CPU queueing with Kueue and Ray

Use this example when you want to understand the scheduling layer beneath TauGrid using only the CPU capacity you already have. It submits raw RayJobs to Kueue and makes admission, pending work, and team borrowing visible.

This is a platform mechanics example that demonstrates Kueue/Ray scheduling directly, distinct from the TauGrid researcher workflow.

Prerequisites

• a disposable or explicitly approved Kubernetes context;
• Kueue and KubeRay installed;
• kubectl access that can create namespaces, queues, and RayJobs; and
• enough CPU capacity for two small Ray workloads.

Run the single-queue demonstration

git clone https://github.com/Azure/taugrid-examples.git
cd taugrid-examples/aks-blog/kueue-ray-cpu

./demo.sh single

The script applies the single-queue resources and enqueues two raw RayJobs. In a second terminal, watch admission:

kubectl get workloads -A --watch
kubectl get rayjobs -A
kubectl get pods -A

The demo includes a shared-context safety guard. Do not bypass it with --allow-shared-context unless the target cluster is intentionally approved for these resources.

What to carry back to TauGrid

TauGrid adds reviewed configuration, workspace policy, queue resolution, and lifecycle commands on top of the objects shown here. Use this example to understand why a TauGrid run can be submitted but still wait for admission.

Continue with queue, quota, and GPU placement or the operator troubleshooting path.

See the complete example README for the team-borrowing mode and manual manifest path.