change yet -- nothing consumes the header until the views are
rewired.
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.
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.
clang-tidy runs misc-include-cleaner with WarningsAsErrors, so a symbol
reached only transitively fails CI. Add the direct includes for JLOG,
beast::Journal, StartUpType, TokenType, toBase58, std::exception and
std::size_t.
JLOG is defined in xrpl/basics/Log.h, and libxrpl.beast cannot include
xrpl.basics -- basics depends on beast, not the reverse. Use the journal
stream idiom the rest of the file already uses.
detachCallbacks() flips a flag that each observable callback checks on entry,
which leaves a callback already past that check running while the twelve
service stops below it tear down the state it reads. Stop the provider at the
same point instead: that joins the reader thread, so once it returns no
callback is running and none can start. Metrics recorded during the remaining
shutdown steps are no longer exported, which is the cost of the guarantee.
Build metricsRegistry_ in the member-init list rather than assigning it in
setup(). getMetricsRegistry() is read from the job queue and io threads, which
are running by then, so the later assignment was an unsynchronised write to the
handle those reads follow.
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.
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.
develop moved TempDir from beast:: to xrpl::, deleting
include/xrpl/beast/utility/temp_dir.h in favour of
include/xrpl/basics/FileUtilities.h. The merge kept this branch's
references to the old API, so the tree no longer compiled: the missing
header is a fatal include, and because DatabaseConfig_test.cpp lands in
the xrpld unity blob it broke the xrpld target itself, not just the tests.
Swap the include and drop the stale beast:: qualifier on 17 uses. The
three src/tests/libxrpl/nodestore files already include FileUtilities.h
and already spell TempDir unqualified elsewhere, so only the qualifier
was wrong there. DatabaseConfig_test.cpp needed the include as well; it
sits in namespace xrpl::node_store, so unqualified TempDir resolves to
xrpl::TempDir through the enclosing namespace.
Two further uses exist only on the sync-diagnostics tip and are fixed
there rather than here.
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.
