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JupyterHub Deployment

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This section describes the tasks that you must complete to deploy JupyterHub in your Kubernetes cluster.

Note It is possible to deploy JupyterHub on platforms other than Kubernetes. Deploying JupyterHub on platforms other than Kubernetes is outside of the scope of this solution.

Prerequisites

Before you perform the deployment exercise that is outlined in this section, we assume that you have already performed the following tasks:

  1. You already have a working Kubernetes cluster.

  2. You have already installed and configured NetApp Astra Trident in your Kubernetes cluster. For more details on Astra Trident, refer to the Astra Trident documentation.

Install Helm

JupyterHub is deployed using Helm, a popular package manager for Kubernetes. Before you deploy JupyterHub, you must install Helm on your Kubernetes control node. To install Helm, follow the installation instructions in the official Helm documentation.

Set Default Kubernetes StorageClass

Before you deploy JupyterHub, you must designate a default StorageClass within your Kubernetes cluster. To designate a default StorageClass within your cluster, follow the instructions outlined in the Kubeflow Deployment section. If you have already designated a default StorageClass within your cluster, then you can skip this step.

Deploy JupyterHub

After completing the steps above, you are now ready to deploy JupyterHub. JupyterHub deployment requires the following steps:

Configure JupyterHub Deployment

Before deployment it is a good practice to optimize the JupyterHub deployment for your respective environment. You can create a config.yaml file and utilize it during deployment using the Helm chart.

An example config.yaml file can be found at https://github.com/jupyterhub/zero-to-jupyterhub-k8s/blob/HEAD/jupyterhub/values.yaml

Note In this config.yaml file, you can set the (singleuser.storage.dynamic.storageClass) parameter for the NetApp Trident StorageClass. This is the storage class that will be used to provision the volumes for individual user workspaces.

Adding Shared Volumes

If you want to use a shared volume for all JupyterHub users you can adjust your config.yaml accordingly. For example, if you have a shared PersistentVolumeClaim called jupyterhub-shared-volume you could mount it as /home/shared in all user pods as:

singleuser:
  storage:
    extraVolumes:
      - name: jupyterhub-shared
        persistentVolumeClaim:
          claimName: jupyterhub-shared-volume
    extraVolumeMounts:
      - name: jupyterhub-shared
        mountPath: /home/shared
Note This is an optional step, you can adjust these parameters to your needs.

Deploy JupyterHub with Helm Chart

Make Helm aware of the JupyterHub Helm chart repository.

helm repo add jupyterhub https://hub.jupyter.org/helm-chart/
helm repo update

This should show output like:

Hang tight while we grab the latest from your chart repositories...
...Skip local chart repository
...Successfully got an update from the "stable" chart repository
...Successfully got an update from the "jupyterhub" chart repository
Update Complete. ⎈ Happy Helming!⎈

Now install the chart configured by your config.yaml by running this command from the directory that contains your config.yaml:

helm upgrade --cleanup-on-fail \
  --install my-jupyterhub jupyterhub/jupyterhub \
  --namespace my-namespace \
  --create-namespace \
  --values config.yaml
Note In this example:

<helm-release-name> is set to my-jupyterhub, which will be the name of your JupyterHub release.
<k8s-namespace> is set to my-namespace, which is the namespace where you want to install JupyterHub.
The --create-namespace flag is used to create the namespace if it does not already exist.
The --values flag specifies the config.yaml file that contains your desired configuration options.

Check Deployment

While step 2 is running, you can see the pods being created from the following command:

kubectl get pod --namespace <k8s-namespace>

Wait for the hub and proxy pod to enter the Running state.

NAME                    READY     STATUS    RESTARTS   AGE
hub-5d4ffd57cf-k68z8    1/1       Running   0          37s
proxy-7cb9bc4cc-9bdlp   1/1       Running   0          37s

Access JupyterHub

Find the IP we can use to access the JupyterHub. Run the following command until the EXTERNAL-IP of the proxy-public service is available like in the example output.

Note We used NodePort service in our config.yaml file, you can adjust for your environment based on your setup (e.g LoadBalancer). 
kubectl --namespace <k8s-namespace> get service proxy-public
NAME           TYPE           CLUSTER-IP     EXTERNAL-IP     PORT(S)        AGE
proxy-public   NodePort   10.51.248.230   104.196.41.97   80:30000/TCP   1m

To use JupyterHub, enter the external IP for the proxy-public service in to a browser.