Distributed Notebook Cluster: Workload Driver

This repository contains a "Workload Driver" for the Distributed Jupyter Notebook Cluster (which is not yet open-sourced).

The Workload Driver provides a web interface containing a dashboard for monitoring the Notebook Cluster. The Workload Driver will also allow users to execute large-scale workloads on the Jupyter Notebook cluster.

Repository Overview

The backend is contained within the internal/ directory. The frontend is contained within the web/ directory. The entrypoint for the backend is in the cmd/server/ directory.

Quick-start

First, clone the repository:

git clone https://github.com/Scusemua/workload-driver-react
cd workload-driver-react

To run the frontend, execute the following:

npm install && npm run start:dev

Next, to run the backend, execute the following in a separate terminal:

make run-server

Development scripts

# Install development/build dependencies
npm install

# Start the development server
npm run start:dev

# Run a production build (outputs to "dist" dir)
npm run build

# Run the test suite
npm run test

# Run the test suite with coverage
npm run test:coverage

# Run the linter
npm run lint

# Run the code formatter
npm run format

# Launch a tool to inspect the bundle size
npm run bundle-profile:analyze

# Start the express server (run a production build first)
npm run start

# Start storybook component explorer
npm run storybook

# Build storybook component explorer as standalone app (outputs to "storybook-static" dir)
npm run build:storybook

Configurations

• TypeScript Config
• Webpack Config
• Jest Config
• Editor Config

Code quality tools

• For accessibility compliance, we use react-axe
• To keep the bundle size in check, we use webpack-bundle-analyzer
• To keep the code formatting in check, we use prettier
• To keep the code logic and test coverage in check, we use jest
• To ensure code styles remain consistent, we use eslint
• To provide a place to showcase custom components, we integrate with storybook
• To provide visually-appealing and functional components, we utilize patternfly

Multi environment configuration

This project uses dotenv-webpack for exposing environment variables to your code. Either export them at the system level like export MY_ENV_VAR=http://dev.myendpoint.com && npm run start:dev or simply drop a .env file in the root that contains your key-value pairs like below:

ENV_1=http://1.myendpoint.com
ENV_2=http://2.myendpoint.com

With that in place, you can use the values in your code like console.log(process.env.ENV_1);

Demo Images