Why your Kubernetes scheduler can't handle AI workloads

This post identifies and explains the limitations of the default Kubernetes scheduler for AI workloads, specifically partial-scheduling deadlocks due to lack of gang scheduling and performance degradation from missing multi-node fabric topology awareness. It then introduces and compares three alternative schedulers: Kueue (queueing and quota management), KAI Scheduler (AI-native scheduling with GPU awareness and topology optimization), and Volcano (mature batch scheduling with gang scheduling and framework integration). It also outlines common deployment patterns like Kueue + Volcano, KAI Scheduler Standalone, and Volcano Standalone.