Why AI‑Specific Gateways are essential for Kubernetes LLM workloads
Traditional API gateways choke on token‑based pricing, variable latency, and prompt routing that AI workloads demand. An AI gateway adds model‑aware routing, token cost tracking, semantic caching, and multi‑LLM federation, letting Kubernetes teams serve LLMs at scale without the performance and compliance pitfalls of classic gateways.