Event-Driven Autoscaling for Serverless Java

on YouTube ↗52m

" summary

Shows that replacing HPA-only scaling with KEDA + Knative + Quarkus targets event metrics (Kafka, SQS) rather than CPU, so KEDA handles 0→1 cold starts and then invokes HPA for larger scale. Demo consumes 5 million Kafka messages, Quarkus consumers scale to up to 10 pods, Knative scales to zero in ~30s, and a sandbox integration combines KEDA and Knative so event scrapers trigger high-concurrency scale-outs. The setup is implemented on OpenShift and the demos work as shown.

AI-written summary · about

" chapters (11)

1. 0:00Introduction and speaker intro
2. 4:12Kubernetes auto scaling basics
3. 9:06Introducing KEDA for event-driven scaling
4. 14:08KEDA vs serverless behavior
5. 19:05Kubernetes vs KNative for serverless
6. 22:37Demo 1: Traditional HPA limitations
7. 28:42Why Quarkus for demos
8. 35:27Demo 2: KEDA event-driven scaling
9. 38:38KNative serverless architecture
10. 44:46Demo 3: KEDA and KNative integration
11. 51:35Conclusion and Q&A

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