Official Docker images for AWS CodeBuild with pre-configured build environments for various programming languages and compute platforms.
AWS CodeBuild Docker Images is a collection of official Dockerfiles that define the build environments used by AWS CodeBuild. These images provide pre-configured environments with specific language runtimes, tools, and dependencies needed for building applications in AWS's managed CI/CD service. They ensure consistency between local development and cloud-based builds.
AWS CodeBuild users who need consistent build environments, DevOps engineers managing CI/CD pipelines on AWS, and developers who want to test builds locally before running them in CodeBuild.
These images are officially maintained by AWS, ensuring full compatibility with CodeBuild's features and services. They provide standardized environments that eliminate configuration drift and reduce setup time for build pipelines.
Official AWS CodeBuild repository for managed Docker images http://docs.aws.amazon.com/codebuild/latest/userguide/build-env-ref.html
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These are the official Dockerfiles for AWS CodeBuild, ensuring full compatibility with the service and reducing configuration errors, as stated in the README.
Supports key languages like Java, .NET, Go, Node.js, Python, and Ruby with multiple versions, detailed in the maintained images list for EC2 and Lambda compute.
The README provides clear commands to build and run images locally with Docker, such as using `docker run -it --entrypoint sh` for interactive debugging.
Images are available for both x86_64 and aarch64 architectures, enabling builds for ARM-based AWS instances or Lambda functions, as shown in the directory structure.
These images are tightly coupled with AWS CodeBuild and Lambda, making them less portable and unsuitable for projects targeting other clouds or on-premises environments.
The README admits that some images are no longer maintained and may not build, forcing users to migrate and potentially breaking existing pipelines without warning.
With nested directories for Ubuntu, Amazon Linux, architectures, and versions, navigating to find the right Dockerfile can be confusing and error-prone for newcomers.