What Network Data Can and Can’t Tell Us About AI Infrastructure

What this post added

This post analyzes network telemetry data to understand the operational demands of AI workloads. It discusses how traffic volume, connection persistence, endpoint concentration, and geographic clustering provide insights into data movement patterns. The post also emphasizes the limitations of interpreting a single quarter of data, highlighting the need for longer-term trend analysis and flexible infrastructure design in the rapidly evolving AI landscape. It explains how network telemetry can inform infrastructure planning by revealing practical questions about sustained high-throughput networking, storage and compute coupling, and regional infrastructure concentration.