Technical Case Studies Full Book
"These are production stories — not proofs of concept."
Real-world scenarios showing how infrastructure teams deliver measurable business impact with AI workloads on Azure. Each case study maps directly to the concepts covered in this book, so you can trace every decision back to a specific chapter.
These are production stories — not proofs of concept. Every metric is grounded in realistic operational data, and every architecture decision reflects the trade-offs infrastructure engineers face daily.
What's Inside
- Case Study 1 — GPU Cluster Buildout for Large-Scale Model Training
- Case Study 2 — Infrastructure as Code for Multi-Environment ML Pipelines
- Case Study 3 — Observability Platform for GPU-Accelerated Inference
- Case Study 4 — Cost Engineering for a Mixed GPU/CPU Inference Fleet
- Case Study 5 — Multi-Team Platform Operations for AI Workloads