Cloud Example Jupyter

Work in progress

Introduction

The goal of this project is to support a class teaching basic programming using Jupyter Notebook Jupyter notebook is a single process that supports only one person. To support a whole class, a jupyter notebook process will need to be run for each student. Jupyter offers a Jupyter Hub that automatically spawns these singe user processes. However, a single machine can only support around 50-70 students before suffering performance issues. Kubernetes allows this process to scale out horizontally by spreading the single-user instances across physical nodes. I will give a break down of different pieces needed to make this work and go into more detail on certain aspects.

Basics

Here is what the Workloads tab looks like:

Details of each deployment:

continuous-image-puller

This deployment:

• Runs a copy of itself on all physical nodes of the cluster. This is called a daemon set by kubernetes.
• The purpose of this deployment is to pull the single-user docker image ahead of time on each node, and automatically on any new nodes to the cluster.