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