Configure Notebook Servers controls and settings in Kubeflow
A Provisioned DKP cluster using version
Creating custom Toleration Groups and Affinity Configurations
You can pre-configure node toleration groups and affinity configurations in the Notebooks UI. These settings allow users to specify
affinity rules for the Notebook pods. This allows notebook-specific workloads to run on specific nodes from a pool of available resources.
For more information about the pod scheduling controls, please refer to the official Kubernetes documentation.
Toleration groups and affinity configs can be configured via the
core.notebook.affinityConfig parameters, respectively.
To configure these resources, create or update the ConfigMap with Kaptain’s configuration and include the following values:
core: notebook: notebookTolerationGroups: - groupKey: "notebooks" displayName: "Notebooks Node Group" tolerations: - key: "dedicated" operator: "Equal" value: "notebook" effect: "NoExecute" notebookAffinityConfig: - configKey: "notebook-affinity-config" displayName: "Notebook Affinity Configuration" affinity: nodeAffinity: requiredDuringSchedulingIgnoredDuringExecution: nodeSelectorTerms: - matchExpressions: - key: topology.kubernetes.io/region operator: In values: - us-west-1 - us-west-2 preferredDuringSchedulingIgnoredDuringExecution: - weight: 1 preference: matchExpressions: - key: another-node-label-key operator: In values: - another-node-label-value
You can set any other desired operator parameters in this file as well, so that you have a single file with all the operator configurations. Please refer to the Toleration v1 core and Affinity v1 core pages in the Kubernetes API documentation to see all the supported fields.
Install Kaptain by following the Install Kaptain documentation. In case of update, edit the
ConfigMap used for Kaptain installation (or the default one, created by Flux controller).
After the installation is complete, the newly added configuration should be available in the Affinity / Tolerations section under Notebooks when configuring a notebook via the Kubeflow UI.
Check a Notebook pod
spec to verify the configuration has been applied to new Notebook server:
kubectl get pod -n <namespace> <pod name> -o yaml
apiVersion: v1 kind: Pod metadata: ... name: jupyter-0 ... spec: affinity: nodeAffinity: preferredDuringSchedulingIgnoredDuringExecution: - preference: matchExpressions: - key: another-node-label-key operator: In values: - another-node-label-value weight: 1 requiredDuringSchedulingIgnoredDuringExecution: nodeSelectorTerms: - matchExpressions: - key: topology.kubernetes.io/region operator: In values: - us-west-1 - us-west-2 ... tolerations: - effect: NoExecute key: dedicated operator: Equal value: notebook - effect: NoExecute key: node.kubernetes.io/not-ready operator: Exists tolerationSeconds: 300 - effect: NoExecute key: node.kubernetes.io/unreachable operator: Exists tolerationSeconds: 300 ...