How to Do Microservice Observability with OpenSearch
summary
Live demo of an e‑commerce microservice pipeline shows instrumentation with the OpenTelemetry collector, log forwarding via FluentBit and Data Prepper, and storage/visualization in OpenSearch. Real‑time trace groups and a service map let operators click a trace ID, jump to correlated logs, and find a checkout/payment failing with a 503 error. App availability is tunable (examples use 100–300 ms thresholds), and built notebooks assemble dashboards and traces into reports exportable to PDF. Workshop code and hands‑on sessions are provided.
AI-written summary · about
chapters (12)
- 0:00Microservice observability intro
- 7:55Why microservices need observability
- 10:03Observability tooling landscape
- 13:14OpenTelemetry data flow
- 15:46OpenSearch observability features
- 18:31Demo architecture & trace flow
- 19:35Trace analytics in OpenSearch
- 21:19Event analytics & log correlation
- 24:52App availability monitoring
- 27:01Performance insights panels
- 28:46Root cause analysis notebooks
- 31:58Next steps & resources
related talks
20mSeeing Is Believing: OpenTelemetry and OpenSearch in Next-Gen Observability
22mFrom Telemetry to Insight: Building AI-Powered Observability Pipelines with OpenSearch
37mBuilding Modern Observability Architecture With OpenSearch, OS Ingest...
29mOpenTelemetry With OpenSearch: Use-Cases, Status and Roadmap
26mPlug-and-Play Observability: OTel Auto-Instrumentation for LLMs in OpenSearch
11mOpenTelemetry + OpenSearch Integration
21mKubernetes Under the Magnifying Glass: Observability With OpenSearch
06mSponsored Keynote: OpenSearch - See Everything: Open Observability for Agentic AI
