Data Science Jupyter Notebook

Purpose of this quickstarter

Provision a shared jupyter notebook within openshift for rapid prototyping of data science applications using crowd authentification

What files / architecture is generated?

+-- Jenkinsfile
+-- docker
| +-- Dockerfile
| +-- jupyter_notebook_config.json
| +-- requirements.txt
| +-- run.sh
+-- src
+-- init.sh

Frameworks used

python 3.6 + jupyter

Usage - how do you start after you provisioned this quickstarter

The quickstarter sets up two pods in openshift. The jupyter notebook is routed through a crowd authentication proxy.

The directory /app/src/work/storage is created where code can be organized using installed git.
Please consider mounting a persistent volume claim for this path.
New python requirements are specified using the requirements.txt

How this quickstarter is built through jenkins

The build pipeline is defined in the Jenkinsfile in the project root. The main stages of the pipeline are:

  1. Patch the build configs and inject nexus credentials for installing python dependencies over nexus pypi repository

  2. Start openshift build

  3. Deploy image to openshift

Builder slave used

jenkins-slave-base

Known limitions

Consider if sufficient computing resources can be provided by the openshift cluster.