Monitoring and Reliability › Monitoring in Production
AI Agent HandbookAll chapters Monitoring and Reliability › Monitoring in ProductionOne section · Sections in this chapter9 / 14 ↓
As your agent runs in production, monitoring becomes an ongoing practice rather than a one-time setup. You'll develop a sense of what's normal for your agent and learn to spot anomalies.
Here are some practices that help:
Set Up Alerts: Configure your monitoring system to notify you when something looks wrong. For example, "alert me if error rate exceeds 5%" or "alert me if average response time exceeds 10 seconds". This way you learn about problems quickly, often before users report them.
Review Metrics Regularly: Even without alerts, check your metrics dashboard periodically. Look for trends. Is usage growing? Are certain features used more than others? Are there patterns in when errors occur?
Analyze Logs: When you see unusual metrics, dig into the logs to understand what's happening. Metrics tell you something is wrong; logs tell you what and why.
Track User Feedback: Metrics and logs show technical health, but user feedback shows whether people are actually satisfied. If users report frustration even when metrics look good, investigate. There might be a usability issue that technical monitoring doesn't capture.
Test Your Monitoring: Occasionally, verify your monitoring is working. Trigger an error intentionally and confirm you get alerted. This ensures your monitoring won't fail silently when you need it.