AWS CodePipeline is a fully-managed continuous delivery service that helps automate the release process for software changes. It enables developers and development teams to rapidly and reliably deploy code changes by integrating with various third-party services like AWS CodeCommit, CodeBuild, CodeDeploy, and more. Here is a step-by-step look at how CodePipeline deploys code changes to AWS:

CodePipeline leverages the concept of pipelines to automate the different stages of the delivery process and release code to production in a coordinated manner. A pipeline in CodePipeline is made up of actions that represent individual steps or activities like building, testing, or deploying code. The key stages in a typical CodePipeline deployment pipeline include:

Source – This stage monitors the source code repository like AWS CodeCommit for any new changes or code commits. CodePipeline automatically detects each new change and triggers the next stage in the pipeline. Some common source providers integrated with CodePipeline include CodeCommit, GitHub, Bitbucket, and S3.

Build – In this stage, CodePipeline runs automated build/test processes on the newly committed code using services like CodeBuild or third-party CI/CD tools like Jenkins, Travis CI, etc. CodeBuild containers are auto-scaled based on demand to ensure builds are seamless and efficient. Build outputs like artifacts containing the build packages are produced and passed to subsequent stages.

Test – This stage runs automated tests like unit, integration, or UI/API tests on the build outputs using services like CodeBuild, third-party tools or custom test runners. Test results are captured and used to determine if the code passes muster for production release or needs additional work.

Deploy/Release – If the code passes all quality checks in the previous stages, it is automatically deployed to various test, staging or production environments using deployment plugins. Some common deployment plugins supported by CodePipeline include CodeDeploy for auto scaling groups/EC2 instances, Amazon ECS, Lambda, CodeDeploy for blue/green deployments, manual approval step etc.

For each new code commit, CodePipeline initializes a new instance of the pipeline and sequentially triggers the connected actions in each stage based on Amazon States Language (ASL). It tracks the whole deployment process and ensures either the entire pipeline executes successfully or rolls back on any failures. Developers receive notifications at each stage and can easily see the current pipeline execution state and history in the CodePipeline console for auditing and troubleshooting purposes.

Some key things that make CodePipeline an effective deployment tool include:

It provides a standardized, repeatable deployment process that is declarative, visible and auditable.

Entire pipelines can be version controlled, tested and gradually changed over time without interrupting existing deployments.

Individual stages can be easily added, removed or reordered as needed without affecting the overall flow.

Powerful integration with various third-party DevOps tools allows leverage of existing workflows where possible.

Automatic scaling of build agents and seamless parallelization of unit/integration tests improves deployment efficiency.

Easy to set permissions using IAM to control who can modify, view or execute pipelines.

Robust rollback mechanisms ensure code deploys only if all checks pass and failed deployments don’t leave applications in inconsistent states.

Integrated notifications and dashboards provide clarity on pipeline executions and failures for quick troubleshooting.

Pipelines can be re-run on demand or automatically based on certain triggers like a new Git tag.

CI/CD best practices like immutable infrastructure, blue/green deployments, canary analysis are readily supported out of the box.

So CodePipeline provides a cloud-native continuous delivery solution for automating code deployments to any AWS infrastructure using a simple yet powerful API-driven model. It takes away the operational overhead of manually coordinating releases while delivering faster, more reliable software updates at scale for modern applications.