--- name: exa-observability description: | Set up comprehensive observability for Exa integrations with metrics, traces, and alerts. Use when implementing monitoring for Exa operations, setting up dashboards, or configuring alerting for Exa integration health. Trigger with phrases like "exa monitoring", "exa metrics", "exa observability", "monitor exa", "exa alerts", "exa tracing". allowed-tools: Read, Write, Edit version: 1.0.0 license: MIT author: Jeremy Longshore --- # Exa Observability ## Overview Set up comprehensive observability for Exa integrations. ## Prerequisites - Prometheus or compatible metrics backend - OpenTelemetry SDK installed - Grafana or similar dashboarding tool - AlertManager configured ## Metrics Collection ### Key Metrics | Metric | Type | Description | |--------|------|-------------| | `exa_requests_total` | Counter | Total API requests | | `exa_request_duration_seconds` | Histogram | Request latency | | `exa_errors_total` | Counter | Error count by type | | `exa_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: 'exa_requests_total', help: 'Total Exa API requests', labelNames: ['method', 'status'], registers: [registry], }); const requestDuration = new Histogram({ name: 'exa_request_duration_seconds', help: 'Exa request duration', labelNames: ['method'], buckets: [0.05, 0.1, 0.25, 0.5, 1, 2.5, 5], registers: [registry], }); const errorCounter = new Counter({ name: 'exa_errors_total', help: 'Exa 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('exa-client'); async function tracedExaCall( operationName: string, operation: () => Promise ): Promise { return tracer.startActiveSpan(`exa.${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: 'exa', level: process.env.LOG_LEVEL || 'info', }); function logExaOperation( operation: string, data: Record, duration: number ) { logger.info({ service: 'exa', operation, duration_ms: duration, ...data, }); } ``` ## Alert Configuration ### Prometheus AlertManager Rules ```yaml # exa_alerts.yaml groups: - name: exa_alerts rules: - alert: ExaHighErrorRate expr: | rate(exa_errors_total[5m]) / rate(exa_requests_total[5m]) > 0.05 for: 5m labels: severity: warning annotations: summary: "Exa error rate > 5%" - alert: ExaHighLatency expr: | histogram_quantile(0.95, rate(exa_request_duration_seconds_bucket[5m]) ) > 2 for: 5m labels: severity: warning annotations: summary: "Exa P95 latency > 2s" - alert: ExaDown expr: up{job="exa"} == 0 for: 1m labels: severity: critical annotations: summary: "Exa integration is down" ``` ## Dashboard ### Grafana Panel Queries ```json { "panels": [ { "title": "Exa Request Rate", "targets": [{ "expr": "rate(exa_requests_total[5m])" }] }, { "title": "Exa Latency P50/P95/P99", "targets": [{ "expr": "histogram_quantile(0.5, rate(exa_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/) - [Exa Observability Guide](https://docs.exa.com/observability) ## Next Steps For incident response, see `exa-incident-runbook`.