The idea of this hands-on is to generate a CI/CD pipeline based on this dummy repository.
- Use your own Github account to fork this repository.
- Create a virtual environment
- You can train new models or change something in the code as you like
- Now create your CI/CD Pipeline
- It should have linting
- Testing
- Deploying a new model
For the deployment of the Docker that has the predict endpoint I used Heroku.
- Create an account on https://id.heroku.com/login.
- Secondly, create a new app with the naming
employee-predict-vantage-{YOUR_NAME}
. - Then, install Heroku CLI using
brew tap heroku/brew && brew install heroku
for MAC. - Create an API key using
heroku authorizations:create
which can somehow be used in your CI/CD pipeline
Make sure you push the container to your own app name. Change this in app/app.py
.
Finally, you can check on Heroku logs if the container is deployed successfully and check if you can predict by running:
streamlit run /app/app.py