Context Propagation

Definition

Context propagation carries execution metadata across process, service, and asynchronous boundaries.

Signals

• Logs
• Traces

Why use it

Keep the same trace connected as a request crosses services or enters a queue.

Common use cases

• Connect HTTP spans
• preserve message context
• enrich logs with the active span.

Benefits

• Provides the shared context needed for distributed tracing and log correlation.

Limitations

• Unsupported boundaries break continuity. Baggage can expose sensitive data and is not automatically copied into telemetry attributes.

Practical pattern

Inject and extract compatible trace context at boundaries. Preserve active context in asynchronous execution and allowlist baggage across trust boundaries.

Supported by

Documented examples, not an exhaustive compatibility list. Features require suitable instrumentation and configuration; availability can depend on the runtime, backend, and subscription.

• OpenTelemetry — Propagator APIs inject and extract context across supported boundaries.

Related concepts

• Correlation IDs
• Trace Correlation
• Log Correlation

Investigation patterns

• Trace to Logs
• Services to Dependencies
• User Session to Backend Trace
• Queue Producer to Consumer

Related guides

• What is Observability?
• What is MTTR?
• OpenTelemetry: Logs to Traces in Python
• OpenTelemetry: Queue Context, Retries and Batches
• Troubleshoot: Log Trace ID Not Found

FAQ

Is baggage required for tracing?

No. Trace context connects spans. Baggage carries optional application key-value data and requires separate handling.