Opentelemetry

A request hits your API gateway, bounces through five microservices, touches two databases, and returns an error. Logs say “something failed.” Which service? Which call? What was the payload? Distributed tracing answers these questions by connecting the dots across service boundaries. The Core Concepts Traces and Spans A trace represents a complete request journey. A span represents a single operation within that journey. T ├ │ │ │ │ │ │ r ─ a ─ c e S ├ ├ │ └ : p ─ ─ ─ a ─ ─ ─ a n b : S S └ S ├ └ c p p ─ p ─ ─ 1 A a a ─ a ─ ─ 2 P n n n 3 I : : S : S S p p p G A U a O a a a u s n r n n t t e : d : : e h r e w D r I P a S S a n a y e e t S v y r r a e e m ( v v b r n e p i i a v t n a c c s i o t r e e e c r e e y P n Q r t u C o ) e h c r e e y c s k s i n g Each span has: ...

When a request fails in a distributed system, the question isn’t if something went wrong—it’s where. Logs tell you what happened. Metrics tell you how often. But tracing tells you the story. The Problem with Logs and Metrics Alone You’ve got 15 microservices. A user reports slow checkout. You check the logs—thousands of entries. You check the metrics—latency is up, but which service? You’re playing detective without a map. This is where distributed tracing shines. It connects the dots across service boundaries, showing you the exact path a request takes and where time is spent. ...