Dshala Backend project

In this project, we are using django as the backend framework and postgresql as the backend database.

Django CI/CD Pipeline in AWS

Why CI/CD?

Continuous Integration and Continuous Deployment offer several benefits:

• Speed and Efficiency: Automate processes to release new features and bug fixes quickly.
• Reliability: Identify and fix errors early in development to ensure high-quality software.
• Collaboration: Facilitate teamwork by integrating code changes into a shared repository.
• Continuous Feedback: Receive quick feedback through continuous testing and deployment.
• Enhanced Security: Detect and address security vulnerabilities promptly.

Setting Up the CI/CD Pipeline

Follow these steps to implement the CI/CD pipeline in AWS:

1. Create a New IAM Role

• Log in to your AWS account.
• Navigate to IAM in the AWS Management Console.
• Create a new IAM role with permissions for services such as CodeDeploy and S3 access.

2. Create an EC2 Instance

• Launch an EC2 instance using the Ubuntu 20.04 or 20.10 image.
• Configure instance settings, including security options and key pairs.

3. Install CodeDeploy-Agent on the Server

• Connect to your server and update repositories.
• Install necessary packages: sudo apt install ruby-full and sudo apt install wget.
• Download and install the CodeDeploy-Agent.
• Verify the installation status: sudo service codedeploy-agent status.

4. Set Up Configuration Files

Create two crucial configuration files in the root directory of your GitHub repository:

• buildspec.yml: Contains build configurations for AWS CodeBuild.
• appspec.yml: Contains deployment configurations for AWS CodeDeploy.

5. Create a CodePipeline

• In the AWS Management Console, navigate to CodePipeline.
• Create a new build project in CodeBuild, specifying source, environment, buildspec file, and log preferences.
• Create a CodeDeploy application and deployment group.
• Create a CodePipeline, connecting GitHub as the source and integrating CodeBuild and CodeDeploy for build and deployment stages.

This automated pipeline triggers a release, cloning the repository, running tests, and deploying the application to the server.