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Manual backups

Your cloud provider may have native ways to back up your Kubernetes cluster and volumes.

This guide describes how you would manually obtain the data you need to repopulate your Nebari instance if your cluster is lost, and you wish to start it up again from the nebari-config.yaml file.

There are three main locations that you need to back up:

  1. The Network File System (NFS) volume where all JupyterLab workspace files are stored
  2. The JupyterHub database (for Dashboard configuration)
  3. The Keycloak user/group database

Network file system

This amounts to:

  • Tarballing the /home directory
  • Saving to object storage [s3, google cloud storage, etc]
  • Downloading and untaring to new cluster

This specific guide shows how to do this on an AWS cluster and upload to AWS S3.


Pod deployment

With kubectl configured, the next step will be to deploy the pod that allows you to access the cluster files. First, save the following pod specification to a file named pod.yaml:

kind: Pod
apiVersion: v1
name: volume-debugger-ubuntu
namespace: dev
- name: volume-to-debug-ubuntu
claimName: "jupyterhub-dev-share"
- name: debugger
image: ubuntu
command: ["sleep", "36000"]
- mountPath: "/data"
name: volume-to-debug-ubuntu

Note in QHub versions before v0.4 replace claimName: "jupyterhub-dev-share" with claimName: "nfs-mount-dev-share" above.

Once the file pod.yml has been created, run the following command:

kubectl apply -f pod.yaml -n dev

If you have a namespace other than the default dev, replace dev with your namespace when running kubectl. To get a shell to this running pod, run:

kubectl exec -n dev --stdin --tty volume-debugger-ubuntu -- /bin/bash

Again replacing the dev namespace as needed.


You must install several apt packages, as the pod spun up is a basic pod. Use the following command:

apt update
apt install curl -y
apt install unzip -y

Because you are on AWS, the AWS command-line tool is also installed:

curl "" -o ""
aws configure

The last line in the command above prompts for your AWS public/private key and default region. Paste each of these and press enter. To ignore and skip the output, press enter.


To back up the file system, run:

cd /data
tar -cvf <custom_name>.tar .

The preferred naming scheme includes a year-month-day, example 2021-04-23_home_backup.tar. You can utilize multi-backups through this step. This step takes several minutes depending on the size of the home directories.

Upload to object storage

Once this is complete, upload the tar file to S3 using the AWS command-line tool:

aws s3 cp 2021-04-23.tar s3://<your_bucket_name>/backups/2021-04-23.tar

Replacing your_bucket_name with a bucket you have created. If you don't have an existing bucket, instructions are here:

Download from object storage and decompress

Now that the data backed up, perform the same steps preceding for the new cluster. This includes:

  • Configuring kubectl for the new cluster.
  • Creating a pod on the new cluster and getting shell access into it.
  • Installing the apt packages.
  • Configuring AWS.

Once AWS gets configured on the new pod, you can then download the backup with:

cd /data
aws s3 cp s3://<your_bucket_name>/backups/2021-04-23.tar .

The last step is to extract the contents of the tarball:

cd /data
tar -xvf 2021-04-23.tar

The file permissions for the default tar is same as the original files.

Important: If upgrading from 0.3.14 or earlier to 0.4 or later

QHub v0.4: If restoring your NFS as part of the upgrade you must also run some extra commands, immediately after extracting from the tar file.

Previous versions contained the shared folder within home. From 0.4.0 both shared and home directories are at the same level with respect to the QHub filesystem:

cd /data
cp -r home/shared/* shared/
rm -rf home/shared/

And then:

chown -R 1000:100 /data/home/*
chown -R 1000:100 /data/shared/*

From QHUb v0.4. all users will have the same uid.

Google cloud provider

To use the Google Cloud provider, install the gsutil CLI instead of the AWS CLI. Otherwise, the instructions are the same as for AWS above, other than when working with S3. Here are the commands to access Google Spaces instead of S3 for copy/download of the backup:

cd /data
gsutil cp 2021-04-23.tar gs://<your_bucket_name>/backups/2021-04-23.tar

cd /data
gsutil cp gs://<your_bucket_name>/backups/2021-04-23.tar .

Digital Ocean

Instructions will be similar to those for AWS above, but use Digital Ocean spaces instead of S3. This guide explains installation of the command-line tool:

JupyterHub Database

The JupyterHub database will mostly be recreated whenever you start a new cluster, but should be backed up to save Dashboard configurations.

You want to do something very similar to the NFS backup, above - this time you need to back up one file located in the PersistentVolume hub-db-dir.

First, you might think you can make a new pod.yaml file, this time specifying claimName: "hub-db-dir" instead of claimName: "jupyterhub-dev-share". However, hub-db-dir is 'Read Write Once' - the 'Once' meaning it can only be mounted to one pod at a time but the JupyterHub pod will already have this mounted! So the same approach will not work here.

Instead of mounting to a new 'debugger pod' you have to access the JupyterHub pod directly using the kubectl CLI.

Look up the JupyterHub pod:

kubectl get pods -n dev

It will be something like hub-765c9488d6-8z4nj.

Get a shell into that pod:

kubectl exec -n dev --stdin --tty hub-765c9488d6-8z4nj -- /bin/bash

There is no need to TAR anything up since the only file required to be backed up is /srv/jupyterhub/jupyterhub.sqlite.

Backing up JupyterHub DB

Now you need to upload the file to S3. You might want to install the AWS CLI tool as we did before, however, as the Hub container is a rather restricted environment the recommended approach is to upload files to AWS S3 buckets using curl.

For more details please refer to the [using curl to access AWS S3 buckets] documentation.

Restoring JupyterHub DB

You will need to overwrite the file /srv/jupyterhub/jupyterhub.sqlite based on the version backed up to S3.

You should restart the pod:

kubectl delete -n dev pod hub-765c9488d6-8z4nj

As for uploads, [you may need to use curl to download items from an AWS S3 bucket]

Keycloak user/group database

Nebari provides a script to export the important user/group database. Your new Nebari cluster will recreate a lot of Keycloak config (including new Keycloak clients which will have new secrets), so only the high-level Group and User info is exported.

If you have a heavily customized Keycloak configuration, some details may be omitted in this export.

Export Keycloak

The export script is at nebari/scripts/

Locate your nebari-config.yaml file, for example by checking out of your Git repo for you Nebari. Activate a virtual environment with the nebari Python package installed.

This assumes that the password visible in the nebari-config.yaml file under the security.keycloak.initial_root_password field is still valid for the root user.

If not, first set the KEYCLOAK_ADMIN_PASSWORD environment variable to the new value.

Run the following to create the export file:

python nebari/scripts/ -c nebari-config.yaml > exported-keycloak.json

You may wish to upload the Keycloak export to the same S3 location where you uploaded the TAR file in the NFS section.

Import Keycloak

To re-import your users and groups, [login to the /auth/ URL] using the root username and password.

Under 'Manage' on the left-hand side, click 'Import'. Locate the exported-keycloak.json file and select it. Then click the 'Import' button.

All users and groups should now be present in Keycloak. Note that the passwords will not have been restored, so you may need to be reset them after this step.