Observable microservices
summary
Describes concrete practices for running microservices in production: use JSON structured logs and a centralized ELK or Splunk pipeline; standardize a few key log dimensions and seed service templates; expose a health endpoint that also validates downstream streams and DBs; track business KPIs via semantic monitoring and synthetic transactions; generate a correlation/trace ID per request and ingest traces into Zipkin/Jaeger/LightStep; example: a new service in a 3+ million‑visitor marketplace adds stream checks, REST output and monitoring and works in production.
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chapters (16)
- 0:00Intro
- 0:16PRINCIPLES OF MICROSERVICES
- 7:00LOG AGGREGATION
- 7:47LOG STRUCTURED DATA
- 8:56TRACK BUSINESS AND SYSTEM EVENTS
- 9:32STANDARDIZE
- 14:00EXAMPLE
- 17:38SEMANTIC MONITORING
- 23:10ALERTS SHOULD BE ACTIONABLE
- 24:01SMART ALERTS
- 28:27ABILITY TO FIND THE ORIGIN OF A REQUEST
- 29:24LOG AGGREGATOR
- 30:46REQUEST GRAPH
- 31:22DISTRIBUTING TRACING TOOLS
- 31:54STANDARDS
- 32:43SUMMARY
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