Monitoring & Observability
Master monitoring and observability for production AI agents including logging, tracing, metrics, and real-time debugging
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Alerts wake you up at 3am. Make them count. Alert on symptoms (error rate spike), not causes (CPU high). Set thresholds based on user impact: if users aren't affected, don't page. Use severity levels: INFO (log only), WARN (investigate tomorrow), ERROR (page immediately). When debugging: 1) Check dashboard (what's broken?), 2) Grep logs by trace ID (what happened?), 3) Examine traces (where's the bottleneck?). 5-minute diagnosis beats 5-hour guesswork.
Interactive: Alert Management Simulator
Watch how alerts trigger based on real-time conditions. Click "Start Monitoring" to simulate an incident:
Debugging Workflow
Too many alerts = ignored alerts. If you page for every warning, engineers will ignore pages. Only alert on user-impacting issues. ERROR alert = immediate response required. WARN alert = investigate during business hours. INFO = just log it. Review alert history monthly: Which alerts were false positives? Which real incidents had no alert? Tune thresholds. Good alerting means 95% of pages are real problems needing immediate action.