bazel-diff VS distroless

From the CI perspective, downloading artifacts from a remote cache offers drastic reductions in builds that run through Bazel by avoiding duplicated work. There’s no doubt that this is great all by itself. But, it’s even better to avoid building/downloading/executing parts of your Bazel workspace that haven’t changed. In general, this is called “test selection” and, fortunately, there are open source implementations that are designed to work with Bazel like https://github.com/Tinder/bazel-diff. This approach has offered wonderful improvements to CI build/test times even without a powerful remote cache implementation.

lots of questions here regarding what this product is. I guess i can provide some information for the context, from a perspective of an outside contributor.

Chainguard Images is a set of hardened container images.

They were built by the original team that brought you Google's Distroless (https://github.com/GoogleContainerTools/distroless)

However, there were few problems with Distroless:

1. distroless were based on Debian - which in turn, limited to Debian's release cadence for fixing CVE.

2. distroless is using bazelbuild, which is not exactly easy to contrib, customize, etc...

3. distroless images are hard to extend.

Chainguard built a new "undistro" OS for container workload, named Wolfi, using their OSS projects like melange (for packaging pkgs) and apko (for building images).

The idea is (from my understanding) is that

1. You don't have to rely on upstream to cut a release. Chainguard will be doing that, with lots of automation & guardrails in placed. This allow them to fix vulnerabilties extremely fast.

> If you have one image based on Ubuntu in your stack, you may as well base them all on Ubuntu, because you only need to download (and store!) the common base image once

This is only true if your infrastructure is static. If your infrastructure is highly elastic, image size has an impact on your time to scale up.

Of course, there are better choices than Alpine to optimize image size. Distroless (https://github.com/GoogleContainerTools/distroless) is a good example.

The same as our code dependencies, container updates can include security patches and bug fixes and improvements. However, they can also include breaking changes and it is crucial you test them thoroughly before putting them into production. Wherever possible, I recommend using the distroless base image which will drastically reduce both your image size, your risk vector, and therefore your maintenance version going forward.

# Use a large Node.js base image to build the application and name it "build" FROM node:18-alpine as build WORKDIR /app # Copy the package.json and package-lock.json files into the working directory before copying the rest of the files # This will cache the dependencies and speed up subsequent builds if the dependencies don't change COPY package*.json /app # You might want to use yarn or pnpm instead RUN npm install COPY . /app RUN npm run build # Instead of using a node:18-alpine image, we are using a distroless image. These are provided by google: https://github.com/GoogleContainerTools/distroless FROM gcr.io/distroless/nodejs:18 as prod WORKDIR /app # Copy the built application from the "build" image into the "prod" image COPY --from=build /app/.output /app/.output # Since this image only contains node.js, we do not need to specify the node command and simply pass the path to the index.mjs file! CMD ["/app/.output/server/index.mjs"]

Lots of examples without the entire OS as other comments mention, an example would be Googles distroless[0]

[0]: https://github.com/GoogleContainerTools/distroless

Docker doesn't do this all the time. Distroless Docker containers are relatively common. https://github.com/GoogleContainerTools/distroless

Deployment: https://github.com/GoogleContainerTools/distroless

Or use distroless image as it includes one, among others. https://github.com/GoogleContainerTools/distroless/blob/main/base/README.md