Microsoft has open-sourced #TauGrid, a cloud-native AI infrastructure platform designed to make running GPU workloads on Kubernetes easier.TauGrid brings several pieces together into a single stack:• A CLI for submitting and managing AI workloads• Kueue for workload queueing, quotas, and scheduling• KubeRay for distributed AI workloads• GPU health monitoring and node diagnostics• Integrated observability for clusters, GPUs, and workloadsIt supports workloads across data preparation, distributed training, fine-tuning, batch inference, and model serving.The interesting part is the separation of responsibilities. Researchers can submit and monitor workloads without needing to manage Kubernetes directly, while platform teams retain control over compute, capacity, identity, policies, and infrastructure.For organizations running GPU-intensive AI workloads, this could provide a more standardized way to manage shared Kubernetes-based AI infrastructure without building all of the integration gl...
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