KEMU: A Declarative Approach to Emulating Kubernetes Clusters at Scale
·13 mins
Optimizing AI workload scheduling requires extensive experimentation and observation, but testing scheduler modifications in production is risky - configuration errors can cause multi-day delays and wasted capacity. This post introduces KEMU, a declarative Kubernetes Emulator Utility that replaces fragmented multi-tool cluster setups with a single configuration specification, enabling safe experimentation with large-scale GPU clusters on minimal resources.