AWS CodeBuild is a fully managed continuous integration and continuous deployment (CI/CD) service provided by Amazon Web Services (AWS). It automates the build, test, and packaging phases of the software development lifecycle, allowing developers to quickly and reliably compile their code, run tests, and produce deployable artifacts.

Importance of AWS CodeBuild for AWS Engineers

For AWS engineers, CodeBuild plays a crucial role in streamlining the software delivery process and ensuring the quality and reliability of applications deployed on AWS infrastructure. Here are several reasons why AWS engineers utilize CodeBuild:

Automated Builds: CodeBuild eliminates the need for manual build processes by automating the compilation, testing, and packaging of code. Engineers define build specifications using build environment configurations and build commands, allowing CodeBuild to execute these tasks consistently and reproducibly.
Scalability and Flexibility: CodeBuild scales seamlessly to accommodate varying workloads and project sizes. Engineers can configure build environments with custom compute resources, such as CPU and memory, to meet the specific requirements of their applications. This flexibility allows for efficient resource utilization and faster build times.
Integration with AWS Services: CodeBuild integrates seamlessly with other AWS services, including AWS CodeCommit, AWS CodePipeline, and AWS CodeDeploy. Engineers can orchestrate end-to-end CI/CD pipelines by connecting CodeBuild to these services, automating the entire software delivery process from source code to deployment.
Dependency Management: CodeBuild supports dependency management tools like Maven, Gradle, npm, and pip, enabling engineers to easily manage project dependencies and libraries. CodeBuild automatically installs and caches dependencies based on the build specifications, reducing build times and ensuring consistent build environments.
Testing and Quality Assurance: CodeBuild facilitates automated testing by executing unit tests, integration tests, and other quality assurance checks as part of the build process. Engineers can define test suites and scripts within the build specifications, allowing CodeBuild to execute them alongside the compilation and packaging steps.
Artifact Generation: After successfully completing the build process, CodeBuild generates deployable artifacts, such as executable binaries, Docker images, or deployment packages. These artifacts are stored in Amazon S3 or other designated repositories, ready for deployment to AWS infrastructure or external environments.
Cost Optimization: CodeBuild offers a pay-as-you-go pricing model, where engineers only pay for the compute resources consumed during the build process. By leveraging managed build environments and optimizing build configurations, engineers can minimize build costs while maximizing productivity.

Real-Time Example:

Consider a scenario where an AWS engineer is responsible for developing and deploying a microservices-based web application on AWS infrastructure. Here's how they leverage AWS CodeBuild in their workflow:

1. Project Setup: The engineer sets up a CodeCommit repository to host the source code of the web application. They define the project structure and configure build specifications using a buildspec.yml file placed in the root directory of the repository.

2. Continuous Integration Pipeline: The engineer creates a CI/CD pipeline using AWS CodePipeline, which orchestrates the entire software delivery process. The pipeline consists of several stages, including source, build, test, and deploy.

3. Build Stage Configuration: In the build stage of the pipeline, the engineer integrates CodeBuild as the build provider. They configure the CodeBuild project with the necessary build environment settings, such as the programming language, runtime version, and build commands.

4. Build Specifications: Within the buildspec.yml file, the engineer defines the build commands and phases required to compile, test, and package the application. This includes installing dependencies, running unit tests, building artifacts, and generating reports.

5. Automated Testing: CodeBuild executes automated tests, including unit tests and integration tests, as part of the build process. The engineer ensures that the test results are captured and reported accurately, enabling timely feedback on the application's quality and stability.

6. Artifact Generation: Upon successful completion of the build, CodeBuild generates deployable artifacts, such as Docker images containing the microservices or ZIP files containing serverless functions. These artifacts are uploaded to an Amazon S3 bucket or an artifact repository for storage and later deployment.

7. Parallel Builds and Optimization: To expedite the build process, the engineer configures CodeBuild to perform parallel builds for different components of the application. They optimize build configurations, including resource allocation and caching strategies, to minimize build times and maximize resource utilization.

8. Continuous Deployment: Once the artifacts are generated, CodePipeline triggers the deployment stage, which deploys the application to AWS infrastructure using services like AWS Elastic Beanstalk, AWS Lambda, or Amazon ECS. The engineer monitors the deployment process and ensures the successful rollout of new application versions.

9. Monitoring and Feedback Loop: Throughout the process, the engineer monitors build and deployment metrics using AWS CloudWatch and other monitoring tools. They analyze build logs, test results, and deployment statuses to identify issues, optimize performance, and iterate on the development process.

10. Iterative Development and Improvement: As the project evolves, the engineer iterates on the CI/CD pipeline, refines build specifications, and introduces new automation tools and techniques to improve efficiency, reliability, and scalability. They collaborate with team members to incorporate feedback and implement best practices.

Conclusion:

In this example, AWS CodeBuild serves as a critical component of the CI/CD pipeline, automating the build, test, and deployment phases of the software delivery process. By leveraging CodeBuild and other AWS services, the engineer accelerates development cycles, improves code quality, and delivers resilient and scalable applications on AWS infrastructure. CodeBuild empowers AWS engineers to focus on innovation and business value, driving continuous improvement and customer satisfaction.

Create a simple index.html file in CodeCommit Repository

First we need to open to AWS Code Commit and Create repository.

No need to change any thing, Just click to create button. After that go IAM And Create a user and provide the permissions.

After that go to USER, go Security credentials and go to HTTPS Git credentials for AWS CodeCommit, Gereate the credentials. How to creeate a user you can check my IAM Blog (Click here).

After that we need to Visual studio code and open the folder and create a file

Now we need to one in integrated terminal.

Now we need to go to code commit and clone the https, After that Click to clone url and Click to clone https. Now we have recevied clone url copy this url and paste to visual studio code. when you paste this url it need to HTTPS Git credentials for AWS CodeCommit. Provide that credentials.

Now clone is done, First we need to init all and check which branch we have.

So we have master branch so we need run add command because index.html file is blogs to working directoy need to push staging area.

Now, we need to commit and provide some message.

Now, we need to push this file to code commit.

Now push command is done, go to the code commit and refresh the service. we have index. html file

Build the index.html using nginx server

Now go to the code build service, go to the build projects.

Click to Create Project.

No need to change anything just click create build project.

Now we need to do buildspec.yml file and push this file to Codecommit

Buildspec.yml file:

version: 0.2
os: linux

phases:
  install:
    commands:
      - echo "Installing NGINX"
      - sudo apt-get update -y
      - sudo apt-get install -y nginx

  build:
    commands:
      - echo "Build started on $(date)"
      - cp index.html /var/www/html/

  post_build:
    commands:
      - echo "Configuring NGINX"

artifacts:
  files:
    - /var/www/html/index.html

Now go the Code commit and see we have buildspec file.

Now go the code build service and start build service.

Now all the code build service success.

Now go S3 Bucket and create a one bucket.

Now we have codebuildbucket22 bucket. how to create a bucket just go to my blog (click this link here).

Now go to the codebuildbucket22 and create a folder also copy the url.

Now we need to go the codebuild and go to the artifacts upload location. click to edit button and go to artifacts.

For Path paste the URL, go S3 Bucket that is codebuildbucket22, go the folder code_output_demo and copy the url and paste here path section include artifact.zip.