Development tools

AWS offers development tools, such as code storage repositories and building tools for managing deployment strategies:

• CodeStar: AWS CodeStar is a tool where we can create, manage, and work on software projects. It comes with easy integration with other AWS services, such as CodeCommit, CodePipeline, CodeBuild, CodeDeploy, and others. It also supports various programming languages, such as C#, HTML5, Java, Node.js, Ruby, PHP, and Python.
• CodeCommit: AWS CodeCommit is a code repository service fully managed by AWS. It provides private Git repositories for enterprises to use as source control. CodeCommit is also compatible with Git tools.
• CodeBuild: AWS CodeBuild is a build service that compiles source code, executes tests, and creates deployable or consumable files. CodeBuild is a fully managed service provided by AWS. It scales as per user requirements and is charged based on minutes used to build the code.
• CodeDeploy: AWS CodeDeploy is an automated application deployment service. CodeDeploy supports deployment to EC2 instances and on-premise servers, and can take deployable files from various locations, such as GitHub, AWS S3 Bucket, and Bitbucket.
• CodePipeline: AWS CodePipeline is an automated service to release an application. CodePipeline allows us to visualize the build and deploy process. We can create multiple stages where CodePipeline first builds your application, executes tests, deploys to the pre-production environment via CodeDeploy or any other deployment process, and then moves to the production environment.
• Cloud9: AWS Cloud9 provides an Integrated Development Environment (IDE) that resides on the cloud and can be accessed from the browser. Cloud9 allows us to write, run, and debug applications in many languages, such as JavaScript, PHP, Python, Java, and many more.
• X-Ray: AWS X-Ray provides analysis of the application, which is useful for developers, architects, or product leads. It provides performance analysis of the application and its connected services. This analysis can later be used to identify any performance issues or errors in the system.