Every existing rule in this checker runs one way: take a consumer -- a collector
dimension, a Tempo tag, a dashboard label, a doc, an asserted metric name -- and
require it to resolve to the *SpanNames.h constants. Rule H looks closest to the
reverse but is still consumer-side: a constant USED at a call site that no header
defines. Nothing looked the other way.
So deleting a setAttribute from a .cpp and leaving its constant in the header
passed every rule and every compiler, while the telemetry it described stopped
being emitted. The workload validation job would eventually notice, but only when
it happens to run, and its path filter deliberately does not watch daemon .cpp
files -- widening it to 1827 C++ files to catch this would fire a twenty-minute
Docker job on nearly every commit.
Rule M closes that: an L1 constant no code under src/ or include/ references. It
searches all references, not just telemetry call sites, because constants are
passed to helpers, stored in locals and used as attribute VALUES -- a
call-site-only scan would report false positives. Constants referenced only by
test code are reported separately, since a constant exercised by a test but by no
production path is still dead in production.
A WARNING, not a failure, for two reasons that are both real here. Six constants
in this tree are already dead, so failing would redden the branch immediately. And
in a stacked chain a constant legitimately lands one commit before its call site,
so a failing rule would break intermediate branches for a condition that resolves
downstream.
What it reports today, all verified unreferenced across the whole repository and
not just src/include: ConsensusSpanNames.h val::increased, val::decreased and
val::unchanged; SpanNames.h seg::link, attr_val::success and attr_val::error.
Placed here rather than upstream on phase-1c, where the checker was introduced,
because the gap it closes is a workload-harness concern -- the contract asserting
a name nothing emits -- and the harness is this branch's. Putting it on 1c would
also mean union-resolving a 1900-line file across ten merge hops, each an
opportunity to silently drop the metric rules that live downstream.
Ported from a patch written against the sync-diagnostics copy, which carries the
metric-side rules I/J/K/L that this branch does not. The rule itself is purely
span-side; the only shared dependency it needed was iter_sources, which arrived
with those metric rules, so that helper is added here on its own. The rule-L
docstring entry and README row that came with the patch context were dropped --
this branch has no rule L.
Verification: rule M reports 262 constants checked and 6 unreferenced, exit code
still 0 because warnings do not change it; 169 unittest cases pass; the checker
compiles; no metric-rule content leaked in from the patch context (0 occurrences
of METRIC_MACRO_CALL or run_rule_i_metric_literals). Proven non-vacuous by
blanking all three call sites of attr::rpcStatus -- the count went 6 to 7 and
named that constant -- then restoring them and watching it return to 6.
An empty metric surface counted as a complete capture. build_query_plan
returns an empty plan without complaining for any config that yields no
gated keys, so pointing --metrics at the wrong file exits 0 and hands the
paste-me path a metrics:{} artifact to offer as the next baseline. Nothing
about such a run is evidence the pipeline works, so declared == 0 is now a
failure rather than vacuously complete.
The bounds checker also raised AttributeError on a baseline entry that is
not an object, instead of naming the key. A validator whose job is to catch
a malformed contract should report it, not crash on it.
Test cleanup is bound to its own temp tree, so a loop no longer leaves five
of six directories behind.
Refreshes baselines/baseline-timings.json from run 32964262700 at 8418d474a7,
byte-identical to the CI artifact. The previous baseline was captured at
6a82fc6f37, before the path-finding load was removed from the workload, so it
described a load shape the harness no longer runs.
Every absolute bound is re-derived, because the rule is hi_next minus baseline
and the baselines moved.
Three more keys stop being gated: span.tx.apply.p50, span.ledger.build.p50 and
span.consensus.ledger_close.p50. This is the rule the previous commit recorded
being applied, not a new exception -- a key is gateable only when its
run-to-run spread fits inside its bound.
The evidence is span.tx.apply.p50, which read 0.7917 ms in the old baseline and
0.00597 ms in this one. That is a 132x move between two runs of the SAME
workload. The old value happened to land mid-distribution, so hi_next minus
baseline gave a 4.21 ms bound that absorbed the spread; the new value lands in
the ladder's first bucket, so the same rule gives 0.0440 ms and cannot survive
one. Whether the gate functioned was decided by where in the distribution the
captured run happened to fall, which is not a threshold in need of tuning.
Measured spreads across four runs agree: 364x, 25.3x and 5.9x respectively.
All five excluded keys share one shape -- a baseline landing in the ladder's
low buckets, where the derived bound is tiny, together with large run-to-run
spread. Single-run baselines cannot support them; a multi-run baseline, or a
spread measurement captured alongside the baseline, is what would let them be
gated again. Not attempted here.
Both runs that would have reddened CI now replay clean, and an injected 10x
regression is still caught on 19 of the 20 remaining keys, 20 of 20 at 20x.
The exception is job.acceptLedger.running.p95, whose baseline fell while its
hi_next did not, moving its floor to 16.28x. It stays gated with that floor
recorded beside the other weak keys.
Also makes the bounds checker report a zero or negative baseline as a named
rule failure instead of dividing by it and raising.
The regression gate has been red on runs with no code change. Only two of
the 25 gated keys ever tripped, both on the same span and never together:
run 32862589645 failed p99 at 25.8750 ms against a 1.0600 ms baseline
(+2341%), run 32867433073 failed p95 at 0.7500 ms against 0.2404 ms
(+212%), and in each run the other quantile sat well inside its own bound.
A real slowdown would move both. This is variance, not a defect.
Measured across four CI runs:
span.ledger.validate.p50 0.0484 to 0.0778 ms 1.6x spread kept
span.ledger.validate.p95 0.1281 to 0.7500 ms 5.9x spread excluded
span.ledger.validate.p99 0.3875 to 25.8750 ms 66.8x spread excluded
Both excluded quantiles reach past their trip point on a healthy run. The
mechanism is arrival timing, not slow code: the span opens only once a
quorum-completing validation arrives (LedgerMaster.cpp:987, inside
checkAccept, past the early return) and wraps the promotion work that
follows, so one slow consensus round dominates the tail of a 3m rate
window and which round that is differs every run.
Widening is not available and must not be attempted later: tolerating
25.8750 ms against a 1.0600 ms baseline needs a bound of about 24.8 ms,
which gates nothing. A bound admitting every healthy run's worst case
admits every regression too. p50 stays gated; it is stable.
THE GENERAL RULE, recorded so this does not recur: an absolute bound
derived as hi_next minus baseline comes from the histogram ladder, so it
budgets for quantization noise and for nothing else. It knows nothing about
how far a metric moves between runs on identical code. Before gating any
key, check its observed maximum across several runs against its trip point
and gate it only with margin. Spread alone proves nothing: tx.apply.p50
swings 364x and never fires, because its 5 ms trip point absorbs the range.
Of the 23 keys still gated the worst reaches 0.67 of its trip point.
Mechanism: spans.names lists span names while _quantiles is shared, so
dropping two quantiles of one span cannot be expressed by deleting a name.
regression-metrics.json gains an excluded_keys map from a flat key to the
reason it is not gated, subtracted by both prom_queries.py (so the key is
never queried) and check_regression_bounds.py rule A. A per-name quantile
override was rejected: a typo there leaves the key gating, whereas a typo
in an exclusion subtracts nothing and new rule F rejects it, along with an
empty reason, a leftover threshold override and a leftover baseline value.
Derived figures recomputed from the committed baseline: 25 gated keys to
23, detection floor 2.02x-9.43x to 2.02x-9.42x, weakly guarded keys ten to
nine, bound over baseline 102%-843% to 102%-842%. The baseline edit is a
deletion of two entries only, with no value rewritten.
Verified: both previously failing runs replay to zero regressions and exit
0; a tenfold increase injected into each of the 23 remaining keys in turn
is still caught in all 23 cases; rule F was confirmed load-bearing by
stubbing it out, which lets a stale exclusion pass.
The gate could not catch a regression on any sub-millisecond span.
compare_to_baseline.py requires both the percentage and the absolute bound to
breach, and every span shared one flat absolute bound of 10 ms (15 ms for p99)
calibrated for a 5-25 ms band the spans do not occupy. Against the baseline
captured on 2026-08-24, where 18 of the 28 quantiles gated at the time sat
below 1 ms, that bound sat 1.15x to 2000x above the metric it guarded, so the
AND never fired: a 100x regression injected into span.ledger.store.p95 reported
0 regressions and exit 0. Injecting a 10x regression into each key in turn was
caught on only 5 of 28.
Give every gated key its own absolute bound, equal to the distance from its
baseline to hi_next, the edge above the top of the bucket the baseline sits in.
The trip point is then exactly hi_next, so the gate fires only once the reading
clears the bucket above the baseline's own. That is the property a multiple of
the enclosing bucket width cannot provide: after the quantile crosses hi, the
interpolation happens across the next bucket, which on this ladder is up to
eight times wider, so no multiple of the enclosing width bounds the excursion.
Measured with a model-free reachability test, a single bucket crossing can
produce a false regression on 2 of 25 keys under the old flat bound and 0 of 25
under this rule. The smallest catchable regression is 2.02x to 9.43x per key.
The job queue bound had the same shape of problem on three of its four keys
(42x, 47x, 220x before). Defaults now sit at each ladder floor, leaving the
percentage bound operative for a metric that somehow reaches them.
Drop span.ledger.store from the gated surface. Its captured quantiles were
0.005, 0.0095 and 0.0099 ms, which is the ladder's 0.01 ms floor times the
quantile: every sample lands under 10 us, so the reported value does not move
even if each store slows from 2 us to 9 us. No bound can gate it. Presence is
still asserted by expected_spans.json and the integration test, and the rate is
still on the ledger-operations dashboard.
Add check_regression_bounds.py, wired into the same workflow step as the bucket
parity check. It fails when a bound is not the one its own baseline implies,
when a gated key has no override, when the baseline and metric surface disagree,
when the percentage bound would become operative, and when a baseline carries
the ladder floor signature. This gate has now broken three times through the
same drift between ladder, baseline and bounds, so documentation alone is not
enough.
compare_to_baseline.py is unchanged: its existing per-metric override mechanism
already expresses all of this.
A missing, unreadable or malformed input makes that check exit 1 naming the
input, rather than reporting success without having checked anything; only a
placeholder baseline, the documented bootstrap state, still exits 0. Its own
tests cover both halves of that contract plus one case per rule, and run in the
workflow before the check so a broken rule reads as a broken rule.
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.
check-otel-naming fails Rule D on this branch: ledger-data-sync.json
aggregates by xrpl_work_item, which nothing in-tree emits because
perf-iac's alloy pipeline stamps it, so it cannot be derived from
*SpanNames.h. The sibling perf-iac identities xrpl_branch and
xrpl_node_role are already allowlisted; this one was missed when the
by() clauses were reintroduced.
Add it to EXTERNAL_INFRA_LABELS alongside them. Verified by removing
the entry again, which restores the failure.
The integration-test sections, alert provisioning headers and a naming-check
test comment were indexed by rollout phase and task numbers defined only in
planning documents outside the shipped tree. Each now names what it covers.
The reference docs had drifted from the code in ways that break the reader
rather than merely misinform: PromQL examples that return no data, a rollback
flag that is a no-op, a sampling knob that does not exist, and two span parents
that moved. Code is treated as the truth throughout; where the code is the
defective side, the doc now records it as a known issue instead of describing
the bug as intent.
Renames the docs missed: histogram names gain the exporter's unit suffix
(ios_latency_milliseconds_bucket and four siblings), ledger_history_mismatch
gains _total, the StatsD-era quantile label gives way to le buckets,
rpc.request becomes rpc.http_request, traces_spanmetrics_calls_total becomes
span_calls_total, and the nine dotted xrpl.* span attributes are recorded as
renamed rather than left as live keys.
Re-parenting: consensus.update_positions and consensus.check are children of
consensus.establish, not of consensus.round.
Units and labels: state_accounting_*_duration is microseconds, not seconds;
cache_metrics label values are case-sensitive; object_count carries demangled
C++ type names. Nodestore read and write latency stays microseconds -- the
nanosecond accumulator change did not move the exported unit.
Adds what shipped but was undocumented: the ledger.acquire span, seven
consensus.round events, twelve span attributes, node_writes_duration_us, the
7-day validation-agreement window, the TxQ admission and reduce-relay metric
families, metrics_endpoint, and the phase-10 validation workflow.
Corrects claims that never held: 10% head sampling (it is fixed at 100%),
configurable redaction (it is unconditional), -DXRPL_ENABLE_TELEMETRY=OFF
(the flag is -Dtelemetry=OFF, default ON), FindOpenTelemetry.cmake and the
xrpl_telemetry target (neither exists), Promtail and a StatsD exporter in the
pipeline (neither exists), and Loki stream selection on job= (only
service_name is a stream label).
Phase 9 is marked complete, its provisioned alerting is attributed to the
branch that shipped it, and Phase 11 stays at zero except the one prerequisite
its code closes. Counts are reconciled repo-wide: 41 emitted span families,
15 dashboards on disk with 14 asserted, 13 alert rules in 5 groups.
Hardens the gate that let this drift through: Rule E of the naming check now
covers the reference docs, its allow-dotted marker is key-scoped and warns on
stale or empty use, a missing checked file is reported instead of silently
skipped, the test suite runs in CI, and doc paths trigger the check.
C++ and CMake changes are comment-only: three MetricsRegistry instrument names,
eight OTelCollector claims of a metric-name prefix that formatName never adds,
and the telemetry option's inverted default.
* upstream/release/3.3.x: (41 commits)
chore: Bump version to 3.3.0
chore: Bump version to 3.3.0-rc7
fix: Increase manifest protocol message size cap and fix manifests relay
fix: Cap untrusted manifests per message and drop oversized ones
chore: Bump version to 3.2.1
chore: Bump version to 3.2.1-rc1
fix: Cap untrusted manifests per message and drop oversized ones
fix: Reject oversized validator manifest before decoding
fix: Reduce untrusted manifest cache cap to 100
fix: Bound untrusted manifest cache
chore: Bump version to 3.3.0-rc6
feat: Package validator-keys inside rippled
chore: Bump version to 3.3.0-rc5
fix: Switch SponsorshipSet to use a delta for sfFeeAmount
fix: Re-revert "fix: Set request size limits and differential pricing for get-object-by-hash calls"
chore: Bump version to 3.3.0-rc4
fix: Revert "fix: Set request size limits and differential pricing for get-object-by-hash calls"
chore: Bump version to 3.3.0-rc3
fix: Reduce untrusted manifest cache cap to 100
fix: Revert "fix: Reject oversized SHAMap nodes in gotStaleData and fetch-pack path"
...
Rule D validated every dashboard label against L1 (*SpanNames.h) and L6
(MetricsRegistry) labels. LogQL labels have a third provenance neither
layer can resolve: they are minted by the collector's regex_parser named
captures (partition, severity) or by an in-query `| regexp` stage
(action, pk, state, mode, phase, jobname, ip, pubkey). Checking them
against L1/L6 reported ten violations for labels correct by
construction.
Make the rule datasource-aware instead of allowlisting a filename. The
dashboard JSON is parsed so each query can be attributed to its
datasource, and queries on a log datasource are skipped. The exemption is
per query, not per file, so a dashboard mixing Prometheus and Loki panels
still has its Prometheus panels validated.
Parsing the JSON also fixed a blind spot: label filters are stored with
backslash-escaped quotes (`label=~\"$v\"`), which the previous raw-text
regex could never match, so only the `sum by (...)` form was ever
checked. With the strings unescaped, 555 queries are now validated where
far fewer were before. That surfaced three legitimate label sources the
rule did not model, each fixed at its source rather than allowlisted:
- deployment_environment / xrpl_network_type: resource attributes the
collector promotes onto metric datapoints. Derived from the config's
resource_metrics_key_attributes, so a new key is picked up
automatically, in both dotted and underscore forms.
- resource.service.instance.id: strips to a dotted service-identity
key, which builtins only held in underscore form.
- name: the TraceQL span-name intrinsic, alongside duration and kind.
A file that does not parse falls back to the raw-text scan, which checks
every query rather than skipping it; JSON validity is already enforced by
the prettier pre-commit hook.
Adds 10 tests: the exemption, per-query scoping in a mixed dashboard,
target-inherits-panel datasource, no sideways inheritance leak, nested
row panels, TraceQL intrinsics, the malformed-JSON fallback, and the
collector-promotion helper.
These changes were developed on the phase-10 branch but belong to content this
branch and its upstreams introduced. Carrying them on phase-10 made its PR diff
report churn in files phase-10 does not own, and left each PR claiming a scope
that did not match its contents.
Moved here from phase-10 (identical content, no functional change):
- Dashboards: all 14 existing boards plus the new log-derived-insights board.
- Docs: telemetry-runbook.md (minus the workload/benchmark sections, which
describe phase-10 tooling) and the new telemetry-glossary.md.
- Grafana Cloud + Alloy export path: collector config, compose override, the
two .env examples and alloy/config.alloy.
- Local stack: otel-collector-config.yaml gains sub-millisecond and
second-scale spanmetrics buckets, pins unit=ms, and promotes
close_time_correct; integration-test.sh and TESTING.md follow.
- Node configs: exported_instance -> service_instance_id in comments; the
mainnet sample now logs at warning to bound log volume.
- Metrics code: Telemetry.cpp builds the metrics pipeline in the constructor
via initMetrics() so the global MeterProvider is published before any
subsystem creates a beast::insight instrument, and the histogram view keeps
each instrument's own name instead of collapsing them under one series.
MetricsRegistry gains a last_close_time gauge and skips negative job-queue
durations. OTelCollector drops an unused accessor.
- Naming CI: xrpl_work_item joins EXTERNAL_INFRA_LABELS and Rule E accepts the
dotted perf-iac resource-attribute form. This must travel with the
dashboards and runbook that reference those labels, or the rules fail.
- Doxygen input glob no longer recurses dot-directories.
Sections describing phase-10 tooling stay on phase-10 and keep their
"Future Enhancement" / "Planned, not yet implemented" markers here; phase-10
removes those markers when it lands the tooling.
The 22 metric label values on the nodestore_state gauge were asserted
nowhere, and the depthSum assertions could not tell the real
fetch_add(depth) from a fetch_add(1) that would silently zero every
derived queueing time.
Make the four observe* helpers and their ObserveFn sink public rather
than private, so the seam the header already claimed is actually
reachable. All four are static and read only their arguments, so this
exposes no object state; a friend declaration would have granted access
to every private member instead. The assertions live in the existing
Beast nodestore suite because src/test compiles into xrpld, which
contains MetricsRegistry.cpp, while xrpl_tests deliberately does not
when telemetry is enabled.
Each helper now has its exact emitted label set asserted, so a typo in
any literal fails instead of silently producing a disjoint series, and
each derived mean is asserted ABSENT on a fresh store -- a refactor to
value_or(0) would draw a believable flat zero on a latency axis and
otherwise pass everything.
Replace the concurrent write-stats test with one that forces genuine
overlap through a latch. NuDB holds one global mutex for the whole
insert and doInsert reads the depth before entering it, so a blocked
thread records a depth of at least 2; asserting depthSum strictly
exceeds insertCount therefore cannot be satisfied by a constant 1. The
old bounds admitted that bug at their floor.
Also: cover the std::nullopt branch on the two backends that exist in
every build, bound the store-duration accumulator by the wall clock,
drop four assertions that cannot fail, and correct two comments that
claimed coverage the tests do not have -- the duplicate-key test is not
the throwing path, because nudb reports key_exists without throwing,
and no test drives NodeStoreScheduler::onFetch.
- JobQueue_test: drop the unused <functional>, and make the two
read-only GaugeFixture instances const. The other two stay mutable
because they submit jobs through fixture.queue.
- DatabaseConfig_test: drop the unused SystemParameters.h and include
ByteUtilities.h for megabytes(), which was reached only transitively.
Regenerate ordering.txt for the resulting edges: test.unit_test arrives
with SuiteJournal.h, and xrpl.protocol leaves with SystemParameters.h.
Rule D rejected the `handler` and `result` dashboard filters even though
both labels are emitted, because the L6 extractor missed them twice over:
- It matched only a key written as an inline literal directly after `{{`.
A label map is a braced list of braced pairs, so in
`Add(1, {{"job_type", a}, {"handler", b}})` only the first key follows
`{{` -- every later one was dropped. A key hoisted into a constant
(`{{kHandlerLabel, v}}`) was invisible in any position.
- It walked *.cpp only, so a constant declared in a header, as
kLabelResult is, could never be found.
Match the label map first and scan its pairs, resolve `k...Label`
constants through their `constexpr char k...[] = "..."` definitions, and
read headers too. Matching the map rather than any `{"key",` in the file
keeps ordinary brace initializers, such as the `{"http", "https"}` scheme
array, out of the label set -- they are not labels and must not license a
dashboard filter. Test code is skipped for the same reason Rule F skips
it: fixtures pass arbitrary literal pairs.
A saturated ledgerData lane makes TimeoutCounter re-arm its timer
without running the timer body, so timeouts_ never advances and the
six-timeout give-up can never fire. Acquisitions then neither finish
nor fail until the one-minute sweep destroys their partial maps, and
the work restarts. Every step of that chain was debug-log-only, so a
node at warning level could not be diagnosed after the fact.
The counters are separate on purpose: deferrals rising while timeouts
stay flat is the signature, and no single counter shows it.
Completions are recorded in done() rather than at the "Done: complete"
log line, because that line also fires for failures and misses the
checkLocal and receiveNode paths; done() is the one funnel every
outcome passes through and its signaled_ guard makes it idempotent.
AcquireStats is only forward-declared in ServiceRegistry so libxrpl
still includes nothing from xrpld. The src/ include path for the test
binary moves out of the telemetry guard, since a header-only type
under src/xrpld/ is testable in every build.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
The consensus headers moved into the isolated xrpl/consensus module and
took a dependency on xrpl/telemetry for the tracing span constants, but
two things were left behind:
- Four includes still pointed at the old src/xrpld/consensus/ location,
which no longer exists, so the build failed with
"fatal error: 'xrpld/consensus/ConsensusParms.h' file not found".
- xrpl.libxrpl.consensus never linked xrpl.libxrpl.telemetry. add_module
isolates each module's headers, so xrpl/telemetry/SpanNames.h was not
on the include path even once the include was repointed.
Repoint the stale includes at xrpl/consensus/, and declare the telemetry
module before consensus so consensus can link it. Regenerate ordering.txt
for the resulting edge.
