Reduce Complexity with Distributing Tracing
summary
Claims that distributed tracing cuts outage time by surfacing latency, root cause, critical paths and service dependencies, and demonstrates using OpenTracing/OpenTelemetry instrumentation with Jaeger on Kubernetes and service meshes to capture traces. Explains spans, span context and baggage, and using tags/logs to query specific transactions (for example by customer ID) and to identify which replica handled a request. Notes persistent storage like Elasticsearch or Cassandra is required to keep history and turn rare 0.2% failures into actionable forensic traces.
AI-written summary · about
chapters (9)
- 0:00Introduction
- 0:42Why microservices
- 6:24Migrating to microservices
- 12:28Distributed tracing basics
- 17:51Open tracing explained
- 23:01Spans and context
- 30:15Tags and logs benefits
- 32:03Span context and baggage
- 33:46Q&A and summary
related talks
49mDistributed Tracing: How the Pros Debug Concurrent and Distributed Systems
37mObservability, Distributed Tracing & the Complex World
35mNavigating the Distributed Systems Execution Maze With OpenTracing
22mDistributed Tracing
57mDistributed Tracing: How the Pros Debug Concurrent and Distributed Systems
14mLeveraging Distributed Tracing in Kubernetes & Containerized Environments
31mUnderstanding Microservices with Distributed Tracing
51mNavigating Distributed Traces
