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9e27120a15
- Add canonical ledgerHash (xrpl.ledger.hash) to SpanNames.h. - LedgerSpanNames: reuse shared canonicals (ledgerSeq, closeTime, closeTimeCorrect, closeResolutionMs, ledgerHash); bare names for tx_count, tx_failed, validations. - PeerSpanNames: reuse shared canonicals (peerId, ledgerHash); bare names for proposal_trusted, validation_full, validation_trusted. - Update call sites in BuildLedger.cpp, LedgerMaster.cpp, PeerImp.cpp. - Update 5 Grafana dashboards: strip xrpl.<domain>. prefix from per-span attr refs in PromQL/TraceQL queries. Keep rule-5 entries. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
385 lines
12 KiB
JSON
385 lines
12 KiB
JSON
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"title": "Transaction Processing Rate",
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"description": "Rate of transactions entering the processing pipeline. tx.process (NetworkOPs.cpp:1227) fires when a transaction is submitted locally or received from a peer and enters processTransaction(). tx.receive (PeerImp.cpp:1273) fires when a raw transaction message arrives from a peer before deduplication.",
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"legendFormat": "tx.process / Sec [{{exported_instance}}]"
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"title": "Transaction Processing Latency",
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"description": "p95 and p50 latency of transaction processing (tx.process span). Measures the time from when a transaction enters processTransaction() to completion. Computed via histogram_quantile() over the spanmetrics duration histogram with a 5m rate window.",
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}
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},
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{
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"title": "Transaction Path Distribution",
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"description": "Breakdown of transactions by origin path. The local attribute indicates whether the transaction was submitted locally (true) or received from a peer (false). Helps understand the ratio of locally-originated vs relayed transactions.",
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"type": "piechart",
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"expr": "sum by (local, exported_instance) (rate(traces_span_metrics_calls_total{exported_instance=~\"$node\", local=~\"$tx_origin\", span_name=\"tx.process\"}[5m]))",
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"title": "Transaction Receive vs Suppressed",
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"description": "Total rate of raw transaction messages received from peers (tx.receive span from PeerImp.cpp:1273). This fires before deduplication via the HashRouter, so the difference between tx.receive and tx.process reflects suppressed duplicate transactions.",
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"targets": [
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{
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"datasource": {
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"type": "prometheus"
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},
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"expr": "sum by (xrpl_tx_suppressed, exported_instance) (rate(traces_span_metrics_calls_total{span_name=\"tx.receive\", exported_instance=~\"$node\"}[$__rate_interval]))",
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"legendFormat": "Suppressed={{xrpl_tx_suppressed}} [{{exported_instance}}]"
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},
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{
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"title": "Transaction Processing Duration Heatmap",
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"description": "Heatmap showing the distribution of tx.process span durations across histogram buckets over time. Each cell represents the count of transactions that completed within that latency bucket in a 5m window. Reveals whether processing times are consistent or exhibit multi-modal patterns.",
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"type": "heatmap",
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"gridPos": {
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"w": 12,
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"type": "prometheus"
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"expr": "sum(increase(traces_span_metrics_duration_milliseconds_bucket{exported_instance=~\"$node\", span_name=\"tx.process\"}[5m])) by (le)",
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"legendFormat": "{{le}}",
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"format": "heatmap"
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}
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]
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},
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{
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"title": "Transaction Apply Duration per Ledger",
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"description": "p95 and p50 latency of applying the consensus transaction set to a new ledger. The tx.apply span (BuildLedger.cpp:88) wraps the applyTransactions() function that iterates through the CanonicalTXSet and applies each transaction to the OpenView. Long durations indicate heavy transaction sets or expensive transaction processing.",
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"targets": [
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{
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"datasource": {
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"type": "prometheus"
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},
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"expr": "histogram_quantile(0.95, sum by (le, exported_instance) (rate(traces_span_metrics_duration_milliseconds_bucket{exported_instance=~\"$node\", span_name=\"tx.apply\"}[5m])))",
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"legendFormat": "P95 tx.apply [{{exported_instance}}]"
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},
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{
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"datasource": {
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"type": "prometheus"
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},
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"expr": "histogram_quantile(0.50, sum by (le, exported_instance) (rate(traces_span_metrics_duration_milliseconds_bucket{exported_instance=~\"$node\", span_name=\"tx.apply\"}[5m])))",
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"legendFormat": "P50 tx.apply [{{exported_instance}}]"
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}
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],
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}
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},
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{
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"title": "Peer Transaction Receive Rate",
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"description": "Rate of transaction messages received from network peers. Sourced from the tx.receive span (PeerImp.cpp:1273) which fires in the onMessage(TMTransaction) handler. High rates may indicate network-wide transaction volume spikes or peer flooding.",
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"type": "timeseries",
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"targets": [
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"expr": "sum by (exported_instance) (rate(traces_span_metrics_calls_total{exported_instance=~\"$node\", span_name=\"tx.receive\"}[5m]))",
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"legendFormat": "tx.receive / Sec [{{exported_instance}}]"
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"spanNulls": true,
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"insertNulls": false,
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"pointSize": 3
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}
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},
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"overrides": []
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}
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},
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{
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"title": "Transaction Apply Failed Rate",
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"description": "Rate of tx.apply spans completing with error status, indicating transaction application failures during ledger building. The span records tx_failed as an attribute. Thresholds: green < 0.1/sec, yellow 0.1-1/sec, red > 1/sec. Some failures are normal (e.g. conflicting offers) but sustained high rates may indicate issues.",
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"type": "stat",
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"datasource": {
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"type": "prometheus"
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},
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"expr": "sum by (exported_instance) (rate(traces_span_metrics_calls_total{exported_instance=~\"$node\", span_name=\"tx.apply\", status_code=\"STATUS_CODE_ERROR\"}[5m]))",
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"legendFormat": "Failed / Sec [{{exported_instance}}]"
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}
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],
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"unit": "ops",
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"thresholds": {
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"steps": [
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{
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"color": "green",
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"value": null
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},
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{
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"color": "yellow",
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"value": 0.1
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},
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{
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"color": "red",
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"value": 1
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}
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]
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}
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},
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"overrides": []
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}
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],
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"schemaVersion": 39,
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"tags": ["rippled", "transactions", "telemetry"],
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"templating": {
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"list": [
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{
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"name": "node",
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"label": "Node",
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"description": "Filter by rippled node (service.instance.id — e.g. Node-1)",
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"type": "query",
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"query": "label_values(traces_span_metrics_calls_total, exported_instance)",
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"datasource": {
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"uid": "prometheus"
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"allValue": ".*",
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"current": {
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"text": "All",
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"value": "$__all"
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},
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"multi": true,
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"refresh": 2,
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"sort": 1
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},
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{
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"name": "tx_origin",
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"label": "TX Origin",
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"description": "Filter by transaction origin (true = local submit, false = peer relay)",
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"type": "query",
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"query": "label_values(traces_span_metrics_calls_total{span_name=\"tx.process\"}, local)",
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"datasource": {
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"type": "prometheus",
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"uid": "prometheus"
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"text": "All",
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]
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},
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"time": {
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"from": "now-1h",
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"to": "now"
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},
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"title": "Transaction Overview",
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"uid": "rippled-transactions"
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}
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