Giter Club home page Giter Club logo

devenes / terraform-docker-swarm-ecr-phonebook Goto Github PK

View Code? Open in Web Editor NEW
1.0 2.0 1.0 11.48 MB

Project aims to deploy Flask Phonebook Application within a Docker Swarm Cluster on Elastic Compute Cloud (EC2) Instances by pulling the app images from the AWS Elastic Container Registry (ECR) repository using Terraform.

License: GNU General Public License v3.0

Dockerfile 0.49% Shell 11.68% HCL 35.34% Python 29.68% HTML 22.80%
aws containerization docker docker-compose docker-swarm dockerfile ecr elastic-compute-cloud elastic-container-registry flask

terraform-docker-swarm-ecr-phonebook's Introduction

Docker Build And Push Terraform Infrastructure Planner

Automated Docker Swarm Deployment of Python Flask App using Terraform

Description

This project aims to deploy a phonebook web application with Docker Swarm on Elastic Compute Cloud (EC2) Instances by pulling the app images from AWS Elastic Container Registry (ECR) repository using Terraform.

Project Architecture

Project

Docker Swarm Cluster

Project

Project

Elastic Container Registry Repository

Project

Terraform Outputs

Output

Output

Case Study Details

  • Your company has recently started a project that aims to serve as phonebook web application. Your teammates have started to work on the project and developed the UI and backend part of the project and they need your help to deploy the app in development environment.

  • You are, as a Cloud/DevOps engineer, requested to deploy the Phonebook Application in the development environment on Docker Swarm on AWS EC2 Instances using Terraform to showcase the project. To do that you need to;

    • Create a new public repository for the project on GitHub.

    • Create docker image using the Dockerfile from the base image of python:alpine.

    • Deploy the app on swarm using docker compose. To do so on the Compose file;

      • Create a MySQL database service with one replica using the image of mysql:5.7;

        • attach a named volume to persist the data of database server.

        • attach init.sql file to initialize the database using configs.

      • Configure the app service to;

        • pull the image of the app from the AWS ECR repository.

        • deploy the one app for each swarm nodes using global mode.

        • run the app on port 80.

      • Use a user-defined overlay network for the services.

    • Push the necessary files for your project from local repo to the new github repo (phonebookswarm).

  • You are also requested; to use AWS ECR as image repository, to create Docker Swarm with 3 manager and 2 worker node instances, to automate the process of Docker Swarm initialization through Terraform in the development environment. To achieve this goals, you can configure Terraform configuration file using the followings;

    • The application should run on Amazon Linux 2 EC2 Instance

    • EC2 Instance type can be configured as t2.micro.

    • To use the AWS ECR as image repository;

      • Enable the swarm node instances with IAM Role allowing them to work with ECR repos using the instance profile.

      • Install AWS CLI Version 2 on swarm node instances to use aws ecr commands.

    • To automate the process of Docker Swarm initialization;

      • Install the docker and docker-compose on all nodes (instances) using the user-data bash script.

      • Create the leader manager node of the swarm. Within the user-data script;

        • Set the first manager node hostname as Leader-Manager.

        • Initialize Docker swarm.

        • Create a docker service named viz on the manager node on port 8080 using the dockersamples/visualizer image, to monitor the swarm nodes easily.

        • Build the docker image from the GitHub URL of the new project repo and tag it appropriately to push it on ECR repo. (Note: Do not forget to install Git to enable Docker to work with git commands)

        • Download docker-compose.yml file from the repo and deploy application stack on Docker Swarm.

      • Create two manager nodes of the swarm. Within the user-data script;

        • Install the python ec2instanceconnectcli package for mssh command.

        • Connect from manager node to the Leader-Manager to get the join-token and join the swarm as manager node using mssh command.

      • Create two worker nodes of the swarm. Within the user-data script;

        • Install the python ec2instanceconnectcli package to use mssh command.

        • Connect from worker node to the Leader-Manager to get the join-token and join the swarm as worker node using mssh command.

    • Create a security group for all swarm nodes and open necessary ports for the app and swarm services.

    • Create an image repository on ECR for the app.

    • Tag the swarm node instances appropriately as Docker-Swarm-Manager <Number>/Docker-Swarm-Worker <Number> to discern them from AWS Management Console.

    • The Web Application should be accessible via web browser from anywhere.

    • Phonebook App Website URL, Visualization App Website URL should be given as output by Cloudformation Service, after the stack created.

At the end of the project, following topics are to be covered;

  • Docker Swarm Deployment

  • Web App and MySQL Database Configuration in Docker Swarm

  • Bash scripting

  • AWS ECR as Image Repository

  • AWS IAM Policy and Role Configuration

  • AWS EC2 Configuration

  • AWS EC2 Security Group Configuration

  • Terraform Configuration File

  • Git & Github for Version Control System

Resources

terraform-docker-swarm-ecr-phonebook's People

Contributors

devenes avatar

Stargazers

 avatar

Watchers

 avatar  avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.