Node-level enforcement and metrics for fractional GPU allocations made by KAI Scheduler.
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Updated
Oct 26, 2026 - Go
Node-level enforcement and metrics for fractional GPU allocations made by KAI Scheduler.
Hands-on GPU/HPC infrastructure operations: K8s GPU scheduling, HAMi sharing, Slurm, observability & vLLM inference. Learn it free on a laptop; validate on one cheap GPU.
Visual planner for KAI Resource Management (KRM) GPU quotas: rebalance departments and projects, catch over-commitment before it is applied, and get kubectl commands or a local commit.
One open-source platform to schedule, serve, benchmark and observe LLMs on NVIDIA and AMD GPUs (Run:ai, Dynamo, AIPerf)
Open-source multi-cluster AI inference platform. Define functions once, deploy anywhere with KV-cache-aware smart routing, multi-tenancy, and autoscaling. Built on SkyPilot, vLLM, KAI Scheduler.
Benchmark Kubernetes GPU schedulers (default, Kueue, Volcano, KAI) on identical AI workload traces: utilisation, fragmentation, queue wait, fairness and cost. No GPUs needed.
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