apko VS rules_docker

apko allows us to build OCI container images from .apk packages.

We have built something very similar to what you are describing: https://github.com/chainguard-dev/apko

apko

Chainguard also appears to have several open source projects.The most popular one is apko, used for building OCI images from APK packages.

Once those are done, I just need to build aws-cli package, put those APK files in a final image with Chainguard's apko.

This is one of my absolute favorite topics. Pardon me while I rant and self-promote :D

Dockerfiles are great for flexibility, and have been a critical contributor to the adoption of Docker containers. It's very easy to take a base image, add a thing to it, and publish your version.

Unfortunately Dockerfiles are also full of gotchas and opaque cargo-culted best practices to avoid them. Being an open-ended execution environment, it's basically impossible to tell even during the build what's being added to the image, which has downstream implications for anybody trying to get an SBOM from the image for example.

Instead, I contribute to a number of tools to build and manage images without Dockerfiles. Each of them are less featureful than Dockerfiles, but being more constrained in what they can do, you can get a lot more visibility into what they're doing, since they're not able to do "whatever the user wants".

1. https://github.com/google/go-containerregistry is a Go module to interact with images in the registry and in tarballs and layouts, in the local docker daemon. You can append layers, squash layers, modify metadata, etc.

2. crane is a CLI that uses the above (in the same repo) to make many of the same modifications from the commandline. `crane append` for instance adds a layer containing some contents to an image, entirely in the registry, without even pulling the base image.

3. ko (https://ko.build) is a tool to build Go applications into images without Dockerfiles or Docker at all. It runs `go build`, appends that binary on top of a base image, and pushes it directly to the registry. It generates an SBOM declaring what Go modules went into the app it put into the image, since that's all it can do.

4. apko (https://apko.dev) is a tool to assemble an image from pre-built apks, without Docker. It's capable of producing "distroless" images easily with config in YAML. It generates an SBOM declaring exactly what apks it put in the image, since that's all it can do.

Bazel's rules_docker is another contender in the space, and GCP's distroless images use it to place Debian .debs into an image. Apko is its spiritual successor, and uses YAML instead of Bazel's own config language, which makes it a lot easier to adopt and use (IMO), with all of the same benefits.

I'm excited to see more folks realizing that Dockerfiles aren't always necessary, and can sometimes make your life harder. I'm extra excited to see more tools and tutorials digging into the details of how container images work, and preaching the gospel that they can be built and modified using existing tooling and relatively simple libraries. Excellent article!

Depends exactly what you're trying to create it for. I advocate for doing it during the build process rather than as a step after.

We open sourced a few tools that do it automatically for containers:

https://github.com/chainguard-dev/apko

https://github.com/chainguard-dev/melange

apko takes apk packages and builds them into OCI images (aka Docker images). Sounds quite simple, because it is:

My company uses Bazel's rules docker to build our images: https://github.com/bazelbuild/rules_docker

They're pretty great and have a lot of the caching and parallelism benefits mentioned in the post for free out of the box, along with determinism (which Docker files don't have because you can run arbitrary shell commands). Our backend stack is also built with Bazel so we get a nice tight integration to build our images that is pretty straightforward.

We've also built some nice tooling around this to automatically put our maven dependencies into different layers using Bazel query and buildozer. Since maven deps don't change often we get a lot of nice caching advantages.

I've seen rules_docker is looking for maintainers here ; Does this mean it doesn't use it that much internally? If so, how do they go about using other services e.g docker-compose for running external services e.g database?

Did you mean this one? https://github.com/bazelbuild/rules_docker

I was very interested in this Bazel-based way of building containers but its README page says "it is on minimal life support," which does not inspire confidence. How's your experience using it?

As others have said docker in docker or a separate build server are your best options using docker. You can also use Bazel (which doesn't require the docker daemon) to build docker images which will build deterministic images every time due to not incorporating the timestamp: https://github.com/bazelbuild/rules_docker

There's some BazelCon talks about people doing similar stuff but not actually open sourcing their code.

P.S. if you use rules_docker please feel free to open a PR to add your company to our README: https://github.com/bazelbuild/rules_docker/#adopters

The docker utility isn't the only way to build and run containers. There's also cri-o, podman, and crun among others for running containers. For building there is podman again, Jib for Java applications, and bazel plus many others. The docker approach of using a client to connect to a daemon required to run as root has turned out to be slow and insecure.

During the last 3 years I've had the pleasure of using Bazel's rules_docker to generate all my container images (https://github.com/bazelbuild/rules_docker).

In a nutshell, rules_docker is a set of build rules for the Bazel build system (https://bazel.build). What's pretty nice about these rules is that they don't rely on a Docker daemon. They are rules that directly construct image tarballs that you can either load into your local Docker daemon or push to a registry.

What's nice about this approach is that image generation works on any operating system. For example, even on a Mac or Windows system that doesn't have Docker installed, you're able to build Linux containers. They are also fully reproducible, meaning that you often don't need to upload layers when pushing (either because they haven't changed, or because some colleague/CI job already pushed those layers).

I guess rules_docker works fine for a variety of programming languages. I've mainly used it with Go, though.