What is Kubernetes-based model serving in MLOps?

Kubernetes enables scalable, fault-tolerant deployment of ML models using containers.

Kubernetes orchestrates containerized ML services, handling scaling, load balancing, and self-healing. Model serving frameworks like KFServing or Seldon deploy inference endpoints with autoscaling and canary rollout support. It ensures high availability and resource optimization across GPU/CPU workloads.