--- name: coderabbit-observability description: | Set up comprehensive observability for CodeRabbit integrations with metrics, traces, and alerts. Use when implementing monitoring for CodeRabbit operations, setting up dashboards, or configuring alerting for CodeRabbit integration health. Trigger with phrases like "coderabbit monitoring", "coderabbit metrics", "coderabbit observability", "monitor coderabbit", "coderabbit alerts", "coderabbit tracing". allowed-tools: Read, Write, Edit version: 1.0.0 license: MIT author: Jeremy Longshore --- # CodeRabbit Observability ## Overview Set up comprehensive observability for CodeRabbit integrations. ## Prerequisites - Prometheus or compatible metrics backend - OpenTelemetry SDK installed - Grafana or similar dashboarding tool - AlertManager configured ## Metrics Collection ### Key Metrics | Metric | Type | Description | |--------|------|-------------| | `coderabbit_requests_total` | Counter | Total API requests | | `coderabbit_request_duration_seconds` | Histogram | Request latency | | `coderabbit_errors_total` | Counter | Error count by type | | `coderabbit_rate_limit_remaining` | Gauge | Rate limit headroom | ### Prometheus Metrics ```typescript import { Registry, Counter, Histogram, Gauge } from 'prom-client'; const registry = new Registry(); const requestCounter = new Counter({ name: 'coderabbit_requests_total', help: 'Total CodeRabbit API requests', labelNames: ['method', 'status'], registers: [registry], }); const requestDuration = new Histogram({ name: 'coderabbit_request_duration_seconds', help: 'CodeRabbit request duration', labelNames: ['method'], buckets: [0.05, 0.1, 0.25, 0.5, 1, 2.5, 5], registers: [registry], }); const errorCounter = new Counter({ name: 'coderabbit_errors_total', help: 'CodeRabbit errors by type', labelNames: ['error_type'], registers: [registry], }); ``` ### Instrumented Client ```typescript async function instrumentedRequest( method: string, operation: () => Promise ): Promise { const timer = requestDuration.startTimer({ method }); try { const result = await operation(); requestCounter.inc({ method, status: 'success' }); return result; } catch (error: any) { requestCounter.inc({ method, status: 'error' }); errorCounter.inc({ error_type: error.code || 'unknown' }); throw error; } finally { timer(); } } ``` ## Distributed Tracing ### OpenTelemetry Setup ```typescript import { trace, SpanStatusCode } from '@opentelemetry/api'; const tracer = trace.getTracer('coderabbit-client'); async function tracedCodeRabbitCall( operationName: string, operation: () => Promise ): Promise { return tracer.startActiveSpan(`coderabbit.${operationName}`, async (span) => { try { const result = await operation(); span.setStatus({ code: SpanStatusCode.OK }); return result; } catch (error: any) { span.setStatus({ code: SpanStatusCode.ERROR, message: error.message }); span.recordException(error); throw error; } finally { span.end(); } }); } ``` ## Logging Strategy ### Structured Logging ```typescript import pino from 'pino'; const logger = pino({ name: 'coderabbit', level: process.env.LOG_LEVEL || 'info', }); function logCodeRabbitOperation( operation: string, data: Record, duration: number ) { logger.info({ service: 'coderabbit', operation, duration_ms: duration, ...data, }); } ``` ## Alert Configuration ### Prometheus AlertManager Rules ```yaml # coderabbit_alerts.yaml groups: - name: coderabbit_alerts rules: - alert: CodeRabbitHighErrorRate expr: | rate(coderabbit_errors_total[5m]) / rate(coderabbit_requests_total[5m]) > 0.05 for: 5m labels: severity: warning annotations: summary: "CodeRabbit error rate > 5%" - alert: CodeRabbitHighLatency expr: | histogram_quantile(0.95, rate(coderabbit_request_duration_seconds_bucket[5m]) ) > 2 for: 5m labels: severity: warning annotations: summary: "CodeRabbit P95 latency > 2s" - alert: CodeRabbitDown expr: up{job="coderabbit"} == 0 for: 1m labels: severity: critical annotations: summary: "CodeRabbit integration is down" ``` ## Dashboard ### Grafana Panel Queries ```json { "panels": [ { "title": "CodeRabbit Request Rate", "targets": [{ "expr": "rate(coderabbit_requests_total[5m])" }] }, { "title": "CodeRabbit Latency P50/P95/P99", "targets": [{ "expr": "histogram_quantile(0.5, rate(coderabbit_request_duration_seconds_bucket[5m]))" }] } ] } ``` ## Instructions ### Step 1: Set Up Metrics Collection Implement Prometheus counters, histograms, and gauges for key operations. ### Step 2: Add Distributed Tracing Integrate OpenTelemetry for end-to-end request tracing. ### Step 3: Configure Structured Logging Set up JSON logging with consistent field names. ### Step 4: Create Alert Rules Define Prometheus alerting rules for error rates and latency. ## Output - Metrics collection enabled - Distributed tracing configured - Structured logging implemented - Alert rules deployed ## Error Handling | Issue | Cause | Solution | |-------|-------|----------| | Missing metrics | No instrumentation | Wrap client calls | | Trace gaps | Missing propagation | Check context headers | | Alert storms | Wrong thresholds | Tune alert rules | | High cardinality | Too many labels | Reduce label values | ## Examples ### Quick Metrics Endpoint ```typescript app.get('/metrics', async (req, res) => { res.set('Content-Type', registry.contentType); res.send(await registry.metrics()); }); ``` ## Resources - [Prometheus Best Practices](https://prometheus.io/docs/practices/naming/) - [OpenTelemetry Documentation](https://opentelemetry.io/docs/) - [CodeRabbit Observability Guide](https://docs.coderabbit.com/observability) ## Next Steps For incident response, see `coderabbit-incident-runbook`.