NuDB serializes every insert behind one global mutex held for the whole
call, so a caller cannot see how long it waited. Record instead the
writer depth joined at and the wall time spent; with mean depth L and
mean insert time W, Little's Law gives service time W/L and queueing
W - W/L. That distinguishes a serialized write path from a saturated
disk: measured on a dev box the device sat 89 percent idle while
throughput stayed flat at 42k inserts per second.
The accounting runs from a ScopeExit guard because the insert can
allocate and therefore throw; leaking the depth would strand the gauge
above zero for the life of the process.
getWriteLoad also stops returning a hardcoded zero. It now reports
writer depth, which is bounded by the writing-thread count and so stays
far below the kMaxWriteLoadAcquire cutoff that gates history
acquisition, where returning bytes or microseconds would have silently
suppressed it.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
fetchDurationUs_ had no getter, so telemetry reached it by building a JSON
object, stringifying a uint64 and parsing it back with stoll on every
collect tick. storeDurationUs_ was declared and never written or read at
all, along with the jss::node_writes_duration_us key.
Both now have accessors, both production store paths time their backend
call, and the registry reads them without the round trip. get_counts also
reports the write duration, so the RPC and the metric agree. Mean read
latency is the signal that separates a cold store from a warm one: warm
reads are single-digit microseconds, cold ones low hundreds.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Both were uint32_t while every sibling counter was uint64_t. On a
multi-day node node_read_bytes read 1,481,244,491 for 1,894,924,394
reads, i.e. 0.8 bytes per read, which is impossible: the counter had
wrapped about 350 times. Read hit rate is used to tell a cold-read
stall from a write-lock ceiling, so a wrapping numerator makes that
diagnosis wrong rather than merely imprecise.
getFetchTotalCount() was already backed by a uint64_t member, so its
32-bit return type truncated a correct value at the accessor. All
three getters now return uint64_t.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Resolved OpenTelemetryPlan/09-data-collection-reference.md: both sides
document the same new metrics, reached by different routes. The incoming
sections came from the phase-6 edit merged forward; this branch already
documents the same surface in its own layout, with the job lifecycle
metrics and the GetObject request path under the MetricsRegistry
section rather than a separate 2a.
Kept this branch's sections to avoid duplicate entries for every metric.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Resolved OpenTelemetryPlan/09-data-collection-reference.md: this branch
replaced the StatsD-shaped Section 2 with OTel-native naming, so the
incoming StatsD tables and the StatsD per-job timer section do not apply
here. Kept this branch's names throughout.
The incoming per-job-type saturation gauge section is new content and is
retained, renumbered to 2.5 and rewritten for the OTel naming: bare
lowercase `jobq_<jobtype>_{waiting,running,deferred}` derived through
OTelCollector rather than the case-preserving `xrpld_`-prefixed StatsD
form.
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 reference entries for the observability surface introduced on
phase-9: the `handler` label on the job instruments, the five
`getobject_*` request metrics, and the per-job-type queue saturation
gauges.
Names here follow this branch's StatsD pipeline, which preserves case
and carries the `xrpld_` prefix, so they differ from the lowercased
OTel-native names used from phase-7 onward. The sections state where
the implementing code lives, since it is introduced downstream.
Also correct pre-existing entries: `job_count` exports as
`jobq_job_count` via the collector group prefix, the non-special job
type count is 35 (not 36), and `JtLedgerData` has five producers.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Match the panel height the operator settled on in Grafana (18 rows) so
all 20 ranked bars render without an inner scrollbar, and reflow the
Sync Diagnostics row and the panels below it accordingly.
The bar labels on 'Overlay Traffic Heatmap (All Categories, Bytes In)'
were raw metric names carrying a redundant '_bytes_in' suffix, and the
half-width 8-row panel truncated both the category and the node
identity.
- Strip the '_bytes_in' suffix from the derived series label; the panel
title already states the metric is inbound bytes.
- Widen the panel to full width and grow it to 12 rows so 20 bars render
with their full category and node labels.
- Shift the Sync Diagnostics row and the panels below it down by 4 to
keep the layout gap-free.
- Note the label derivation in the panel description.
The panel plotted only Full and Tracking, so the states a node actually
passes through while catching up were invisible. On the dev box's cold
sync the node spent ~19 minutes in Connected and ~3 seconds in Syncing,
while Tracking totalled 2 microseconds -- the one non-Full line the
panel did draw was the least informative of the five.
Add Syncing, Connected and Disconnected series (state-ladder order,
matching the Operating Mode Transitions panel) and rename the panel to
"State Duration Rate (All States)". Because the node is always in
exactly one state, the five rates sum to ~1.0, so the panel now reads as
"which state is time going into right now", and a handover between two
lines marks a state change with its width showing the dwell time.
Description expanded to the full section set (keywords, computation
boundary, references) used by the other panels on this dashboard.
Verified live: rate(state_accounting_connected_duration)/1e6 reaches
1.0 then 0.387 across the catch-up window and syncing reaches 0.0103 --
both previously undrawable.
The dashboard showed 54 individual signals but no single answer to
"is this node healthy and doing its job?". A reader had to correlate
server state, ledger age and peer counts by eye.
Add a stat panel at the top that reduces the two conditions that define
a healthy observer node to one green/red verdict:
server_state == 4 (Full) AND validated_ledger_age < 30s
Both terms use `== bool` so each yields 0/1, joined with
`* on(service_instance_id)` so the verdict is per node. Value mappings
render 1 as "Healthy" (green) and 0 as "Not Healthy" (red) with
background colouring, so the state is readable at a glance.
Placed at y=0 per the dashboard convention that gauges/stats lead;
existing panels shift down by 4 rows with no other change.
Verified live against Grafana Cloud: returns 1 for aws-dev-xrpl-1
(Full, validated seq 105,824,596).
The four aggregated Sync Diagnostics panels grouped by xrpl_work_item,
which no layer in this repo emits (it is injected by the perf-iac
harness). That tripped Rule D of the telemetry naming check:
D ledger-data-sync.json xrpl_work_item
must exist in L1, a metric label, or be a builtin
Align with the convention used by every other aggregated panel in the
dashboard set: group by (service_instance_id, xrpl_branch,
xrpl_node_role) and leave the xrpl_ident label_join untouched. The
legend is unaffected -- label_join over a label dropped by the
aggregation contributes an empty segment, which the trailing
label_replace already strips.
Verified live: both the NuDB ratio and the job-queue p95 queries still
return per-node series rendering as "[aws-dev-xrpl-1]".
The 0-4 values now render as named states via value mappings, so the numeric
axis label is misleading. Rename to "Server State".
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Add value mappings (0 Disconnected, 1 Connected, 2 Syncing, 3 Tracking,
4 Full) and matching red->green thresholds to the Sync State panel, so the
line, tooltip, and legend render state names and colors instead of bare 0-4.
Keeps the minimal custom-key convention; only the Sync State panel changes.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Rework the 10 Sync Diagnostics panels' legends to match the format used by the
existing panels: wrap each query in label_join + label_replace to build the
xrpl_ident label ([service_instance_id, xrpl_branch, xrpl_work_item] with empty
values stripped) and set displayName to "${series} ${xrpl_ident}". Verified
against a live node: renders as "Series [aws-dev-xrpl-1]" with no empty-label
gaps, identical mechanism to the original 15 panels. Only the new panels change.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Add a 10-panel "Sync Diagnostics" row that shows ledger-sync slowdown and its
causes, laid out top-to-bottom as symptom -> latency -> root cause:
- Red flags: Sync State, Validated Ledger Age, Ledger Close Rate
- Latency: Job Queue Wait p95 by type, NuDB Read Latency, I/O Scheduler p95
- Root cause: NuDB Cache Hit Ratio, NuDB Read Pressure, Job Queue Depth,
Load Factor & Peers
All panels use native beast::insight metrics introduced on this branch
(nodestore_state, ledgermaster_*, jobq_*_q, ios_latency, load_factor_metrics,
peer_finder_*) plus the consensus.mode_change span metric. Queries filter by
the dashboard's $node and tier variables and were verified against a live
node. Nodestore ratio panels use sum-by(identity) matching to bridge the
metric= sub-label.
Format matches the dashboard convention: minimal custom keys, ${DS_PROMETHEUS}
datasource uid, and the standard What/How/Reading/Healthy/Watch/Source/Function
description structure. Pure-append; existing panels untouched.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
