rippled/docs/telemetry-runbook.md

xrpld Telemetry Operator Runbook

Overview

xrpld supports OpenTelemetry distributed tracing to provide visibility into RPC requests, transaction processing, and consensus rounds.

This runbook covers operating a running node and querying its traces. For building xrpld with telemetry support and the internal architecture, see build/telemetry.md.

Quick Start

1. Start the observability stack

docker compose -f docker/telemetry/docker-compose.yml up -d

This starts:

• OTel Collector on ports 4317 (gRPC), 4318 (HTTP), and 13133 (health)
• Tempo trace storage on http://localhost:3200
• Grafana on http://localhost:3000 (Tempo pre-configured as datasource)

2. Enable telemetry in xrpld

Add to your xrpld.cfg:

[telemetry]
enabled=1
endpoint=http://localhost:4318/v1/traces

3. Build with telemetry support

conan install . --build=missing -o telemetry=True
cmake --preset default -Dtelemetry=ON
cmake --build --preset default

Configuration Reference

Option	Default	Description
enabled	0	Master switch for telemetry
endpoint	http://localhost:4318/v1/traces	OTLP/HTTP endpoint
service_name	xrpld	OpenTelemetry service name resource attribute
service_instance_id	node public key	OpenTelemetry service instance ID resource attribute
trace_rpc	1	Enable RPC request tracing
trace_transactions	1	Enable transaction tracing
trace_consensus	1	Enable consensus tracing
trace_peer	1	Enable peer message tracing (high volume)
trace_ledger	1	Enable ledger tracing
consensus_trace_strategy	deterministic	Consensus trace ID strategy (deterministic or random)
batch_size	512	Max spans per batch export
batch_delay_ms	5000	Delay between batch exports
max_queue_size	2048	Max spans queued before dropping
use_tls	0	Use TLS for exporter connection
tls_ca_cert	(empty)	Path to CA certificate bundle
tls_client_cert	(empty)	Client cert (PEM) for mutual TLS; empty = one-way TLS
tls_client_key	(empty)	Private key (PEM) for tls_client_cert

Span Reference

All spans instrumented in xrpld, grouped by subsystem:

RPC Spans (Phase 2)

Span Name	Source File	Attributes	Description
rpc.http_request	ServerHandler.cpp	request_payload_size	Top-level HTTP RPC request
rpc.ws_upgrade	ServerHandler.cpp	—	WebSocket upgrade handshake
rpc.ws_message	ServerHandler.cpp	command	WebSocket RPC message
rpc.process	ServerHandler.cpp	is_batch, batch_size	RPC processing (child of rpc.http_request/ws_message)
rpc.command.<name>	RPCHandler.cpp	command, version, rpc_role, rpc_status, load_type	Per-command span (e.g., rpc.command.server_info)

Transaction Spans (Phase 3)

Span Name	Source File	Attributes	Description
tx.process	NetworkOPs.cpp	tx_hash, local, path, tx_type, fee, sequence, ter_result, applied	Transaction submission and processing
tx.receive	PeerImp.cpp	peer_id, tx_hash, tx_type, peer_version, suppressed, tx_status	Transaction received from peer relay
tx.apply	BuildLedger.cpp	ledger_seq, tx_count, tx_failed	Transaction set applied per ledger
tx.preflight	applySteps.cpp	stage, tx_type, ter_result	Stateless checks stage
tx.preclaim	applySteps.cpp	stage, tx_type, ter_result	Ledger-aware checks stage
tx.transactor	Transactor.cpp	stage, tx_type, ter_result, applied	Apply stage (transactor runs)

The three apply-pipeline spans (tx.preflight, tx.preclaim, tx.transactor) share a deterministic trace_id from txID[0:16], so they group under one trace per transaction. The stage attribute (preflight / preclaim / apply) drives the collector spanmetrics stage dimension, giving per-stage RED metrics on the Transaction Overview dashboard.

Transaction Queue Spans (Phase 3)

Span Name	Source File	Attributes	Description
txq.enqueue	TxQ.cpp	tx_hash, tx_type	Transaction enqueue decision (child of tx.process)
txq.apply_direct	TxQ.cpp	--	Direct apply attempt (bypassing queue)
txq.batch_clear	TxQ.cpp	--	Batch clear of queued transactions for an account
txq.accept	TxQ.cpp	queue_size, ledger_changed	Ledger-close accept loop over queued transactions
txq.accept_tx	TxQ.cpp	tx_hash, retries_remaining, ter_code, txq_status	Per-transaction apply during accept
txq.cleanup	TxQ.cpp	ledger_seq	Post-close cleanup of expired queue entries

Consensus Spans (Phase 4)

Span Name	Source File	Attributes	Description
consensus.round	RCLConsensus.cpp	consensus_ledger_id, ledger_seq, consensus_mode, trace_strategy, consensus_round_id	Root span for a consensus round (deterministic or random trace ID)
consensus.phase.open	Consensus.h	--	Open phase duration (child of round)
consensus.proposal.send	RCLConsensus.cpp	consensus_round, is_bow_out	Consensus proposal broadcast
consensus.ledger_close	RCLConsensus.cpp	ledger_seq, consensus_mode	Ledger close event
consensus.establish	Consensus.h	converge_percent, establish_count, proposers	Establish phase duration (child of round)
consensus.update_positions	Consensus.h	converge_percent, proposers, disputes_count	Position update and dispute resolution (see Events below)
consensus.check	Consensus.h	agree_count, disagree_count, converge_percent, have_close_time_consensus, threshold_percent, consensus_result	Consensus threshold check
consensus.accept	RCLConsensus.cpp	proposers, round_time_ms, quorum, disputes_count, consensus_state	Ledger accepted by consensus
consensus.accept.apply	RCLConsensus.cpp	ledger_seq, close_time, close_time_correct, close_resolution_ms, consensus_state, proposing, round_time_ms, parent_close_time, close_time_self, close_time_vote_bins, resolution_direction, tx_count	Ledger application with close time details (see Events below)
consensus.validation.send	RCLConsensus.cpp	ledger_seq, proposing, ledger_hash, full_validation, validation_sign_time	Validation sent after accept (follows-from link)
consensus.mode_change	RCLConsensus.cpp	mode_old, mode_new	Consensus mode transition
consensus.proposal.receive	PeerImp.cpp	proposal_trusted, consensus_round	Proposal received from peer (extracts parent context from TraceContext when present; falls back to standalone span for older peers)
consensus.validation.receive	PeerImp.cpp	validation_trusted, ledger_seq	Validation received from peer (extracts parent context from TraceContext when present; falls back to standalone span for older peers)

Consensus Span Events

Parent Span	Event Name	Event Attributes	Description
consensus.update_positions	dispute.resolve	tx_id, dispute_our_vote, dispute_yays, dispute_nays	Emitted per dispute when votes are tallied
consensus.accept.apply	tx.included	tx_id	Emitted per transaction included in the accepted ledger

Close Time Queries (Tempo TraceQL)

# Find rounds where validators disagreed on close time
{name="consensus.accept.apply"} | close_time_correct = false

# Find consensus failures (moved_on)
{name="consensus.accept.apply"} | consensus_state = "moved_on"

# Find slow ledger applications (>5s)
{name="consensus.accept.apply"} | duration > 5s

# Find specific ledger's consensus details
{name="consensus.accept.apply"} | ledger_seq = 92345678

# Find all spans in a consensus round (deterministic trace strategy)
{name="consensus.round"} | consensus_round_id = <round_id>

# Find dispute resolutions
{name="consensus.update_positions"} >> {event:name="dispute.resolve"}

Ledger Spans (Phase 6)

Span Name	Source File	Attributes	Description
ledger.build	BuildLedger.cpp:31	ledger_seq, tx_count, tx_failed	Ledger build during consensus
ledger.validate	LedgerMaster.cpp:915	ledger_seq, validations	Ledger promoted to validated
ledger.store	LedgerMaster.cpp:409	ledger_seq	Ledger stored in history

Peer Spans (Phase 6)

Span Name	Source File	Attributes	Description
peer.proposal.receive	PeerImp.cpp:1667	peer_id, proposal_trusted	Proposal received from peer
peer.validation.receive	PeerImp.cpp:2264	peer_id, validation_trusted	Validation received from peer

---

Insights and Sample Queries

This section shows what questions you can answer using the span attributes, with example Tempo TraceQL queries.

Transaction Workflow Analysis

# Find all AMM transactions (AMMDeposit, AMMWithdraw, AMMCreate, etc.)
{name="tx.process"} | tx_type =~ "AMM.*"

# Find Payment transactions that failed
{name="tx.process"} | tx_type = "Payment" && ter_result != "tesSUCCESS"

# Compare latency of different transaction types
{name="tx.process"} | tx_type = "OfferCreate"
{name="tx.process"} | tx_type = "Payment"

# Find high-fee transactions (fee > 1 XRP = 1000000 drops)
{name="tx.process"} | fee > 1000000

# Find transactions that were not applied
{name="tx.process"} | applied = false

# Trace a specific transaction by type across the network
{name=~"tx\\..*"} | tx_type = "NFTokenMint"

Apply Pipeline by Stage

# All three stages of one transaction (preflight -> preclaim -> apply)
{name=~"tx.preflight|tx.preclaim|tx.transactor"}

# Transactions that failed at the preclaim stage
{name="tx.preclaim"} | ter_result != "tesSUCCESS"

# Transactions that hard-failed preflight (never reached preclaim/apply)
{name="tx.preflight"} | ter_result != "tesSUCCESS"

PromQL on the span-derived metrics (dashboard: Transaction Overview):

# Per-stage throughput — the funnel preflight >= preclaim >= apply
sum by (stage) (rate(traces_span_metrics_calls_total{span_name=~"tx.preflight|tx.preclaim|tx.transactor"}[5m]))

# Per-stage p95 latency
histogram_quantile(0.95, sum by (le, stage) (rate(traces_span_metrics_duration_milliseconds_bucket{span_name=~"tx.preflight|tx.preclaim|tx.transactor"}[5m])))

# Per-stage failure rate (ter_result != tesSUCCESS; a failing ter completes the
# span normally, so filter on the attribute, not status_code which only flags exceptions)
sum by (stage) (rate(traces_span_metrics_calls_total{span_name=~"tx.preflight|tx.preclaim|tx.transactor", ter_result!~"tesSUCCESS|"}[5m]))

Alerting: a rising tx.preflight / tx.preclaim failure rate points to malformed or stale-sequence submissions (often spam or a misbehaving client); a rising tx.transactor failure rate points to apply-time problems. Alert per stage rather than on a single aggregate so the failing stage is obvious.

Sampling caveat: these stage metrics are span-derived and inherit the tracer head-sampling ratio (sampling_ratio). At sampling_ratio < 1.0 they undercount proportionally — treat them as relative trends, not absolute transaction counts. Native StatsD metrics are unsampled.

Transaction Queue Health

# Find transactions rejected from the queue
{name="txq.accept_tx"} | txq_status = "failed"

# Which transaction types get queued most often?
{name="txq.enqueue"} | tx_type = "Payment"
{name="txq.enqueue"} | tx_type = "OfferCreate"

# Find ledger closes that applied queued transactions
{name="txq.accept"} | ledger_changed = true

# Find transactions that exhausted retries
{name="txq.accept_tx"} | txq_status = "retried" && retries_remaining = 0

RPC Debugging

# Find batch RPC requests
{name="rpc.process"} | is_batch = true

# Find large RPC payloads (>100KB)
{name="rpc.http_request"} | request_payload_size > 100000

# Find resource-heavy RPC commands (by load_type)
{name=~"rpc.command.*"} | load_type = "exceptioned RPC"

# Find a specific WebSocket command
{name="rpc.ws_message"} | command = "subscribe"

# Find slow pathfinding with many source assets
{name="pathfind.discover"} | pathfind_num_source_assets > 10

PathFinding Performance

# Find pathfinding for specific currencies
{name="pathfind.compute"} | pathfind_dest_currency = "USD"

# Find expensive pathfinding (many source assets to explore)
{name="pathfind.discover"} | pathfind_num_source_assets > 20

# Find large pathfinding requests
{name="pathfind.compute"} | duration > 1s

Consensus Health

# Find rounds where consensus timed out (expired)
{name="consensus.accept"} | consensus_state = "expired"

# Find rounds where we moved on without full agreement
{name="consensus.accept"} | consensus_state = "moved_on"

# Find rounds with many disputes
{name="consensus.accept"} | disputes_count > 5

# Find bow-out proposals (node resigned from round)
{name="consensus.proposal.send"} | is_bow_out = true

# Correlate validation with its ledger
{name="consensus.validation.send"} | ledger_hash = "<hash>"

# Find rounds where validators disagreed on close time
{name="consensus.accept.apply"} | close_time_correct = false

Cross-Subsystem Correlation

# Follow a transaction from receive through queue to ledger
{name=~"tx\\..*|txq\\..*"} | tx_type = "Payment" && duration > 500ms

# Find all NFT-related activity
{name=~"tx\\..*|txq\\..*"} | tx_type =~ "NFToken.*"

# Find consensus rounds with slow transactions
{name="consensus.accept"} | round_time_ms > 5000

Where to Look (Quick Reference)

Question	Span	Key Attributes
"Which tx type is slowest?"	tx.process	tx_type + duration
"Why was my tx rejected?"	tx.process	ter_result, applied
"Is the TxQ backing up?"	txq.accept	queue_size, ledger_changed
"Why was my tx dropped from queue?"	txq.accept_tx	txq_status, ter_code
"Are batch requests a problem?"	rpc.process	is_batch, batch_size
"Which RPC is expensive?"	rpc.command.*	load_type, duration
"Did consensus stall?"	consensus.check	consensus_stalled
"Was consensus outcome normal?"	consensus.accept	consensus_state
"Did a validator bow out?"	consensus.proposal.send	is_bow_out
"Which ledger was validated?"	consensus.validation.send	ledger_hash

---

Cross-Node Trace Propagation

xrpld propagates trace context across nodes via protobuf TraceContext fields embedded in peer-to-peer messages. When Node A sends a transaction, proposal, or validation, it injects its active span's trace/span IDs into the protobuf message. Node B extracts that context on receipt and creates a child span, linking the two nodes into a single distributed trace.

How It Works

Node A (sender)                          Node B (receiver)
+-----------------------------+          +-------------------------------+
| tx.process / consensus.*    |          | PeerImp::onMessage()          |
|   |                         |          |   |                           |
|   v                         |          |   v                           |
| SpanGuard::getTraceBytes()  |          | extract TraceContext from      |
|   |                         |          | protobuf message               |
|   v                         |   send   |   |                           |
| injectSpanContext() --------|--------->|   v                           |
| sets TraceContext fields    |  proto   | txReceiveSpan()               |
| (trace_id, span_id, flags) |  msg     | proposalReceiveSpan()         |
+-----------------------------+          | validationReceiveSpan()       |
                                         |   |                           |
                                         |   v                           |
                                         | child span with parent link   |
                                         +-------------------------------+

Send-Side Injection

Message Type	Injection Point	Mechanism
TMTransaction	NetworkOPs::apply()	Injects tx.process span into relay msg
TMProposeSet	RCLConsensus::propose()	Injects active context into proposal msg
TMValidation	RCLConsensus::validate()	Injects active context into validation msg

Receive-Side Extraction

Message Type	Extraction Point	Helper Function
TMTransaction	PeerImp::onMessage(TMTransaction)	TxTracing::txReceiveSpan()
TMProposeSet	PeerImp::onMessage(TMProposeSet)	ConsensusReceiveTracing::proposalReceiveSpan()
TMValidation	PeerImp::onMessage(TMValidation)	ConsensusReceiveTracing::validationReceiveSpan()

Key Files

File	Role
src/xrpld/telemetry/PropagationHelpers.h	injectSpanContext() — SpanGuard to protobuf
include/xrpl/telemetry/TraceContextPropagator.h	OTel context <-> protobuf conversion primitives
src/xrpld/telemetry/ConsensusReceiveTracing.h	Proposal/validation receive span factories
src/xrpld/telemetry/TxTracing.h	Transaction receive span factory

Backwards Compatibility

Older peers that do not populate TraceContext fields in their messages will simply produce empty trace bytes on the receive side. The extraction helpers detect this and create standalone (root) spans instead of child spans. No errors are logged and no data is lost — the receive span is still created with all its normal attributes, it just lacks a cross-node parent link.

Example Tempo Queries

# Find cross-node transaction traces (tx.process -> tx.receive across nodes)
{name="tx.receive"} && status != error

# Find proposals received with cross-node parent context
{name="consensus.proposal.receive"} && nestedSetParent > 0

# Trace a transaction across the network by its hash
{name=~"tx\\..*"} | tx_hash = "<hash>"

# Find all spans in a cross-node consensus trace
{rootServiceName="xrpld"} | consensus_round_id = <round_id>

# Compare latency between sender and receiver for validations
{name="consensus.validation.send" || name="consensus.validation.receive"}

Prometheus Metrics (Spanmetrics)

The OTel Collector's spanmetrics connector automatically derives RED (Rate, Errors, Duration) metrics from every span. No custom metrics code is needed in xrpld.

Generated Metric Names

Prometheus Metric	Type	Description
traces_span_metrics_calls_total	Counter	Total span invocations
traces_span_metrics_duration_milliseconds_bucket	Histogram	Latency distribution buckets
traces_span_metrics_duration_milliseconds_count	Histogram	Latency observation count
traces_span_metrics_duration_milliseconds_sum	Histogram	Cumulative latency

Metric Labels

Every metric carries these standard labels:

Label	Source	Example
span_name	Span name	rpc.command.server_info
status_code	Span status	STATUS_CODE_UNSET, STATUS_CODE_ERROR
service_name	Resource attribute	xrpld
span_kind	Span kind	SPAN_KIND_INTERNAL

Additionally, span attributes configured as dimensions in the collector become metric labels. The collector dimensions use the bare attribute keys emitted by the code, so the label name equals the attribute name:

Span Attribute	Metric Label	Applies To
command	command	rpc.command.* spans
rpc_status	rpc_status	rpc.command.* spans
consensus_mode	consensus_mode	consensus.ledger_close spans
local	local	tx.process spans
proposal_trusted	proposal_trusted	peer.proposal.receive spans
validation_trusted	validation_trusted	peer.validation.receive spans

Histogram Buckets

Configured in otel-collector-config.yaml:

1ms, 5ms, 10ms, 25ms, 50ms, 100ms, 250ms, 500ms, 1s, 5s

StatsD Metrics (beast::insight)

xrpld has a built-in metrics framework (beast::insight) that emits StatsD-format metrics over UDP. These complement the span-derived RED metrics by providing system-level gauges, counters, and timers that don't map to individual trace spans.

Configuration

Add to xrpld.cfg:

[insight]
server=statsd
address=127.0.0.1:8125
prefix=xrpld

The OTel Collector receives these via a statsd receiver on UDP port 8125 and exports them to Prometheus alongside spanmetrics.

Metric Reference

Gauges

Prometheus Metric	Source	Description
xrpld_LedgerMaster_Validated_Ledger_Age	LedgerMaster.h:373	Age of validated ledger (seconds)
xrpld_LedgerMaster_Published_Ledger_Age	LedgerMaster.h:374	Age of published ledger (seconds)
xrpld_State_Accounting_{Mode}_duration	NetworkOPs.cpp:774	Time in each operating mode (Disconnected/Connected/Syncing/Tracking/Full)
xrpld_State_Accounting_{Mode}_transitions	NetworkOPs.cpp:780	Transition count per mode
xrpld_Peer_Finder_Active_Inbound_Peers	PeerfinderManager.cpp:214	Active inbound peer connections
xrpld_Peer_Finder_Active_Outbound_Peers	PeerfinderManager.cpp:215	Active outbound peer connections
xrpld_Overlay_Peer_Disconnects	OverlayImpl.h:557	Peer disconnect count
xrpld_job_count	JobQueue.cpp:26	Current job queue depth
xrpld_{category}_Bytes_In/Out	OverlayImpl.h:535	Overlay traffic bytes per category (57 categories)
xrpld_{category}_Messages_In/Out	OverlayImpl.h:535	Overlay traffic messages per category

Counters

Prometheus Metric	Source	Description
xrpld_rpc_requests	ServerHandler.cpp:108	Total RPC request count
xrpld_ledger_fetches	InboundLedgers.cpp:44	Ledger fetch request count
xrpld_ledger_history_mismatch	LedgerHistory.cpp:16	Ledger hash mismatch count
xrpld_warn	Logic.h:33	Resource manager warning count
xrpld_drop	Logic.h:34	Resource manager drop count

Histograms (from StatsD timers)

Prometheus Metric	Source	Description
xrpld_rpc_time	ServerHandler.cpp:110	RPC response time (ms)
xrpld_rpc_size	ServerHandler.cpp:109	RPC response size (bytes)
xrpld_ios_latency	Application.cpp:438	I/O service loop latency (ms)
xrpld_pathfind_fast	PathRequests.h:23	Fast pathfinding duration (ms)
xrpld_pathfind_full	PathRequests.h:24	Full pathfinding duration (ms)

Deployment Tiers

Multiple xrpld instances can send telemetry to per-tier collectors that all forward to one Grafana stack. Four resource attributes segregate the data so one dashboard set serves every deployment:

Dimension	Attribute	Set by	Example values
Node	service.instance.id	xrpld cfg	alice-laptop, ci-runner-7
Service	service.name	xrpld cfg	xrpld, pratik-xrpld
Network	xrpl.network.type	xrpld node	mainnet, testnet, devnet
Environment	deployment.environment	collector	local, test, ci, prod

Dashboards expose these as the template variables $node, $service_name, $xrpl_network_type, and $deployment_environment (each variable name matches its Prometheus label). Select them top-down — environment → network → service → node. Selecting All matches every value, including series lacking the label, so mixed old/new data never disappears.

Who owns which attribute

• Node and service come from xrpld config (service_instance_id, service_name). Unique per process.
• Network is a property of the chain the node joined; the node derives it from [network_id] and stamps xrpl.network.type on all three signals.
• Environment is a property of where the collector runs; each collector serves one environment and stamps it.

The upsert vs insert rule

The collector's resource/tier processor uses two actions on purpose:

• deployment.environment → upsert (overwrite). The collector is the environment, so it is authoritative.
• xrpl.network.type → insert (fill only if absent). The node knows its real network, so the collector must not overwrite it — insert only supplies a value when the source did not (e.g. an older xrpld build). This is what lets a local node connected to mainnet report network=mainnet, not the collector's default.

Configuring a collector for a tier

Each tier runs its own collector. Set the two values in the resource/tier processor of the collector config (otel-collector-config.yaml for local backends, otel-collector-config.grafanacloud.yaml for Grafana Cloud):

processors:
  resource/tier:
    attributes:
      - key: deployment.environment
        value: <tier> # local | test | ci | prod
        action: upsert
      - key: xrpl.network.type
        value: <network> # mainnet | testnet | devnet (fallback only)
        action: insert

Suggested per-tier values:

Collector	deployment.environment	xrpl.network.type (fallback)
Developer laptop	local	devnet
Test machines	test	testnet
CI runs	ci	testnet
Production observer	prod	mainnet

The xrpl.network.type value is only a fallback: when the node stamps its own network (all current builds do), the node's value wins. Set it to the network the collector most commonly serves.

How the tier labels reach metrics

Resource attributes do not become Prometheus labels automatically. Two collector settings make it work, both already enabled:

• prometheus.resource_to_telemetry_conversion: enabled: true promotes resource attributes to metric labels on the local scrape surface.
• spanmetrics.resource_metrics_key_attributes lists the tier attributes so span-derived series stay grouped per node and tier.

Traces and logs carry resource attributes natively; Grafana Cloud ingests all three signals' attributes over OTLP directly.

Grafana Dashboards

Ten dashboards are pre-provisioned in docker/telemetry/grafana/dashboards/:

RPC Performance (rpc-performance)

Panel	Type	PromQL	Labels Used
RPC Request Rate by Command	timeseries	sum by (command) (rate(traces_span_metrics_calls_total{span_name=~"rpc.command.*"}[5m]))	command
RPC Latency p95 by Command	timeseries	histogram_quantile(0.95, sum by (le, command) (rate(traces_span_metrics_duration_milliseconds_bucket{span_name=~"rpc.command.*"}[5m])))	command
RPC Error Rate	bargauge	Error spans / total spans × 100, grouped by command	command, status_code
RPC Latency Heatmap	heatmap	sum(increase(traces_span_metrics_duration_milliseconds_bucket{span_name=~"rpc.command.*"}[5m])) by (le)	le (bucket boundaries)
Overall RPC Throughput	timeseries	rpc.request + rpc.process rate	—
RPC Success vs Error	timeseries	by status_code (UNSET vs ERROR)	status_code
Top Commands by Volume	bargauge	topk(10, ...) by command	command
WebSocket Message Rate	stat	rpc.ws_message rate	—

Transaction Overview (transaction-overview)

Panel	Type	PromQL	Labels Used
Transaction Processing Rate	timeseries	rate(traces_span_metrics_calls_total{span_name="tx.process"}[5m]) and tx.receive	span_name
Transaction Processing Latency	timeseries	histogram_quantile(0.95 / 0.50, ... {span_name="tx.process"})	—
Transaction Path Distribution	piechart	sum by (local) (rate(traces_span_metrics_calls_total{span_name="tx.process"}[5m]))	local
Transaction Receive vs Suppressed	timeseries	rate(traces_span_metrics_calls_total{span_name="tx.receive"}[5m])	—
TX Processing Duration Heatmap	heatmap	tx.process histogram buckets	le
TX Apply Duration per Ledger	timeseries	p95/p50 of tx.apply	—
Peer TX Receive Rate	timeseries	tx.receive rate	—
TX Apply Failed Rate	stat	tx.apply with STATUS_CODE_ERROR	status_code

Consensus Health (consensus-health)

Panel	Type	PromQL	Labels Used
Consensus Round Duration	timeseries	histogram_quantile(0.95 / 0.50, ... {span_name="consensus.accept"})	—
Consensus Proposals Sent Rate	timeseries	rate(traces_span_metrics_calls_total{span_name="consensus.proposal.send"}[5m])	—
Ledger Close Duration	timeseries	histogram_quantile(0.95, ... {span_name="consensus.ledger_close"})	—
Validation Send Rate	stat	rate(traces_span_metrics_calls_total{span_name="consensus.validation.send"}[5m])	—
Ledger Apply Duration	timeseries	histogram_quantile(0.95 / 0.50, ... {span_name="consensus.accept.apply"})	—
Close Time Agreement	timeseries	rate(traces_span_metrics_calls_total{span_name="consensus.accept.apply"}[5m])	—
Consensus Mode Over Time	timeseries	consensus.ledger_close by consensus_mode	consensus_mode
Accept vs Close Rate	timeseries	consensus.accept vs consensus.ledger_close rate	—
Validation vs Close Rate	timeseries	consensus.validation.send vs consensus.ledger_close	—
Accept Duration Heatmap	heatmap	consensus.accept histogram buckets	le

Ledger Operations (ledger-operations)

Panel	Type	PromQL	Labels Used
Ledger Build Rate	stat	ledger.build call rate	—
Ledger Build Duration	timeseries	p95/p50 of ledger.build	—
Ledger Validation Rate	stat	ledger.validate call rate	—
Build Duration Heatmap	heatmap	ledger.build histogram buckets	le
TX Apply Duration	timeseries	p95/p50 of tx.apply	—
TX Apply Rate	timeseries	tx.apply call rate	—
Ledger Store Rate	stat	ledger.store call rate	—
Build vs Close Duration	timeseries	p95 ledger.build vs consensus.ledger_close	—

Peer Network (peer-network)

Requires trace_peer=1 in the [telemetry] config section.

Panel	Type	PromQL	Labels Used
Proposal Receive Rate	timeseries	peer.proposal.receive rate	—
Validation Receive Rate	timeseries	peer.validation.receive rate	—
Proposals Trusted vs Untrusted	piechart	by proposal_trusted	proposal_trusted
Validations Trusted vs Untrusted	piechart	by validation_trusted	validation_trusted

Node Health -- StatsD (xrpld-statsd-node-health)

Panel	Type	PromQL	Labels Used
Validated Ledger Age	stat	xrpld_LedgerMaster_Validated_Ledger_Age	—
Published Ledger Age	stat	xrpld_LedgerMaster_Published_Ledger_Age	—
Operating Mode Duration	timeseries	xrpld_State_Accounting_*_duration	—
Operating Mode Transitions	timeseries	xrpld_State_Accounting_*_transitions	—
I/O Latency	timeseries	histogram_quantile(0.95, xrpld_ios_latency_bucket)	—
Job Queue Depth	timeseries	xrpld_job_count	—
Ledger Fetch Rate	stat	rate(xrpld_ledger_fetches[5m])	—
Ledger History Mismatches	stat	rate(xrpld_ledger_history_mismatch[5m])	—
Key Jobs Execution Time	timeseries	xrpld_acceptLedger{quantile="$quantile"} (+ 10 more key jobs)	quantile
Key Jobs Dequeue Wait Time	timeseries	xrpld_acceptLedger_q{quantile="$quantile"} (+ 10 more)	quantile
FullBelowCache Size	timeseries	xrpld_Node_family_full_below_cache_size	—
FullBelowCache Hit Rate	gauge	xrpld_Node_family_full_below_cache_hit_rate	—
Ledger Publish Gap	stat	Published_Ledger_Age - Validated_Ledger_Age	—
State Duration Rate (Full vs Tracking)	timeseries	rate(xrpld_State_Accounting_Full_duration[5m]) / 1000000	—
All Jobs Execution Time (Detail)	timeseries	{__name__=~"xrpld_<all_jobs>", quantile="$quantile"}	quantile
All Jobs Dequeue Wait (Detail)	timeseries	{__name__=~"xrpld_<all_jobs>_q", quantile="$quantile"}	quantile

Network Traffic -- StatsD (xrpld-statsd-network)

Panel	Type	PromQL	Labels Used
Active Peers	timeseries	xrpld_Peer_Finder_Active_*_Peers	—
Peer Disconnects	timeseries	xrpld_Overlay_Peer_Disconnects	—
Total Network Bytes	timeseries	rate(xrpld_total_Bytes_In/Out[5m])	—
Total Network Messages	timeseries	xrpld_total_Messages_In/Out	—
Transaction Traffic	timeseries	xrpld_transactions_Messages_In/Out	—
Proposal Traffic	timeseries	xrpld_proposals_Messages_In/Out	—
Validation Traffic	timeseries	xrpld_validations_Messages_In/Out	—
Traffic by Category	bargauge	topk(10, xrpld_*_Bytes_In)	—
Duplicate Traffic (Wasted Bandwidth)	timeseries	rate(xrpld_*_duplicate_Bytes_In/Out[5m])	—
All Traffic Categories (Detail)	timeseries	topk(15, rate(xrpld_*_Bytes_In[5m]))	—

RPC & Pathfinding -- StatsD (xrpld-statsd-rpc)

Panel	Type	PromQL	Labels Used
RPC Request Rate	stat	rate(xrpld_rpc_requests[5m])	—
RPC Response Time	timeseries	histogram_quantile(0.95, xrpld_rpc_time_bucket)	—
RPC Response Size	timeseries	histogram_quantile(0.95, xrpld_rpc_size_bucket)	—
RPC Response Time Heatmap	heatmap	xrpld_rpc_time_bucket	—
Pathfinding Fast Duration	timeseries	histogram_quantile(0.95, xrpld_pathfind_fast_bucket)	—
Pathfinding Full Duration	timeseries	histogram_quantile(0.95, xrpld_pathfind_full_bucket)	—
Resource Warnings Rate	stat	rate(xrpld_warn[5m])	—
Resource Drops Rate	stat	rate(xrpld_drop[5m])	—

Span → Metric → Dashboard Summary

Span Name	Prometheus Metric Filter	Grafana Dashboard
rpc.http_request	{span_name="rpc.http_request"}	RPC Performance (Overall Throughput)
rpc.ws_upgrade	{span_name="rpc.ws_upgrade"}	-- (available but not paneled)
rpc.ws_message	{span_name="rpc.ws_message"}	RPC Performance (WebSocket Rate)
rpc.process	{span_name="rpc.process"}	RPC Performance (Overall Throughput)
rpc.command.*	{span_name=~"rpc.command.*"}	RPC Performance (Rate, Latency, Error, Top)
tx.process	{span_name="tx.process"}	Transaction Overview (Rate, Latency, Heatmap)
tx.receive	{span_name="tx.receive"}	Transaction Overview (Rate, Receive)
tx.apply	{span_name="tx.apply"}	Transaction Overview + Ledger Ops (Apply)
txq.enqueue	{span_name="txq.enqueue"}	-- (available but not paneled)
txq.apply_direct	{span_name="txq.apply_direct"}	-- (available but not paneled)
txq.batch_clear	{span_name="txq.batch_clear"}	-- (available but not paneled)
txq.accept	{span_name="txq.accept"}	-- (available but not paneled)
txq.accept_tx	{span_name="txq.accept_tx"}	-- (available but not paneled)
txq.cleanup	{span_name="txq.cleanup"}	-- (available but not paneled)
consensus.round	{span_name="consensus.round"}	-- (available but not paneled)
consensus.phase.open	{span_name="consensus.phase.open"}	-- (available but not paneled)
consensus.establish	{span_name="consensus.establish"}	-- (available but not paneled)
consensus.update_positions	{span_name="consensus.update_positions"}	-- (available but not paneled)
consensus.check	{span_name="consensus.check"}	-- (available but not paneled)
consensus.accept	{span_name="consensus.accept"}	Consensus Health (Duration, Rate, Heatmap)
consensus.proposal.send	{span_name="consensus.proposal.send"}	Consensus Health (Proposals Rate)
consensus.ledger_close	{span_name="consensus.ledger_close"}	Consensus Health (Close, Mode)
consensus.validation.send	{span_name="consensus.validation.send"}	Consensus Health (Validation Rate)
consensus.accept.apply	{span_name="consensus.accept.apply"}	Consensus Health (Apply Duration, Close Time)
consensus.mode_change	{span_name="consensus.mode_change"}	-- (available but not paneled)
consensus.proposal.receive	{span_name="consensus.proposal.receive"}	-- (available but not paneled)
consensus.validation.receive	{span_name="consensus.validation.receive"}	-- (available but not paneled)
ledger.build	{span_name="ledger.build"}	Ledger Ops (Build Rate, Duration, Heatmap)
ledger.validate	{span_name="ledger.validate"}	Ledger Ops (Validation Rate)
ledger.store	{span_name="ledger.store"}	Ledger Ops (Store Rate)
peer.proposal.receive	{span_name="peer.proposal.receive"}	Peer Network (Rate, Trusted/Untrusted)
peer.validation.receive	{span_name="peer.validation.receive"}	Peer Network (Rate, Trusted/Untrusted)

Troubleshooting

No traces appearing in Tempo

1. Check xrpld logs for Telemetry starting message
2. Verify enabled=1 in the [telemetry] config section
3. Test collector connectivity: curl -v http://localhost:4318/v1/traces
4. Check collector logs: docker compose -f docker/telemetry/docker-compose.yml logs otel-collector
5. Verify Tempo is receiving data: open Grafana → Explore → select Tempo datasource → search by service.name = xrpld
6. Check Tempo logs: docker compose -f docker/telemetry/docker-compose.yml logs tempo

High memory usage

• Reduce trace volume with collector-side tail sampling (xrpld head sampling is fixed at 1.0 and is not configurable)
• Reduce max_queue_size and batch_size
• Disable high-volume trace categories: trace_peer=0

Collector connection failures

• Verify endpoint URL matches collector address
• Check firewall rules for ports 4317/4318
• If using TLS, verify certificate path with tls_ca_cert

Performance Tuning

Scenario	Recommendation
Production mainnet	trace_peer=0; reduce volume via collector tail sampling
Testnet/devnet	Full tracing (head sampling fixed at 1.0)
Debugging specific issue	Full tracing (head sampling fixed at 1.0)
High-throughput node	Increase batch_size=1024, max_queue_size=4096

Disabling Telemetry

Set enabled=0 in config (runtime disable) or build without the flag:

cmake --preset default -Dtelemetry=OFF

When telemetry is compiled out, all trace macros expand to no-ops with zero overhead.