Turning Off JupyterHub and Computational Resources

When you are done with your hub, you should delete it so you are no longer paying money for it. The following sections describe how to delete your JupyterHub resources on various cloud providers.

Google Cloud Engine

  1. First, delete the namespace the hub was installed in. This deletes any disks that may have been created to store user’s data, and any IP addresses that may have been provisioned.

    kubectl delete namespace <your-namespace>
  2. Next, you should delete the kubernetes cluster. You can list all the clusters you have.

    gcloud container clusters list

    You can then delete the one you want.

    gcloud container clusters delete <CLUSTER-NAME> --zone=<CLUSTER-ZONE>
  3. Double check to make sure all the resources are now deleted, since anything you have not deleted will cost you money! You can check the web console (make sure you are in the right project and account!) to make sure everything has been deleted.

    At a minimum, check the following under the Hamburger (left top corner) menu:

    1. Compute Engine -> Disks
    2. Container Engine
    3. Networking -> Load Balancing

    These might take several minutes to clear up, but they shouldn’t have anything related to your JupyterHub cluster after you have deleted the cluster.

Amazon AWS

The easiest way to delete your cloud resources on AWS is to use their website. Go to the CloudFormation page. This should have a list of all running AWS stacks that you’ve created.

If you followed the JupyterHub guide, there should be two items, both containing the name that you chose for this stack. For each item, click the checkbox next to it. Then, click Actions and finally Delete Stack. Answer “yes” to any confirmation dialogues, and this should begin the process of deleting your Kubernetes cluster.


Sometimes AWS fails to delete parts of the stack on a first pass. Be sure to double-check that your stack has in fact been deleted, and re-perform the actions above if needed.