/zero-to-mlhub-k8s

Helm Chart & Documentation for deploying JupyterHub on Kubernetes

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Zero to MLHub with Kubernetes

This repo contains a Helm chart for MLHub and a guide to use it. Together, they allow you to make a JupyterHub available to a very large group of users such as the staff and students of a university.

MLHub Modifications

In this repo, we made some modifications to the forked repo and its helm chart and default values so that it works with the ml-hub and ml-workspace images. Hence, we do not use the hub or singleuser-sample image in the images/ directory. For most parts you should be able to follow the comprehensive guide linked below.

Most prominent changes:

  • change of the command fields in hub and proxy yamls
  • modifying ports to make tunnelling of ssh possible
  • changes of default values, e.g. the used images
  • changes of paths, e.g. the ssl secret mount path

We do not push the helm chart to a repository for now, so feel free to download it from the mlhub releases page or to create the package yourself via helm package jupyterhub/.

You can then deploy the chart via helm upgrade --install mlhub packaged-chart.tgz --namespace $namespace --values config.yaml. The config.yaml can be used to overrride default values.


Original Readme:

The guide

The Zero to JupyterHub with Kubernetes guide provides user-friendly steps to deploy JupyterHub on a cloud using Kubernetes and Helm.

The guide is complemented well by the documentation for JupyterHub.

The Helm chart

The JupyterHub Helm chart lets a user create a reproducible and maintainable deployment of JupyterHub on a Kubernetes cluster in a cloud environment. The released charts are made available in our Helm chart repository.

History

Much of the initial groundwork for this documentation is information learned from the successful use of JupyterHub and Kubernetes at UC Berkeley in their Data 8 program.

Acknowledgements

Thank you to the following contributors:

  • Aaron Culich
  • Carol Willing
  • Chris Holdgraf
  • Erik Sundell
  • Ryan Lovett
  • Yuvi Panda

Future contributors are encouraged to add themselves to this README file too.

Licensing

This repository is dual licensed under the Apache2 (to match the upstream Kubernetes charts repository) and 3-clause BSD (to match the rest of Project Jupyter repositories) licenses. See the LICENSE file for more information!