Continuous Intelligence Workshop

A demo on how to apply continuous delivery principles to train, test and deploy ML models.

Workshop pre-requisites

Before the workshop, please ensure you have done the following:

  • Install a code editor of your choice. If you aren’t familiar with a code editor, VS Code or PyCharm (community edition) are good options.
  • Install and start Docker
    • Mac users
    • Linux users
    • Windows
    • Important things to note:
      • You will be prompted to create a DockerHub account. Follow the instructions in order to download Docker
      • Follow the installation prompts (go with the default options) until you have successfully started Docker
      • [Windows users] When prompted to enable Hyper-V and Containers features, click 'Ok' and let computer restart again.
      • You may have to restart your computer 2-3 times.
  • Install a REST client (e.g. Insomnia)
  • Create accounts:
  • [Windows Users only] Install git bash. We will be using git bash as the terminal for the workshop.

Setup

Note:

  • If you encounter any errors, please refer to FAQs for a list of common errors and how to fix them.
  • If the issue is still not fixed, please file an issue here and we'll look into it.
  • [Windows users] If you're new to Docker, please use the Git Bash terminal to run the commands below

Setup instructions

  1. Fork repository: https://github.com/davified/ci-workshop-app
  2. Clone repository: git clone https://github.com/YOUR_USERNAME/ci-workshop-app
  3. Start Docker on your desktop (Note: Wait for Docker to complete startup before running the subsequent commands. You'll know when startup is completed when the docker icon in your taskbar stops animating)
  4. Build docker image
# [Mac/Linux users]
docker build . -t ci-workshop-app --build-arg user=$(whoami)

# [Windows users]
MSYS_NO_PATHCONV=1 docker build . -t ci-workshop-app --build-arg user=$(whoami)
  1. Start docker container
# [Mac/Linux users]
docker run -it -v $(pwd):/home/ci-workshop-app -p 8080:8080 ci-workshop-app bash

# [Windows users]
winpty docker run -it -v C:\\Users\\path\\to\\your\\ci-workshop-app:/home/ci-workshop-app -p 8080:8080 ci-workshop-app bash
# Note: to find the path, you can run `pwd` in git bash, and manually replace forward slashes (/) with double backslashes (\\)
! Pre-workshop setup stops here
### Other useful docker commands ###
# See list of running containers
docker ps

# Start a bash shell in a running container when it’s running
docker exec -it <container-id> bash

Now you're ready to roll!

Common commands (run these in the container)

# Add some color to your terminal
source bin/color_my_terminal.sh

# Run unit tests
python -m unittest discover -s src/

# Train model
python src/train.py

# Start flask app
python src/app.py

# Make requests to your app
# 1. In your browser, visit http://localhost:8080
# 2. In another terminal in the container, run:
bin/predict.sh http://localhost:8080

# You can also use this script to test your deployed application later:
bin/predict.sh http://my-app.herokuapp.com

FAQs

Please refer to FAQs for:

  • a list of common errors that you may encounter, and how you can fix them.
  • IDE configuration instructions

Configuring CD pipeline

Instructions for setting up your CD pipeline are in docs/CD.md.

Once the CD pipeline is set up, you only need to git add, git commit and git push your code changes, and the CD pipeline will do everything (train, test, deploy) for you.

Bonus: Deploying using Kubernetes

Instructions here