AI for Infra Pros¶
The Practical Handbook for Infrastructure Engineers Entering the AI Era
"You don't need to be a data scientist to work with AI — but you do need to understand how it runs, scales, breaks, and costs money."
15 Chapters in 5 Parts
61K+ Words
220+ Pages
3 Hands-On Labs
10 Troubleshooting Scenarios
55+ AI Terms in Glossary
About This Book¶
Every AI model that reaches production sits on top of infrastructure someone had to build, scale, secure, and keep running. That someone is you.
This handbook was born from years of bridging the gap between systems engineering and machine learning. It translates AI concepts into the language infrastructure, cloud, and DevOps engineers already speak — and gives you the practical depth to architect, deploy, monitor, and operate AI workloads at production scale.
This is not an AI/ML textbook. It's a practitioner's handbook. Every chapter includes production-grade examples, decision matrices, hands-on labs, and the kind of hard-won lessons that only come from running AI infrastructure in the real world.
What's Inside¶
GPU & Compute VM families, CUDA vs Tensor Cores, nvidia-smi, and the memory math behind OOM errors
Data Pipelines Storage architecture, BlobFuse2, NVMe staging, and why I/O is the hidden bottleneck
Infrastructure as Code Production-ready Terraform and Bicep for GPU clusters, AKS node pools, and CI/CD
MLOps Model registries, CI/CD for models, A/B testing infrastructure, and supply chain security
Monitoring & Observability DCGM, Managed Prometheus, KQL queries, and the six dimensions of AI observability
Security Prompt injection defense, private endpoints, managed identities, and content safety
Cost Engineering GPU cost modeling, spot VMs for training, PTU economics, and FinOps practices
Platform Ops at Scale Multi-tenancy, GPU scheduling (Kueue, Volcano), SLA design, and fleet management
Troubleshooting 10 real-world failure scenarios with step-by-step diagnosis and resolution
Career Paths AI Infra Engineer, MLOps Engineer, AI Platform Engineer, and a 30-day plan
Get the Book¶
AI for Infra Pros — Full Book
$35 PDF, ePub, and MOBI · Free lifetime updates
- All 15 chapters (220+ pages)
- 3 hands-on labs with IaC templates
- 10 production troubleshooting scenarios
- Case studies, cheatsheets, and technical FAQ
- PDF, ePub, and MOBI formats
- Free lifetime updates
Read Free Chapters¶
Start reading now — these chapters are available for free right here on the site:
Chapter 1 Why AI Needs You The infrastructure engineer's case for entering the AI world
Chapter 4 The GPU Deep Dive CUDA, memory hierarchy, multi-GPU strategies, and debugging
Chapter 15 Visual Glossary 55+ AI terms explained through infrastructure analogies
Hands-On Labs All 3 Labs GPU VM with Bicep, AKS with Terraform, Inference API with Azure ML
Who This Book Is For¶
This handbook is written for professionals with 5+ years of infrastructure experience who are new to AI but technically sharp:
- Infrastructure and Cloud Engineers (Azure, AWS, GCP)
- DevOps and Site Reliability Engineers
- Solutions and Cloud Architects
- Platform Engineers
- Security and Governance Professionals
- Data Engineers who want to understand the infrastructure side of AI
No prior AI/ML knowledge is required. Every concept is explained through infrastructure analogies you already know.
About the Author¶
Created by Ricardo Martins
Principal Solutions Engineer @ Microsoft Author of Azure Governance Made Simple and Linux Hackathon rmmartins.com
"AI needs infrastructure. And infrastructure needs engineers who understand AI. This book is the bridge."
Disclaimer: This is an independent, personal project — not an official Microsoft publication. The views and content are solely the author's own. While many examples use Azure, the concepts, architectures, and operational practices in this book apply to any cloud platform — AWS, GCP, or on-premises. If you manage infrastructure, this book was written for you, regardless of your cloud provider. All trademarks and product names belong to their respective owners.