Kubernetes for AI Services
You'll start by building your kubernetes-deployment skill in Chapter 1, then progressively refine it through core and specialized chapters. The FastAPI agent from Module 6 is the primary application you'll deploy, manage, and harden on Kubernetes.
Goals
- Understand Kubernetes Architecture: Control plane, nodes, and the declarative state model.
- Master Workload Objects: Deploy and operate Pods, Deployments, Services, Jobs, and CronJobs.
- Configuration & Isolation: Manage application settings with ConfigMaps/Secrets and namespace isolation.
- Resource Profiling & Scaling: Configure resource requests/limits, HPA, and rolling updates.
- Cluster Hardening: Implement RBAC, health probes, and production best practices.
- AI-Assisted Manifests: Use kubectl-ai to generate and evaluate complex manifests.
- Develop Reusable Patterns: Produce a production-grade Kubernetes deployment skill.
Chapter Progression
Outcome & Method
You'll finish with your Module 6 FastAPI agent running on Kubernetes—fully secured, health-checked, and autoscaled—alongside a robust Kubernetes deployment skill. The 4-Layer progression moves from fundamental concepts to AI-assisted manifest generation, culminating in a specification-driven capstone and optional deep dives for advanced architectural patterns.
Prerequisites
- Module 7 Sub-module 1: Container image pushed to a Docker registry.
- Local Cluster: Docker Desktop with Kubernetes enabled (or an equivalent k8s cluster).
- CLI Familiarity: Basic terminal skills; prior Kubernetes experience is not required.