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Thursday, December 7 • 3:50pm - 4:25pm
Large Scale Teaching Infrastructure with Kubernetes - Yuvi Panda, Berkeley University

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Data Science & Programming literacy is an important aspect of literacy in the 21st century, but teaching these skills at scale is quite difficult. At UC Berkeley, we are trying - our 'Foundations of Data Science' course has no pre-requisites, and routinely attracts more than a 1000 students from across majors. 

Requiring students to have local programming environments installed & debugged is a non-starter at this scale. We have been running a Kubernetes based JupyterHub environment that allows them to do all their programming with a web based environment with Jupyter Notebooks. This is an important change in many ways:

1. Lets students start instantly with writing code, rather than dealing with the accidental complexity of installing software locally

2. Acts as an equalizer - a student using a chromebook borrowed from the library has no disadvantage over someone using an expensive Macbook Pro

3. This is course critical infrastructure, and needs high availability at low human / dollar cost

In this talk we'll go over how we have:

1. Used Kubernetes to make reduce our costs while allowing a larger group of people to deploy safely to various cloud providers.

2. Extracted our JupyterHub deployment into a project part of Project Jupyter (Zero to JupyterHub) that is being adopted at other universities & organizations.


Yuvi Panda

UC Berkeley, Data Science Education Program

Thursday December 7, 2017 3:50pm - 4:25pm CST
Ballroom B, Level 1
  In Production - KubeCon