LLM inference has unique challenges—long prompts, token-by-token generation, bursty traffic, and the need for high GPU utilization—making routing, scheduling, and autoscaling harder than standard ML serving. This talk covers how KServe enables scalable, cost-efficient, Kubernetes-native LLM inferenc