Here is the example of the kubeflow-dashboard-operator that ends up on a GPU node (las2-mlgpu43).
The application is specified in the bundle as follows:
kubeflow-dashboard:
charm: kubeflow-dashboard
channel: 1.6/stable
scale: 1
_github_repo_name: kubeflow-dashboard-operator
constraints: tags=node.mldatanode=true,^node.mlgpunode=true
Here is the example of the kubeflow- dashboard- operator that ends up on a GPU node (las2-mlgpu43). dashboard: repo_name: kubeflow- dashboard- operator mldatanode= true,^node. mlgpunode= true
The application is specified in the bundle as follows:
kubeflow-
charm: kubeflow-dashboard
channel: 1.6/stable
scale: 1
_github_
constraints: tags=node.
$ kubectl get statefulsets.apps -n kubeflow kubeflow- dashboard- operator -o json | jq .spec.template. spec.affinity
null
Here is the full YAML for the kubeflow- dashboard- operator statefulset: https:/ /pastebin. canonical. com/p/RGb2YyzRr 3/ dashboard- operator statefulset: https:/ /pastebin. canonical. com/p/Y6pYgHxQz D/
Here is the full JSON for the kubeflow-
The cluster has the following nodes: plane,master 35d v1.24.6 plane,master 35d v1.24.6 plane,master 35d v1.24.6 plane,master 35d v1.24.6 plane,master 35d v1.24.6
NAME STATUS ROLES AGE VERSION
las2-mlgpu41 Ready <none> 29d v1.24.3
las2-mlgpu43 Ready <none> 28d v1.24.3
lv01-mlkfwapp-l01 Ready <none> 34d v1.24.6
lv01-mlkfwapp-l02 Ready <none> 34d v1.24.6
lv01-mlkfwapp-l03 Ready <none> 34d v1.24.6
lv01-mlkfwapp-l04 Ready <none> 34d v1.24.6
lv01-mlkfwapp-l05 Ready <none> 34d v1.24.6
lv1-mlksapp-l01 Ready control-
lv1-mlksapp-l02 Ready control-
lv1-mlksapp-l03 Ready control-
lv1-mlksapp-l04 Ready control-
lv1-mlksapp-l05 Ready control-
Here is the full YAML for the nodes in the cluster: https:/ /pastebin. canonical. com/p/gjqR2hnjY h/ /pastebin. canonical. com/p/R8PKD3DBP q/
Here is the full JSON for the nodes in the cluster: https:/