Modern generative AI and large language model (LLM) services create unique traffic-routing challenges on Kubernetes. Unlike typical short-lived, stateless web requests, LLM inference sessions are often long-running, resource-intensive, and partially stateful. For example, a single GPU-backed model server may keep multiple inference sessions active and maintain in-memory token caches. Traditional load balancers focused on HTTP path or round-robin lack the specialized capabilities needed for th...
