Zero to JupyterHub with Kubernetes

JupyterHub allows users to interact with a computing environment through a webpage. As most devices have access to a web browser, JupyterHub makes it is easy to provide and standardize the computing environment of a group of people (e.g., for a class of students or an analytics team).

This project will help you set up your own JupyterHub on a cloud and leverage the clouds scalable nature to support large groups of users. Thanks to Kubernetes, we are not tied to a specific cloud provider.

Note that this project is under active development so information and tools may change. You can be a part of this change! If you see anything that is incorrect or have any questions, feel free to reach out in the gitter chat or create an issue at the issues page. If you have tips or deployments that you would like to share, see Resources from the community.

This documentation is for jupyterhub chart version 0.0.1-set.by.chartpress, which deploys JupyterHub 1.1.0.

This version of the chart requires kubernetes ≥1.11 and helm ≥2.11.

What To Expect

This guide will help you deploy and customize your own JupyterHub on a cloud. While doing this, you will gain valuable experience with:

  • A cloud provider such Google Cloud, Microsoft Azure, Amazon EC2, IBM Cloud…

  • Kubernetes to manage resources on the cloud

  • Helm to configure and control the packaged JupyterHub installation

  • JupyterHub to give users access to a Jupyter computing environment

  • A terminal interface on some operating system

It’s also possible you end up getting experienced with:

Note

For a more elaborate introduction to the tools and services that JupyterHub depends upon, see our Utilized Tools page.

Setup JupyterHub

This tutorial starts from Step Zero: your Kubernetes cluster and describes the steps needed for you to create a complete initial JupyterHub deployment. This will use the JupyterHub Helm chart which provides sensible defaults for an initial deployment.

Setup JupyterHub

Customization Guide

JupyterHub can be configured and customized to fit a variety of deployment requirements. If you would like to expand JupyterHub, customize its setup, increase the computational resources available for users, or change authentication services, this guide will walk you through the steps. See the Configuration Reference for a list of frequently used configurable helm chart fields.

Customization Guide

Administrator Guide

This section provides information on managing and maintaining a staging or production deployment of JupyterHub. It has considerations for managing cloud-based deployments and tips for maintaining your deployment.

Administrator Guide

Resources from the community

This section gives the community a space to provide information on setting up, managing, and maintaining JupyterHub.

Important

We recognize that Kubernetes has many deployment options. As a project team with limited resources to provide end user support, we rely on community members to share their collective Kubernetes knowledge and JupyterHub experiences.

Note

Contributing to Z2JH. If you would like to help improve the Zero to JupyterHub guide, please see the issues page as well as the contributor guide.

We hope that you will use this section to share deployments with on a variety of infrastructure and for different use cases. There is also a community maintained list of users of this Guide and the JupyterHub Helm Chart.

Please submit a pull request to add to this section. Thanks.

Community section

Reference

Reference

Institutional support

This guide and the associated helm chart would not be possible without the amazing institutional support from the following organizations (and the organizations that support them!)

Setup Kubernetes