10 - Production Engineering

What You Will Learn

• Dockerfiles for GPU inference: CUDA-compatible base images, -devel vs -runtime, multi-stage builds, why weights shouldn't be baked into the image
• Core Kubernetes objects for model serving: Deployment, Service, Ingress, HorizontalPodAutoscaler
• GPU scheduling: node pools, taints/tolerations, why GPU requests must equal limits
• Helm charts: templating deployments across environments, helm template vs --dry-run
• Model lifecycle: registries (MLflow), blue/green vs canary vs champion-challenger rollout, rollback criteria decided before launch
• Security and compliance for AI systems: IAM least privilege, secrets management, PHI/PII in traces and eval datasets, SAST/dependency scanning, HIPAA's four technical safeguards
• Building a release-readiness checklist you'd introduce in a first 90 days

Chapter Map

#	File	Topic	Difficulty
1	Docker for GPU Inference	CUDA base images, multi-stage builds, weight mounting	Intermediate
2	Kubernetes & Helm	Deployment/Service/Ingress/HPA, GPU scheduling, Helm charts	Advanced
3	Model Lifecycle & Rollout	Registries, blue/green, canary, champion-challenger, rollback criteria	Advanced
4	Security & Compliance	IAM, secrets, PHI/PII handling, SAST, HIPAA safeguards	Advanced
5	Q&A Review Bank	18+ Q&A pairs across all topics	All levels

Recommended Learning Paths

Path A: Deployment Fundamentals

1. Docker for GPU Inference - package the service
2. Kubernetes & Helm - run it in production
3. Helm Chart & Release Checklist - build the real artifact

Path B: Interview Preparation (Accelerated)

1. Kubernetes & Helm - GPU scheduling questions are common at Director/Principal level
2. Model Lifecycle & Rollout - canary vs champion-challenger is a frequent distinction to defend
3. Security & Compliance - HIPAA safeguards named precisely
4. Q&A Review Bank - drill all questions

Path C: Regulated/Healthcare Roles

1. Security & Compliance
2. Model Lifecycle & Rollout - rollback discipline matters more under regulatory review
3. Cross-reference Prior Authorization for a worked PHI-handling example

Resources

• Q&A Review Bank - 18+ Q&A pairs in this module
• Cross-topic Interview Questions

Key Cross-References

• Serving the model that gets deployed here → Serving & Inference
• Registry promotion evidence → Fine-Tuning Lab: Benchmarking Base vs Tuned
• Tracing and eval-gate infrastructure → Agentic AI: Evaluation & Observability
• PHI-handling worked examples → Prior Authorization, Smart Diagnostic Assistant

Next Topic

11 - Platform Breadth (coming soon)