Designing NVIDIA AI Infrastructure
GPU compute, networking, orchestration, and security in NVIDIA's stack, explained
Created by Vivian Aranha
Get a clear understanding of NVIDIA's AI infrastructure stack, including GPU sharing, networking, orchestration, and security. Learn how these components work together to support AI workloads and how to make informed architecture decisions for various deployment scenarios.
Packt | Aug 2026 | 134 min
What You Will Learn
You will explore key concepts through clear explanations, real-world architecture diagrams, and configuration examples. Each section connects technologies to operational scenarios, helping you build a mental model for making design and troubleshooting decisions in enterprise environments.
Key Features
- Gain practical knowledge of GPU sharing, orchestration, and resource models
- Understand how networking, storage, and security shape AI infrastructure
- Learn to evaluate design choices for cloud, on-premises, and edge deployments
Target Audience
Ideal for infrastructure engineers, MLOps professionals, solutions architects, and technical leads who want a reliable understanding of NVIDIA's AI stack. If you have experience with Linux, containers, or cloud platforms and need to design or evaluate GPU-powered systems, this course will help you bridge knowledge gaps and make confident decisions.
