Add ai-ml/gke-ray/kueue-concurrent-admission: ephemeral RayJobs with Kueue Concurrent Admission - #2149
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Add Kueue setup and ephemeral RayJob manifests demonstrating Kueue's Concurrent Admission feature on GKE, along with sample documentation. - kueue-setup.yaml: ResourceFlavor, ClusterQueue, LocalQueue - ephemeral-rayjob.yaml: RayJob using local queue and GPU resources - README.md: Overview and quickstart commands
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Description
This PR adds a new sample under
ai-ml/gke-ray/kueue-concurrent-admissionthat demonstrates how to runephemeral RayJobs across multiple resource flavors using Kueue's Concurrent Admission feature on GKE.
Concurrent Admission lets a
ClusterQueueevaluate multipleResourceFlavors at the same time, so anephemeral RayJob can start on whichever flavor has capacity first (for example, a reservation-backed GPU
node pool or a DWS Flex-Start node pool) instead of waiting on strict flavor ordering. This reduces
RayJob start latency for bursty, short-lived GPU workloads.
These manifests back the user guide
Start RayJobs faster across multiple resource flavors.
Files added
ai-ml/gke-ray/kueue-concurrent-admission/kueue-setup.yamlResourceFlavors (reservation-flavor,dws-flex-flavor), aClusterQueuewithconcurrentAdmissionPolicy(migration.mode: TryPreferredFlavors,constraints.lastAcceptableFlavorName: reservation-flavor), and aLocalQueue(user-queue).ai-ml/gke-ray/kueue-concurrent-admission/ephemeral-rayjob.yamlRayJob(shutdownAfterJobFinishes: true) labeled withkueue.x-k8s.io/queue-name: user-queue, running 3 single-GPU Ray tasks on 3 worker replicas.ai-ml/gke-ray/kueue-concurrent-admission/README.mdNotes
kueue.x-k8s.io/v1beta2API, which is required forconcurrentAdmissionPolicy.kueue.x-k8s.io/queue-namelabel (not an annotation), consistent with Fix kueue.x-k8s.io/queue-name metadata field #2052.gke_ai_ml_gke_ray_kueue_concurrent_admission_kueue_setupandgke_ai_ml_gke_ray_kueue_concurrent_admission_ephemeral_rayjob.Tasks