/Azure_CICD_Pipeline

Udacity's Building a CI/CD Pipeline Project (Azure)

Primary LanguagePython

Overview

This is a Web Service that uses a pretrained model to predict Boston house prices. The web service is deployed to Azure as an App service.

Project Plan

Instructions

Running the App Locally with Docker

To run the app locally you need to be running Docker. Go to the flask-sklearn directory and execute the script to start a container running the app:

$ cd flask-sklearn
$ ./run_docker.sh

Run Docker

Open a new terminal, go to the same directory and execute the client call:

$ cd flask-sklearn
$ ./make_prediction.sh

You can adjust the prediction by editing the CURL call in that script.

Run Docker

Other Screenshots

  • Project running on Azure App Service

Run Docker

Run Docker

  • Project cloned into Azure Cloud Shell

Run Docker

  • GitHub Actions

Run Docker

  • Passing tests that are displayed after running the make all command from the Makefile

Run Docker

  • Output of a test run

Run Docker

  • Successful run of the project in Azure Pipelines

Run Docker

  • Running Azure App Service

Run Docker

  • Successful prediction from deployed flask app in Azure Cloud Shell>

Run Docker

Enhancements

The most obvious enhancement is to add a Web GUI for the application to allow users to make predictions interactively.

After that adding support for more cities is the most obvious next step.

Demo

YouTube