Project Overview

This project containerizes a pre-trained sklearn model (model_data/boston_housing_prediction.joblib) that has been trained to predict housing prices in Boston.

Setup the Environment

• Create a virtualenv and activate it make setup
• Run make install to install the necessary dependencies

Running app.py

1. Standalone: python app.py
2. Run in Docker: ./run_docker.sh
3. Run in Kubernetes: ./run_kubernetes.sh

Calling the service

A sample call can be found in make_predictions.sh

Kubernetes Steps

• Setup and Configure Docker locally
• Setup and Configure Kubernetes locally
• Create Flask app in Container
• Run via kubectl

Custom Docker Image repos

To push locally built docker image to your repo edit and then run upload_docker.sh