Setting the file. One moment.
Subchapter 2.4
references/kaito-workspaces.mdMarkdown2 KBView on GitHub
This is diagnosis only. Route add-on enablement, Workspace creation, model
selection, and provider selection to airunway-aks-setup.
kubectl get workspace <workspace> -o yaml
kubectl describe workspace <workspace>
az aks show --subscription <subscription> -g <resource-group> -n <cluster> \
--query '{id:id,location:location,provisioningState:provisioningState}' -o json
az vm list-usage --location <region> -o json
az vm list-skus --location <region> --resource-type virtualMachines \
--all -o jsonMicrosoft Learn says machine readiness can take up to 10 minutes and Workspace
readiness up to 20 minutes depending on model size. After the observed duration
exceeds the applicable documented window, use only status and conditions
reported by the Workspace, including documented ResourceReady,
InferenceReady, and WorkspaceSucceeded when present. Do not invent
NodeClaim, controller-log, or private condition chains.
Correlate a not-ready status with:
If neither is decisive, preserve the status, timestamps, region, instance type, and missing evidence, then hand off to the cluster/quota owner or Azure Support.
Deleting a Workspace does not remove GPU node pools provisioned for it; Microsoft Learn requires those pools to be found and deleted manually. Present Workspace deletion and each pool deletion as separate charged-resource mutations, explain the cleanup dependency, and wait for explicit authorization. Do not stop/start the cluster as a diagnostic action.