logging-guidelines

Structured logging formats data as JSON with consistent fields like trace_id, span_id, and correlation_id. This standardization captures full request context across services, enabling unified observability and faster incident response compared to plain text logs.

Configure Pino to emit a single, richly-detailed log per request ensuring error-first logging, snake_case field naming, and proper PII redaction. Include trace_id, span_id, and correlation_id to capture full request context for efficient debugging and incident response.

Yes, apply this standardized structured logging across services to capture full request context and high-cardinality identifiers. It enforces 100% visibility for failures and includes correlation context like trace_id and span_id for unified observability.

Apply tail sampling to reduce log noise while preserving critical signals. Combine this with error-first logging to enforce 100% visibility for failures, ensuring structured JSON logs capture full request context without overwhelming your observability platform.

Including trace_id, span_id, and correlation_id in logs captures full request context across services. This correlation context enables unified observability and efficient debugging by linking related log entries across distributed systems during incident response.

Apply tail sampling when you need to reduce log noise while preserving critical signals. Combine it with structured JSON logging and error-first visibility to ensure failures and full request context are captured without overwhelming your observability platform.