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Comment by ekcasey | Hacker News Reader

Image rebasing and layer reuse really matter at scale. Patching base images for many images simultaneously in a registry is a huge win if you are an organization running thousands of containers and there is a CVE in one of the OS packages in your base image. Optimizing data transfer similarly matters when you add up the gains across many containers.

And devs like fast builds too :)

I also don't really see how this project is "incompatible" with anything in the docker ecosystem. I hope Dockerfiles have a long and healthy life. CNBs are another method to build OCI compatible images that provides a lot of benefits for some types of users and use cases.

I expect that the pack cli will eventually build on top of and take advantage of Buildkit

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The incompatibility I mentioned is with Dockerfiles.

You’re right that more flexible patching and optimizing transfers are valuable. But those problems are independent of build frontends: you could solve them once for both buildpacks and Dockerfiles. In fact buildkit is well on its way to doing exactly that.

Basically I would prefer if buildpacks and Dockerfiles could all be built with the same tooling. CNB seems like a wasted opportunity to do that, because it bundles two things that should be orthogonal: a new build format, and a new build implementation. Docker is going in the opposite direction by unbundling the format (Dockerfile) from the implementation (buildkit).

> But those problems are independent of build frontends: you could solve them once for both buildpacks and Dockerfiles.

You can build an image with both technologies, but that's not the key to the argument. The key here is every Dockerfile is unique and potentially quite different from any other Dockerfile. Small differences in layer order and layer contents multiply to very large inefficiencies at scale.

The way you tackle this problem is to make the ordering and contents of layers predictable for any given software that is being built. You can achieve this with Dockerfiles with golden images, strict control of access to Dockerhub, complicated `FROM` hierarchies, the whole shebang.

But at that point you are reinventing buildpacks, at your own expense.

Note that this doesn't change with or without buildkit.

> a new build format, and a new build implementation. Docker is going in the opposite direction by unbundling the format (Dockerfile) from the implementation (buildkit).

Is your understanding that we invented a new image format or that we rewrote most of Docker? Or that the way we've written it prevents, for all times and all purposes, adopting buildkit as part of the system in future?

Because both of those are misapprehensions. We have extensively reused code and APIs from Docker, especially the registry API.

> Small differences in layer order and layer contents multiply to very large inefficiencies at scale.

Can you provide an example of how layer order can cause an issue?

Consider:

    FROM nodejs
    COPY /mycode /app
    RUN npm install /app

Now suppose I change my app code. In a Dockerfile situation, the change to the `COPY` invalidates the `RUN npm install /app` layer, even if I didn't change anything that NPM would care about.

An NPM buildpack can signal that there's nothing to change, allowing the overall lifecycle to skip re-building that layer.

There's also the problem of efficient composition. Suppose I have this:

    RUN wget https://example.com/popular-shell-script.sh && \
        go get https://git.example.com/something-else@abc123 && \
        ./popular-shell-script.sh && \
        rm ./popular-shell-script

And this:

        RUN go get https://git.example.com/something-else@abc123

Both of the resulting images will contain the same `something-else` binary and in an ideal world of file-level manifests I could save on rebuilds and bandwidth consumption (NixOS has this, approximately).

But I don't get to do that, because the layers have different overall contents and different digests. Buildpacks don't get you all the way to a file-centric approach, but because they follow a repeatable, controlled pattern of selecting the contents and order of layers, they greatly improve layer reuse between many images.

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