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Monitoring & Observability

Master monitoring and observability for production AI agents including logging, tracing, metrics, and real-time debugging

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Metrics & Dashboards

Metrics are numbers that tell the health story: requests/second, error rate %, P50/P95/P99 latency, cost per request. Track them over time. Plot them on dashboards. Set baselines: "normal is 500ms P95, 0.1% error rate, $0.05/request". When metrics deviate, investigate. Dashboard rule: 5-second glance should reveal system health. Red = bad, green = good, yellow = investigate. No clutter.

Interactive: Real-Time Metrics Dashboard

Explore key metrics across different time windows. Change the time range to see how metrics vary:

Agent Performance Dashboard
Total Requests
↗️
1,250
healthy
Error Count
↘️
15
healthy
P95 Latency
→
450ms
healthy
Total Cost
↗️
$12.5
healthy

Essential Metrics to Track

🎯 Business Metrics
  • • Task success rate
  • • User satisfaction
  • • Requests per user
  • • Revenue impact
⚡ Performance Metrics
  • • P50/P95/P99 latency
  • • Error rate %
  • • Throughput (req/s)
  • • Queue depth
💰 Cost Metrics
  • • Token usage
  • • API costs
  • • Cost per request
  • • Monthly burn rate
💡
Dashboard Design Principles

Single pane of glass: All critical metrics visible without scrolling. Red/yellow/green:Color code health instantly. Percentiles over averages: P95 reveals tail latency; average hides it.Compare to baseline: Show current vs. normal. Drill-down enabled: Click metric → see logs/traces. If dashboard doesn't reveal problems in 5 seconds, redesign it.

← Logging & Tracing