Demystifying Fractional GPUs in Kubernetes: MIG, Time Slicing, and Custom Schedulers

GPU sharing in Kubernetes can be achieved through three main approaches: MIG provides hardware-level isolation for production workloads but requires specific NVIDIA GPUs and static configuration; time slicing offers flexible dynamic sharing across any NVIDIA GPU but with weaker isolation; custom schedulers like KAI enable fine-grained fractional GPU allocation with high configurability but require cluster modifications. The choice depends on hardware constraints, workload requirements, and isolation needs.