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

This post analyzes network telemetry data to understand the characteristics of AI infrastructure traffic. It details how network volume, connection persistence, endpoint concentration, and geographic patterns reveal operational demands. The post highlights that while network data shows current AI workload behavior (e.g., elephant flows, regional clustering), it cannot definitively predict future infrastructure design due to the rapid evolution of AI technologies and compute availability. It emphasizes that interpreting network telemetry requires observing trends over multiple quarters and that flexible, interoperable tech stacks are crucial for adapting to the dynamic AI ecosystem.