Observability
Observability is a critical foundation, not an afterthought. Without visibility into problems, neither AI nor humans can act. In an AI-coding world where engineers see less of the produced code, observability is the safety net.
Always Managed Services
Use managed observability services. Engineers should focus on the product, not building monitoring infrastructure. Logging, alerting, and tracing are solved problems.
Structured Logs
- Include consistent filterable identifiers in every log:
providerCode,propertyId,userId, etc. - Use domain language in log identifiers. Not internal IDs — use
providerCode,roomTypeCode,ratePlanCode. - Keep the same base data on related logs — consistent identifiers across related entries enable correlation.
- Be specific in log messages. “Property has no room_type in DB” is better than “not found.”
- Do not duplicate what the framework provides — base location, timestamp, etc. are automatic.
AI and Observability
- Log AI agent inputs and outputs. Essential for debugging AI-driven flows.
- Monitor production behavior of AI-generated code the same way you monitor any critical system.
Performance Monitoring
Define what “bad” looks like. Move fast until monitoring shows you need to act. You cannot optimize what you cannot see.
- P50/P75 real user experience, not synthetic benchmarks.
- Monitoring is the key — invest in visibility before investing in optimization.
Error Levels
The error level does not depend only on the error type. A ValidationFailed could be an error if critical. A NotFound could be a warning if expected. Choose levels based on business impact.
Evolution
- Feb 2026 — initial version from IDENTITY.md observability positions and code review patterns.