Step-by-Step: How to Get Started with JupyterHub

This guide walks you through launching your first computing environment on the Nautilus JupyterHub.

1. Open the Login Page

  • Go to JupyterHub website
  • Click Sign in with Authentik

2. Sign in with Authentik

  • You’ll be redirected to an authentication gateway.
  • Click ORCID. In the search box, type: California State University, Fullerton Then select it from the dropdown.
  • Click Log On

3. Log In via CSUF SSO

  • You’ll be redirected to the CSUF Single Sign-On (SSO) page.
  • Log in using your campus credentials (username and password).

4. Set Server Options

  • Once logged in, you'll see the Server Options screen.

    Here you can configure:

    • Region (default: Any)
    • GPUs (optional; set to 1 if using GPU-enabled images)
    • Cores (e.g., 1, 2, or more depending on your job)
    • RAM (e.g., 4 for 4GB; leave blank for default)
    • GPU Type (optional)
    • Image this is your environment, such as: NRP Deep Learning & Data Science Full, PyTorch, SciPy, TensorFlow, R, Julia, etc.

See our Nautilus JupyterHub - Image & Resource Guide for a breakdown of each option and what to choose.

5. Start Your Server

  • Once you’ve configured your environment, scroll down and click Start
  • This will launch your JupyterHub server. It may take up to a minute to initialize.

6. Start Coding!

Welcome to your workspace!

  • Open or create a .ipynb notebook
  • Write your code
  • Run

You’re now running on the Nautilus Hypercluster your code is powered by scalable research-grade infrastructure.

Always remember to stop your server to release resources when you're done. How to Release Resources on JupyterHub Services