Observability Tracing and Monitoring

Observability Tracing and Monitoring

Audit Logs

50 of 57 in this book · 2 min read

Domain: Observability, Tracing & Monitoring
Status: Implementation guidance / design checklist
Applicability: Depends on product architecture and risk

Concept

Audit Logs is the capability concerned with audit logs in the broader domain of inspectable operations and diagnostic evidence. Its purpose is to make this concern explicit, testable, governable, and reusable across AI-powered workflows. Specify which events and dimensions of Audit Logs operators must inspect to diagnose incidents.

Recommended Practices

  • Correlate traces by run ID; redact secrets; sample responsibly; define useful dashboards and alert thresholds.
  • Define an owner, API/schema contract, failure response, and acceptance criteria for audit logs.
  • Add automated positive, negative, boundary, and permission tests for audit logs; review metrics in staging and production.

Example Use Cases

  • On-call engineers identify the failed tool call and the exact model/configuration for a broken workflow.
  • Apply audit logs in a high-volume enterprise workflow while recording the user, project scope, input contract, and observable outcome.

Common Implementation Pitfalls

  • Logging private prompts indiscriminately or collecting metrics without actionable alerts.
  • No documented fallback, operational owner, or signal showing when audit logs is failing.
  • Testing only happy paths while ignoring missing data, revoked access, malformed outputs, and partial outages.

Production Readiness Checklist

  • An accountable owner and technical contract for audit logs are documented.
  • At least one successful and one failing end-to-end scenario is reproducible.
  • Access controls, retention, and audit requirements are verified where relevant.
  • Release monitoring includes a measurable success or failure signal for this capability.

Design Questions

  1. What concrete risk or business requirement requires Audit Logs?
  2. What happens when it is unavailable, wrong, stale, or slow?
  3. How is its success evaluated against a trusted reference or observed outcome?
  4. Who can change its configuration, and how are changes released and rolled back?

Related Areas