Articles tagged with "gpu-scheduling"
Building edge AI inference on K3s runs into standard Kubernetes GPU resource management (integer units, request=limit). Here's how to share one GPU across multiple models, and what to watch for with time-slicing.
Ten years after Kubernetes launched, AI agents and LLM inference have upended three of its core assumptions: how GPUs are allocated, how autoscaling decisions are made, and how model serving is built. Here's how to rethink your K3s cluster with Dynamic Resource Allocation, KEDA, and KServe.
Generative AI has made it possible for almost anyone to write code, yet as more companies adopt AI, demand for MLOps talent who can reliably run GPUs and model serving on Kubernetes keeps rising. Here's why, and how a managed Kubernetes platform can help.