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The official Jupyter Conference
August 22-23, 2017: Training
August 23-25, 2017: Tutorials & Conference
New York, NY

Schedule: JupyterHub deployments sessions

Descriptions of (often large scale) deployments of JupyterHub to serve specific populations or use cases, whether internal to an organization or open to the public.

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9:00am–12:30pm Wednesday, August 23, 2017
Deploying JupyterHub for students and researchers
Location: Concourse E Level: Intermediate
Min Ragan-Kelley (Simula Research Laboratory), Carol Willing (Cal Poly San Luis Obispo), Yuvi Panda (Data Science Education Program (UC Berkeley)), Ryan Lovett (Department of Statistics, UC Berkeley)
Average rating: **...
(2.00, 1 rating)
JupyterHub, a multiuser server for Jupyter notebooks, enables you to offer a notebook server to everyone in a group—which is particularly useful when teaching a course, as students no longer need to install software on their laptops. Min Ragan-Kelley, Carol Willing, Yuvi Panda, and Ryan Lovett get you started deploying and customizing JupyterHub for your needs. Read more.
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11:05am–11:45am Thursday, August 24, 2017
How JupyterHub tamed big science: Experiences deploying Jupyter at a supercomputing center
Location: Nassau Level: Intermediate
Shreyas Cholia (Lawrence Berkeley National Laboratory), Rollin Thomas (Lawrence Berkeley National Laboratory), Shane Canon (Lawrence Berkeley National Laboratory)
Shreyas Cholia, Rollin Thomas, and Shane Canon share their experience leveraging JupyterHub to enable notebook services for data-intensive supercomputing on the Cray XC40 Cori system at the National Energy Research Scientific Computing Center (NERSC). Read more.
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11:55am–12:35pm Thursday, August 24, 2017
Building a notebook platform for 100,000 users
Location: Nassau Level: Intermediate
Scott Sanderson (Quantopian)
Average rating: *****
(5.00, 1 rating)
Scott Sanderson describes the architecture of the Quantopian Research Platform, a Jupyter Notebook deployment serving a community of over 100,000 users, explaining how, using standard extension mechanisms, it provides robust storage and retrieval of hundreds of gigabytes of notebooks, integrates notebooks into an existing web application, and enables sharing notebooks between users. Read more.
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1:50pm–2:30pm Thursday, August 24, 2017
Managing a 1,000+ student JupyterHub without losing your sanity
Location: Nassau Level: Intermediate
Ryan Lovett (Department of Statistics, UC Berkeley), Yuvi Panda (Data Science Education Program (UC Berkeley))
Average rating: *****
(5.00, 1 rating)
The UC Berkeley Data Science Education program uses Jupyter notebooks on a JupyterHub. Ryan Lovett and Yuvi Panda outline the DevOps principles that keep the largest reported educational hub (with 1,000+ users) stable and performant while enabling all the features instructors and students require. Read more.
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5:00pm–5:40pm Friday, August 25, 2017
Democratizing access to open data by providing open computational infrastructure
Location: Nassau Level: Non-technical
Yuvi Panda (Data Science Education Program (UC Berkeley))
Average rating: *****
(5.00, 1 rating)
Open data by itself is not enough. You need open computational infrastructures as well. Yuvi Panda offers an overview of a volunteer-led open knowledge movement that makes all of its data available openly and explores the free, open, and public computational infrastructure recently set up for people to play with and build things on its data (using a JupyterHub deployment). Read more.