Distributed Tracing Explained: How to Find Bottlenecks Across Microservices

Distributed tracing fills a critical gap in observability that logs and metrics alone cannot address, by mapping the full journey of a single request across multiple services. Unlike dashboards that show per-service latency in isolation, a trace can pinpoint the exact database query or downstream call causing slowness. OpenTelemetry has emerged as the standard implementation, offering auto-instrumentation for HTTP calls and database queries with minimal setup, while custom spans can capture business-specific context like order IDs. Because tracing every production request is cost-prohibitive, tail sampling allows teams to retain 100% of error and slow traces while discarding most routine ones. Common pitfalls include failing to propagate trace context between services, over-sampling at the start, and omitting business identifiers that make traces actionable during debugging.