Containers and #Kubernetes Made Easy Deep Dive into Podman Desktop
summary
Podman Desktop shows an end-to-end workflow: it builds a Flask guestbook and Redis image, runs two containers (ports 5000→501 mapped), collapses them into a single pod and deploys the generated Kubernetes YAML to a local kind cluster exposed on localhost:9090 — the demo runs successfully. The AI Lab spins up LLaMA/mistralai model servers (local API on port 801), uses Chroma vector DB and LangChain for a RAG pipeline (PDF uploaded, retrieval returns correct citation), and outlines production serving with kserve and GPU pass-through.
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chapters (13)
- 0:00Introduction and welcome
- 1:02What is Podman and Podman Desktop
- 8:02Building containers from source
- 12:36Converting containers to pods
- 13:38Deploying to Kubernetes
- 16:04Developer sandbox for Kubernetes
- 19:17AI integration with Podman Desktop
- 22:29AI Lab extension overview
- 23:35Building RAG applications
- 30:19Adding AI to Java apps
- 34:33AI models in production
- 36:59GPU acceleration for AI
- 37:43Q&A session
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