JupyterHub is a multiuser server for Jupyter notebooks, focused on supporting deployments in research and education. Recent development of JupyterHub has focused on deploying scalable and sustainable JupyterHub deployments via Kubernetes using the JupyterHub helm chart, and at least as much work has gone into documenting and supporting deploying JupyterHub on Kubernetes as developing the core JupyterHub codebase. JupyterHub 0.9 has added numerous performance and customization improvements as well as the ability to use JupyterHub as an OAuth provider for external services.
Min Ragan-Kelley, Carol Willing, and Yuvi Panda discuss recent additions and future plans for the project, outline best practices for deploying JupyterHub, and detail what you need to get started. Along the way, they share lessons learned from some of JupyterHub’s largest deployments.
Min Ragan-Kelley is a postdoctoral fellow at Simula Research Lab in Oslo, Norway, where he focuses on developing JupyterHub, Binder, and related technologies and supporting deployments of Jupyter in science and education around the world. Min has been contributing to IPython and Jupyter since 2006 (full-time since 2013).
Carol Willing is a research software engineer at Cal Poly San Luis Obispo working full-time on Project Jupyter, a Python Software Foundation fellow and former director, a Jupyter Steering Council member, a geek in residence at FabLab San Diego, where she teaches wearable electronics and software development, and an independent developer of open hardware and software. She co-organizes PyLadies San Diego and San Diego Python, contributes to open source community projects, including OpenHatch, CPython, Jupyter, and AnitaB.org’s open source projects, and is an active member of the MIT Enterprise Forum in San Diego. She enjoys sharing her passion for electronics, software, problem solving, and the arts. Previously, Carol worked in software engineering management, product and project management, sales, and the nonprofit sector. She holds an MS in management with an emphasis on applied economics and high-tech marketing from MIT and a BSE in electrical engineering from Duke University.
Yuvi Panda is infrastructure lead for the Data Science Education Program at UC Berkeley, where he works on scaling JupyterHub for use by thousands of students. A programmer and DevOps engineer, he wants to make it easy for people who don’t traditionally consider themselves programmers to do things with code and builds tools (Quarry, PAWS, etc.) to sidestep the list of historical accidents that constitute the “command-line tax” that people have to pay before doing productive things with computing. He’s a core member of the JupyterHub team and works on mybinder.org as well. Yuvi is also a Wikimedian, since you can check out of Wikimedia, but you can never leave.
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