Practices for implementing effective logging in distributed systems: structured logging, levels, correlation, and centralized aggregation.
Effective logging in distributed systems goes beyond console.log. It requires structure, cross-service correlation, appropriate levels, and centralized aggregation to be useful for debugging and auditing.
Logs in JSON format instead of plain text:
{"level":"info","msg":"Order created","orderId":"123","userId":"456","traceId":"abc","timestamp":"2026-03-16T10:00:00Z"}Benefits: efficient search, field filtering, automatic parsing.
| Level | Use |
|---|---|
| DEBUG | Development detail |
| INFO | Normal business events |
| WARN | Unexpected non-critical situations |
| ERROR | Failures requiring attention |
Include traceId and requestId in every log to trace a request across multiple services.
Logs are the first diagnostic tool when something fails. Structured logs, with appropriate levels and cross-service correlation, turn hours of debugging into minutes. Unstructured logs are noise that hides the signal.
Ability to understand a system's internal state from its external outputs: logs, metrics, and traces, enabling problem diagnosis without direct system access.
Cloud computing model where the provider manages infrastructure automatically, allowing code execution without provisioning or managing servers, paying only for actual usage.
Observability technique tracking requests across multiple services in distributed systems, enabling bottleneck identification and failure diagnosis.