The GPU Shortage Inside Your Own Infrastructure: Why AI Workloads Queue While Capacity Sits Idle

AI workloads often queue despite GPUs showing low compute utilization because GPU allocation, memory, and placement constraints limit actual availability. Kubernetes assigns whole GPUs to pods, blocking others even if usage is low. Different GPU sharing methods have tradeoffs and no single solution fits all workloads.