isa56k / UdacityOperationalizeMachineLearning

Udactiy Operationalize Machine Learning Project

Current Build Status is:

Project Overview

This project deploys a ML API that can be used for the Udacity DevOps Operationalize Machine Learning API project.

• Test code using linting
• Complete a Dockerfile to containerize this application
• Deploys containerized application using Docker and make a prediction
• Improve the log statements in the source code for this application
• Configure Kubernetes and create a Kubernetes cluster
• Deploy a container using Kubernetes and make a prediction
• Upload a complete Github repo with CircleCI to indicate that your code has been tested

---

How To Get Started

Setup the Environment

• Create a virtualenv and activate it
• 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

Kubernetes Steps

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