go-containerregistry VS docker-tools

I also explored another module, go-containerregistry, in order to build images without root privileges. The approach is completely different, and we can manipulate each component of the container image separately. This can present an advantage, if you're looking for a way to fine tune things.

Use crane ls in a different job to check the tags in the registry. Create an artifact from its output that you evaluate in your kaniko job to check if the build should run or not.

Multi-arch builds are easy to "transfer" IMHO

crane cp docker.io/openfaas/gateway:0.10.0 ghcr.io/openfaas/gateway:0.10.0

If you've not used it yet - do take a look. Crane doesn't pull the images into a local Docker library for re-tagging and re-pushing.

https://github.com/google/go-containerregistry/blob/main/cmd...

crane - tool to copy images from one repo to another - https://github.com/google/go-containerregistry/blob/main/cmd/crane/doc/crane.md

pretty sure the crane being referred by alex is this one: https://github.com/google/go-containerregistry/tree/main/cmd/crane

https://github.com/google/go-containerregistry/tree/main/cmd...

It was recommended in this article:

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!

Look at using tools like skopeo or crane

Pretty much any tool works: docker, podman, kaniko, crane(if you're brave), ko... list goes on.

For the scanning, we (.NET team) use the scanning services provided in Azure Container Registry (ACR). This is an internal ACR and the results of that are internal as mentioned in the post.

All the other tooling we use is open source. You can find our build infrastructure at https://github.com/dotnet/docker-tools. There's a tool there called image-builder that provides much of the functionality. I've written a blog post on how we use Azure Pipelines to manage the builds. Between image-builder and the pipelines, there's some automation that automatically rebuilds our images whenever a parent image changes.