observability

Structured logging and traceId propagation are implemented by enforcing JSON log schemas with required fields like ISO8601 timestamps and passing the traceId via the x-trace-id header across microservices. Storing trace context in AsyncLocalStorage ensures all logs within a request share the same identifier.

The /health/live and /health/ready endpoints serve distinct readiness purposes: /health/live checks if the application process is running, while /health/ready verifies dependency checks to gate load balancer traffic based on true service availability.

Prometheus metrics for distributed environments are exposed by defining and instrumenting counters and histograms like http_requests_total, http_request_duration_seconds, and db_query_duration_seconds to support SLOs and alerting.

While the standard is designed for Node.js and similar backend services, the observability principles apply universally. Any distributed environment can enforce JSON structured logs, x-trace-id propagation, health endpoints, and Prometheus metrics.

Required fields in a JSON structured log schema for centralized parsing include timestamp (ISO8601 with milliseconds), level, traceId, module, action, and message to enable reliable querying across observability pipelines.

Inconsistent logging makes incident detection slow because missing trace propagation and fragmented metrics prevent reliable correlation across services, making debugging and alerting error-prone without a single enforceable observability standard.