What is the Distributed Tracing pattern and how do trace context headers propagate across services?

Distributed Tracing reconstructs the end-to-end path of a single request as it flows across multiple microservices, providing a flamegraph of timings that reveals where latency accumulates and where failures occur. Without it, correlating logs from 10 services for a single slow request requires manual, error-prone cross-referencing.

Key concepts:

• Trace — the complete journey of a request, identified by a globally unique traceId. All spans belonging to the same originating request share this ID.
• Span — a named, timed unit of work within a single service (e.g., "HTTP GET /orders/42", "DB SELECT orders", "Kafka publish OrderPlaced"). A span records start time, duration, service name, tags (metadata), and the parentSpanId linking it to its caller.
• Context propagation — the tracing library injects the trace context into outbound call headers; the receiving service extracts it and creates a child span with the correct traceId and parentSpanId.

# W3C Trace Context header (standard across OpenTelemetry, Jaeger, Zipkin)
traceparent: 00-4bf92f3577b34da6a3ce929d0e0e4736-00f067aa0ba902b7-01
#            version-traceId(128-bit hex)       -spanId(64-bit)-flags

# Outgoing HTTP request from Service A to Service B includes this header.
# Service B extracts traceId + parentSpanId, creates its own child span.
# All spans are sent asynchronously to Jaeger / Zipkin / AWS X-Ray.

Two propagation standards are in common use:

• W3C Trace Context (traceparent + tracestate headers) — the IETF standard, supported natively by OpenTelemetry.
• Zipkin B3 headers (X-B3-TraceId, X-B3-SpanId, X-B3-ParentSpanId, X-B3-Sampled) — older but still widely used by Istio, Zipkin, and some Jaeger deployments.

For async messaging, the trace context is injected into message headers (Kafka record headers, AMQP headers) so traces span across broker boundaries.

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