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

• Customizing your Deployment
  • Applying configuration changes
• Customizing User Environment
  • Choose and use an existing Docker image
  • Selecting a user interface
  • Use JupyterLab by default
  • Customize an existing Docker image
  • Set environment variables
  • About user storage and adding files to it
  • Using multiple profiles to let users select their environment
  • Set command to launch
  • Disable specific JupyterLab extensions
• Customizing User Resources
  • Set user memory and CPU guarantees / limits
  • Set user GPU guarantees / limits
  • Modifying user shared memory size
  • Modifying user storage type and size
  • Expanding and contracting the size of your cluster
• Customizing User Storage
  • How can this process break down?
  • Configuration
  • Turn off per-user persistent storage
  • Additional storage volumes
• Customizing User Management
  • Culling user pods
  • Admin Users
  • Authenticating Users