“dynamic-resource-allocation”

AI Workloads on Kubernetes: GPUs, Inference, and Serving

From device plugins to Dynamic Resource Allocation (GA since Kubernetes 1.34), GPU sharing with MIG and time-slicing, accelerator node pools, and how scheduling and serving stacks like KServe and vLLM differ for training versus inference.