Quasi-Enterprise JupyterHub Deployment

Welcome to a small project that enables an aspiring person to run a "Science Platform" suitable for astrophysics research. This might be overkill if all you need is a local JupyterLab notebook with Python 3.7 (and the amazing astronomy and processing libraries). However, if you want to leverage more of an ecosystem around those components with JupyterHub then this can be a springboard to launch your own project.

If you're looking for a large enterprise-scale JupyterHub deployment running on Kubernetes then checkout Zero-to-JupyterHub with k8s

Spin-up a JupyterHub server with these features

• Reverse-Proxy
• Industry-standard SSO Authentication
• SQL database for persistent configurations and for SQL-based workflows
• Mock S3 object store
• Full-suite of the common Python astrophysics & astronomical libraries
• Spark processing cluster (future)

Loosely based on the documented JupyterHub deployment at Université de Versailles which is described in depth in this blog post.

Additionally look up the official JupyterHub Docker Deploy for more JupyterHub+Docker information.

All-🌟 projects making this demonstration possible

• Docker
• Keycloak
• Python
• Postgres
• Zenko CloudServer
• JupyterHub

Features

Adapt to your needs

This deployment is ready for you to explore. But if you want to clone and roll on your own server read below!

Disclaimer: ensure you understand the well-written by outdated blog post first, to be sure you understand the configuration.

Then, if you like, clone this repository and look into making (at least) the following changes:

• In .env, set the variable HOST to the name of the server you intend to host your deployment on.
• In reverse-proxy/traefik.toml, edit the paths in certFile and keyFile and point them to your own TLS certificates. Possibly edit the volumes section in the reverse-proxy service in docker-compose.yml.
• In jupyterhub/jupyterhub_config.py, edit the "Authenticator" section according to your authentication server. If in doubt, read here.

Other changes you may like to make:

• Edit jupyterlab/Dockerfile to include different software you like. Do not forget to change jupyterhub/jupyterhub_config.py accordingly, in particular the "user data persistence" section.

Run!

Once you are ready, build and launch the application with:

docker-compose build
docker-compose up -d

Then navigate to jupyterhub.docker.localhost (Google Chrome might work better than other browsers, YMMV)

Stop

docker-compose down

More

Read the Docker Compose manual to learn how to manage your application.