Extending your JupyterHub setup

The helm chart used to install JupyterHub has a lot of options for you to tweak. This page lists some of the most common changes.

Applying configuration changes

The general method is:

  1. Make a change to the config.yaml

  2. Run a helm upgrade:

    helm upgrade <YOUR_RELEASE_NAME> jupyterhub/jupyterhub --version=v0.4 -f config.yaml

    Where <YOUR_RELEASE_NAME> is the parameter you passed to --name when installing jupyterhub with helm install. If you don’t remember it, you can probably find it by doing helm list.

  3. Wait for the upgrade to finish, and make sure that when you do kubectl --namespace=<YOUR_NAMESPACE> get pod the hub and proxy pods are in Ready state. Your configuration change has been applied!

Authenticating with OAuth2

JupyterHub’s oauthenticator has support for enabling your users to authenticate via a third-party OAuth provider, including GitHub, Google, and CILogon.

Follow the service-specific instructions linked on the oauthenticator repository to generate your JupyterHub instance’s OAuth2 client ID and client secret. Then declare the values in the helm chart (config.yaml).

Here are example configurations for two common authentication services. Note that in each case, you need to get the authentication credential information before you can configure the helmchart for authentication.


For more information see the full example of Google OAuth2 in the next section.

  type: google
    clientId: "yourlongclientidstring.apps.googleusercontent.com"
    clientSecret: "adifferentlongstring"
    callbackUrl: "http://<your_jupyterhub_host>/hub/oauth_callback"
    hostedDomain: "youruniversity.edu"
    loginService: "Your University"


  type: github
    clientId: "y0urg1thubc1ient1d"
    clientSecret: "an0ther1ongs3cretstr1ng"
    callbackUrl: "http://<your_jupyterhub_host>/hub/oauth_callback"

To add a whitelist of usernames add to the config file under hub:

    extraConfig: |
        c.Authenticator.whitelist = {"user1", "user2"}

Full Example of Google OAuth2

If your institution is a G Suite customer that integrates with Google services such as Gmail, Calendar, and Drive, you can authenticate users to your JupyterHub using Google for authentication.


Google requires that you specify a fully qualified domain name for your hub rather than an IP address.

  1. Log in to the Google API Console.
  2. Select a project > Create a project… and set ‘Project name’. This is a short term that is only displayed in the console. If you have already created a project you may skip this step.
  3. Type “Credentials” in the search field at the top and click to access the Credentials API.
  4. Click “Create credentials”, then “OAuth client ID”. Choose “Application type” > “Web application”.
  5. Enter a name for your JupyterHub instance. You can give it a descriptive name or set it to be the hub’s hostname.
  6. Set “Authorized JavaScript origins” to be your hub’s URL.
  7. Set “Authorized redirect URIs” to be your hub’s URL followed by “/hub/oauth_callback”. For example, http://example.com/hub/oauth_callback.
  8. When you click “Create”, the console will generate and display a Client ID and Client Secret. Save these values.
  9. Type “consent screen” in the search field at the top and click to access the OAuth consent screen. Here you will customize what your users see when they login to your JupyterHub instance for the first time. Click Save when you are done.
  10. In your helm chart, create a stanza that contains these OAuth fields:
  type: google
    clientId: "yourlongclientidstring.apps.googleusercontent.com"
    clientSecret: "adifferentlongstring"
    callbackUrl: "http://<your_jupyterhub_host>/hub/oauth_callback"
    hostedDomain: "youruniversity.edu"
    loginService: "Your University"

The ‘callbackUrl’ key is set to the authorized redirect URI you specified earlier. Set ‘hostedDomain’ to your institution’s domain name. The value of ‘loginService’ is a descriptive term for your institution that reminds your users which account they are using to login.

Expanding and contracting the size of your cluster

You can easily scale up or down your cluster’s size to meet usage demand or to save cost when the cluster is not being used. Use the resize command and provide a new cluster size (i.e. number of nodes) as a command line option --size:

gcloud container clusters resize \
             <YOUR-CLUSTER-NAME> \
             --size <NEW-SIZE> \
             --zone <YOUR-CLUSTER-ZONE>

To display the cluster’s name, zone, or current size, use the command:

gcloud container clusters list

After resizing the cluster, it may take a couple of minutes for the new cluster size to be reported back as the service is adding or removing nodes. You can find the true count of currently ‘ready’ nodes using kubectl get node to report the current Ready/NotReady status of all nodes in the cluster.


When organizing and running a workshop, resizing a cluster gives you a way to save cost and prepare JupyterHub before the event. For example:

  • One week before the workshop: You can create the cluster, set everything up, and then resize the cluster to zero nodes to save cost.
  • On the day of the workshop: You can scale the cluster up to a suitable size for the workshop. This workflow also helps you avoid scrambling on the workshop day to set up the cluster and JupyterHub.
  • After the workshop: The cluster can be deleted.