AI App Delivery Top 10: Unoptimized Traffic Steering
F5, Thursday, July 2nd, 2026
F5 explains why traditional traffic-steering assumptions break down in unpredictable AI environments.
This entry in F5's AI App Delivery Top 10 series argues that traditional traffic-steering approaches fail when AI workloads are unpredictable and backend resources vary widely in capability. Without optimized steering, organizations end up with overloaded paths, underutilized capacity, and bottlenecks that degrade the whole system.
F5 recommends segmenting traffic into distinct lanes, implementing programmable routing rules that respond to real-time conditions, and aligning traffic with data locality. The goal is to keep AI inference performant and cost-efficient at scale.