Automate Your Development Workflow with CI/CD and Docker

Introduction

The use of modern deployment tools has revolutionized how we manage and deliver software. Docker, an essential technology for containerization, allows you to package applications and their dependencies into portable containers. Combined with the AWS CI/CD pipeline, Docker offers automation, scalability, and efficiency, making it suitable for projects of varying sizes.

In this article, we will present a practical guide to deploying a Java application in a Docker container using the AWS CI/CD pipeline. Additionally, we will discuss the importance of Docker and how Docker Compose simplifies the management of multi-container applications.

Why We Chose AWS CI/CD

AWS stands out for its integration, scalability, and automation capabilities, making its combination with Docker highly effective. The main reasons include:

• Scalability: Services like EC2 automatically adjust to demand, ensuring cost efficiency and high availability.
• Seamless Integration: Tools like CodePipeline, CodeBuild, and CodeDeploy naturally connect with services like ECR, RDS, and ALB.
• Automation: Automating builds, tests, and deployments eliminates manual errors and saves time.

Best Practices to Follow

• IAM Roles: Assign only necessary permissions to ensure security resilience.
• Resource Tagging: Helps in tracking costs and identifying resources.
• Cost Optimization: Periodically assess resource usage to improve cost management.

Prerequisites

1. AWS Account

An active AWS account with the necessary permissions.

2. EC2 Instance

An Amazon EC2 instance will act as the deployment server, running a supported operating system.

3. IAM Roles

Create IAM roles with appropriate permissions:

• CodeDeploy Role: Allows CodeDeploy to interact with other AWS services.
• EC2 Instance Role: Necessary for communication with CodeDeploy and other AWS services.

4. Source Control Repository

Set up a source code repository, such as AWS CodeCommit, GitLab, or GitHub.

5. Amazon S3

An S3 bucket configured to store deployment artifacts and logs.

Containerizing Applications

Containerization is fundamental to our deployment strategy. Here’s how we perform containerization with Docker:

• Defining a Dockerfile: Specify the necessary steps to create the application image.

# Use the official OpenJDK image as the base image
FROM public.ecr.aws/docker/library/openjdk:17
# Set the working directory
WORKDIR /app
# Copy the application JAR file to the container
COPY target/java-app.jar /root/ROOT.jar
# Expose the application port
EXPOSE 8080
# Set the command to run the application
ENTRYPOINT /sbin/entrypoint.sh

Managing and Versioning Docker Images with Amazon ECR

Amazon ECR is crucial for managing and versioning our Docker integration with AWS.

Create a Repository on AWS ECR: Using ECR ensures version control and simplifies deployments.

Automating Deployment with AWS CodePipeline

The AWS CodePipeline manages the CI/CD pipeline in an integrated manner:

• Source Stage: Retrieves the latest code from the repository.
• Build Stage (CodeBuild): Builds the Docker image and sends it to Amazon ECR.

BuildSpec File

version: 0.2
phases:
  install:
    runtime-versions:
      java: corretto17
      docker: 20
    commands:
      - mvn clean install -DskipTests
  pre_build:
    commands:
      - aws ecr get-login-password --region $AWS_DEFAULT_REGION | docker login --username AWS --password-stdin $AWS_ACCOUNT_ID.dkr.ecr.$AWS_DEFAULT_REGION.amazonaws.com
  build:
    commands:
      - mvn package -DskipTests
      - docker build -t $IMAGE_REPO_NAME:$IMAGE_TAG .
  post_build:
    commands:
      - docker push $AWS_ACCOUNT_ID.dkr.ecr.$AWS_DEFAULT_REGION.amazonaws.com/$IMAGE_REPO_NAME:$IMAGE_TAG

Setting Up Artifact Storage

Use Amazon S3 as an artifact repository to ensure effective and organized storage.

1. Configuring the S3 Bucket

• Access the S3 service in the AWS console.
• Select create bucket and assign a unique name.
• Enable versioning to maintain the artifact history.

2. Configuring Bucket Permissions

Grant the necessary permissions to allow CodePipeline and CodeBuild to upload artifacts.

Integrating with CodePipeline

• Create a new pipeline in AWS CodePipeline.
• Select your Git repository in the source provider section.
• Set the artifact location in the previously created S3 bucket.
• Choose CodeDeploy as the deployment provider.

Conclusion

Adopting CI/CD in AWS has transformed our deployment process. By utilizing Docker containerization with services like EC2, ECR, and CodePipeline, we created an automated and scalable system. This allows teams to focus on innovation and delivering value while AWS manages the complexities.

CI/CD with Docker and AWS is the perfect solution for modernizing deployment workflows, promoting automation and agility in deliveries.

Source: CI/CD with Docker and AWS: Automating Your Development Workflow