Deploy Python Apps on Kubernetes and Prepare for Scale
summary
Shows a reproducible path: a Dockerized Flask/Django workflow, a search-in-a-box project that adds 100% unit test coverage, a Parquet-backed crawler, and a working deployment on MiniKube demo exposing Deployments, Services, Ingress, PersistentVolumes and ConfigMaps. Shows how the same YAML patterns run a GPU-backed LLM from Hugging Face with Ray for inference, how autoscaling behaves, and that the toy app successfully serves real queries when replicas increase.
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chapters (7)
- 0:00Introduction to the topic
- 3:28Evolution of orchestration
- 6:36Search engine as a template
- 12:21Kubernetes core concepts
- 16:11Deployment and networking
- 18:55Scaling Python applications
- 23:31Machine learning on Kubernetes
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