Implement distributed tracing with correlation IDs, trace propagation, and span tracking across microservices. Use when debugging distributed systems, monitoring request flows, or implementing observability.

Correlation & Distributed Tracing Table of Contents [Overview]( overview) [When to Use]( when to use) [Quick Start]( quick start) [Reference Guides]( reference guides) [Best Practices]( best practices) Overview Implement correlation IDs and distributed tracing to track requests across multiple services and understand system behavior. When to Use Microservices architectures Debugging distributed systems Performance monitoring Request flow visualization Error tracking across services Dependency analysis Latency optimization Quick Start Minimal working example: Reference Guides Detailed implementations in the references/ directory: Guide Contents [Correlation ID Middleware (Express)](references/correlation id middleware express.md) Correlation ID Middleware (Express) [OpenTelemetry Integration](references/opentelemetry integration.md) OpenTelemetry Integration [Python Distributed Tracing](references/python distributed tracing.md) Python Distributed Tracing [Manual Trace Propagation](references/manual trace propagation.md) Manual Trace Propagation Best Practices ✅ DO Generate trace IDs at entry points Propagate trace context across services Include correlation IDs in logs Use structured logging Set appropriate span attributes Sample traces in high traffic systems Monitor trace collection overhead Implement context propagation ❌ DON'T Skip trace propagation Log without correlation context Create too many spans Store sensitive data in spans Block on trace reporting Forget error tracking

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