Empowering Quarkus Applications with AI and OpenTelemetry on Kubernetes
summary
Demo shows a Quarkus app instrumented with OpenTelemetry, packaged by Maven (kubernetes manifests auto-generated), pushed to Azure Container Registry and deployed to AKS with kubectl; an OpenTelemetry Collector and operator run as pods and telemetry exports to Log Analytics/Jaeger. A Postgres-backed Microsweeper app receives a 300 virtual users load test, CPU stays ~2–3% so no autoscale triggers, and GitHub Copilot chat generates working otel config YAML and a OpenTelemetry operator deployment.
AI-written summary · about
chapters (13)
- 0:00Welcome
- 1:50Observability for Java apps
- 4:02OpenTelemetry standard
- 5:46Microsweeper demo app
- 7:12Deploying to AKS
- 9:25Building Quarkus app
- 13:22Deploy with manifests
- 14:45AKS benefits
- 15:30GitHub Copilot telemetry
- 19:48Automate OpenTelemetry on AKS
- 20:50Quarkus OpenTelemetry integration
- 22:36Analyzing telemetry data
- 25:32Jaeger Zipkin visualization
related talks
42mDistributed Tracing Integration with OpenTelemetry and Knative
46mKubernetes. From 0 to Production-Grade with Java.
49mKubernetes. From 0 to Production-Grade with Java
34mDistributed Tracing Integration with OpenTelemetry and Knative
58mBuilding Observable Java Apps that Scale with Quarkus
45mInstrument Your Native Spring Boot and Quarkus Applications with OpenTelemetry
28mDistributed Tracing Integration with OpenTelemetry and Knative _ _ _
08mOpenTelemetry and Quarkus