Looking for Some Best Practices for Managing Docker Images in Buildkite Pipelines?

Docker
1

Hello everyone,

I am looking for advice on how to effectively manage Docker images within Buildkite pipelines. Recently, I have run into a few challenges related to optimizing image sizes and improving overall pipeline speed.

Here’s what I have tried so far:

  • Reducing Image Size: I switched to using slimmer base images like alpine but sometimes it leads to dependency issues. Has anyone found a balance between small image sizes and functionality: ??
  • Docker Caching: I have enabled Docker layer caching in my pipeline but I am still facing longer build times when images are pulled during each step. Any tips for making better use of caching or speeding up image pulls: ??
  • Image Tagging Strategy: I’m considering implementing a more structured tagging strategy for my Docker images to avoid pulling outdated versions but I am unsure how to structure this efficiently in a Buildkite environment.

Has anyone else tackled these issues or found other ways to streamline their Docker workflows on Buildkite: ?? I would love to hear what has worked for you, especially for reducing build times and maintaining efficient CI/CD pipelines. I have searched on the web about this and I got this result Docker in Docker, Kaniko or Buildpacks: Building containers in containers on Kubernetes but looking forward to more tips and advices.

Thanks in advance !!

Derek Theler

2

Hey @derektheler112 :wave:

Thanks for sending through your question and welcome to the buildkite community!

  • Reducing Image Size: I switched to using slimmer base images like alpine but sometimes it leads to dependency issues. Has anyone found a balance between small image sizes and functionality: ??

This really depends on what specific image you are using and its purpose. As you have found, changing to a smaller base image (like alpine) will have a noticeable effect on the image size but will also require you to resolve any dependencies manually. If you are able to bundle your dependencies in easily when the image is build then this is a great place to start improving your overall performance.

If you haven’t already looked into it then using the multi-stage feature in your Dockerfile is another way you can shrink the size of docker images. This is a great way to build a working artifact on a specified final image, while leaving behind anything left over from the build process

Reference: Multi-stage | Docker Docs

  • Docker Caching: I have enabled Docker layer caching in my pipeline but I am still facing longer build times when images are pulled during each step. Any tips for making better use of caching or speeding up image pulls: ??

There is actually a docker-compose plugin that may be of interest, this would let you build the images on the fly and cache them as needed between steps which I believe should address the problem your currently facing.

Reference: docker-compose-buildkite-plugin/docs/examples.md at master · buildkite-plugins/docker-compose-buildkite-plugin · GitHub

Another method to speed up the downloading of images would be to use the agent hooks (specifically agent-startup) as a way to pre-pull any required docker base images on to the host during startup, this will ensure the images exist when they are required.

Reference: Buildkite Agent hooks v3 | Buildkite Documentation

  • Image Tagging Strategy: I’m considering implementing a more structured tagging strategy for my Docker images to avoid pulling outdated versions but I am unsure how to structure this efficiently in a Buildkite environment.

I’ve had a look around and I can’t find any suggestions on how to manage tagging docker images. As far as I can tell these wont have any noticeable effect on performance and there is no preference or policy around this, so please feel free to use whatever strategy works for you.

Reference: Image tag best practices - Azure Container Registry | Microsoft Learn

Finally, we do have a few other suggestions on how to improve build times that aren’t docker focused;

  • Implementing parallel testing to divide tests into smaller, independent tasks that can run concurrently.
  • Splitting large builds into smaller, more manageable ones.
  • Only building what’s changed, instead of the entire codebase.
  • Creating multiple job queues with different specification hardware, so that build jobs can be assigned to build agents with appropriate resources.
  • Best practices | Docker Docs

Let me know if you have any questions!