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JAEGER
End-to-end distributed tracing for microservices and AI pipelines
Apache-2.0
ABOUT
In distributed systems — including LLM serving stacks with multiple model replicas, vector databases, and API gateways — a single user request fans out across dozens of services. Debugging latency spikes or errors without request-level context is nearly impossible. Jaeger provides end-to-end distributed tracing: it captures the full path of each request as it traverses services, showing spans, timing, and errors on an interactive timeline.
INTEGRATION GUIDE
1. Trace multi-step LLM inference requests across model servers, caches, and databases
2. Identify slow services in an agent orchestration pipeline by visualizing span timing
3. Correlate errors in production AI systems with upstream service failures
4. Monitor tail latency distributions across distributed model serving infrastructure
5. Debug performance regressions after deploying a new model version or routing change
TAGS
distributed-tracingobservabilitymicroservicesmonitoringopentelemetrycncf