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Created a container for a Flask web app using Docker and deployed the container to aKubernetes cluster using Amazon EKS.

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Deploying a Flask API

This is the project starter repo for the fourth course in the Udacity Full Stack Nanodegree: Server Deployment, Containerization, and Testing.

In this project you will containerize and deploy a Flask API to a Kubernetes cluster using Docker, AWS EKS, CodePipeline, and CodeBuild.

The Flask app that will be used for this project consists of a simple API with three endpoints:

  • GET '/': This is a simple health check, which returns the response 'Healthy'.
  • POST '/auth': This takes a email and password as json arguments and returns a JWT based on a custom secret.
  • GET '/contents': This requires a valid JWT, and returns the un-encrpyted contents of that token.

The app relies on a secret set as the environment variable JWT_SECRET to produce a JWT. The built-in Flask server is adequate for local development, but not production, so you will be using the production-ready Gunicorn server when deploying the app.

Initial setup

  1. Fork this project to your Github account.
  2. Locally clone your forked version to begin working on the project.

Dependencies

  • Docker Engine
    • Installation instructions for all OSes can be found here.
    • For Mac users, if you have no previous Docker Toolbox installation, you can install Docker Desktop for Mac. If you already have a Docker Toolbox installation, please read this before installing.
  • AWS Account
    • You can create an AWS account by signing up here.

Project Steps

Completing the project involves several steps:

  1. Write a Dockerfile for a simple Flask API
  2. Build and test the container locally
  3. Create an EKS cluster
  4. Store a secret using AWS Parameter Store
  5. Create a CodePipeline pipeline triggered by GitHub checkins
  6. Create a CodeBuild stage which will build, test, and deploy your code

For more detail about each of these steps, see the project lesson here.

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Created a container for a Flask web app using Docker and deployed the container to aKubernetes cluster using Amazon EKS.

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  • Python 95.5%
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