Code Lab - 01: Helm Chart & Release Checklist

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This lab packages the Serving & Inference FastAPI + vLLM endpoint as a real deployable artifact - a Dockerfile, a Helm chart with autoscaling, and a one-page release-readiness checklist you could hand to a team on day one of an on-call rotation.

Lab Overview

Property	Detail
Patterns	GPU Dockerfile, Helm templating, HPA autoscaling
Deploys	The Module 09 FastAPI + vLLM serving endpoint
Complexity	Intermediate
Files	Dockerfile, helm-chart/, release-readiness-checklist.md

What's Inside

01-Helm-Chart-and-Release-Checklist/
  README.mdx                        - architecture, what this demonstrates, how to run it
  Dockerfile                        - multi-stage GPU inference image
  helm-chart/
    Chart.yaml
    values.yaml                     - image, replica count, GPU resources, autoscaling bounds
    templates/
      deployment.yaml
      service.yaml
      hpa.yaml
  release-readiness-checklist.md    - the standalone "first 90 days" artifact

Prerequisites

• Docker with nvidia-container-toolkit for local GPU testing (optional - helm lint/--dry-run don't need a GPU)
• helm v3 and kubectl pointed at any cluster (a local kind/minikube cluster is enough to validate)

Getting Started

cd 01-Helm-Chart-and-Release-Checklist
helm lint helm-chart/
helm install --dry-run vllm-serving helm-chart/ -f helm-chart/values.yaml

What to Read Alongside

• Docker for GPU Inference
• Kubernetes & Helm
• Model Lifecycle & Rollout - the checklist operationalizes this note