Load Testing AI: Aiming at a Moving Target

AI-powered features are everywhere, but most teams are still load testing these like traditional APIs. That’s a problem! AI systems behave differently under pressure with latency spikes, token limits, cascading failures, and unpredictable cost explosions.

This talk examines how to load test AI-backed applications realistically, accounting for non-deterministic responses, variable execution times, and external dependencies. We’ll break down common failure patterns seen in production AI systems and walk through practical strategies to simulate real user behavior at scale. A short demo will show how to design scenarios that test both performance and resilience.

What you’ll gain: - How AI workloads differ from classic web/API traffic - Patterns for modeling realistic AI usage under load - Techniques to test latency, throughput, and cost boundaries - How to turn AI performance tests into actionable insights