GPUStack Operator provides a fantastic way to manage accelerator resources in Kubernetes.
Built on top of Node Feature Discovery and Kueue, it discovers accelerators (GPU/NPU/TPU) on every node, profiles node capacity into normalized per-device units, and materializes the results into a Kueue-based scheduling chain (ResourceFlavor → ClusterQueue → Cohort / LocalQueue).
A single gpustack-operator binary exposes three subcommands — worker (control plane), worker-gateway (cross-cluster aggregation), and device-manager (per-node DaemonSet) — that drive a four-stage chain:
- Bootstrap — the Worker installs the NFD and Device Manager DaemonSets.
- Device discovery — Node Feature Discovery labels nodes by PCI vendor and CPU identity; the Device Manager then detects accelerators and reports per-device feature labels.
- Capacity profiling — the Worker normalizes each node's CPU/RAM/storage and per-accelerator capacity into profile labels, keyed by the node's CPU identity.
- Queue construction — four Worker controllers materialize the labels into Kueue
ResourceFlavor,Cohort,ClusterQueue, andLocalQueueobjects.
See Architecture for the stage-by-stage detail, label/naming conventions, and a worked example cluster.
- Architecture — how device discovery, node capacity profiling, and the Kueue scheduling chain work, with a worked example cluster.
- Development — build, lint, test, code generation, and dependency management commands.
- Environment Variables — every
GPUSTACK_*knob, per-manufacturer overrides, and vendor toolkit paths.
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