12 min read · Free guide

The AI Infrastructure Buying Guide

How to scope AI infrastructure that actually trains and serves models — GPUs, fabric, storage, power, cooling, and software — without over- or under-buying.

What's inside

Right-sizing GPUs to training vs. inference workloads
Why the network fabric (not the GPU) is usually the bottleneck
Storage and data-pipeline throughput for AI
Power, cooling, and liquid-cooling realities at rack scale
The software stack: orchestration, MLOps, and observability
A procurement checklist (TAA, GSA/SEWP, lead times)