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This is just a quick update to let you know that we’ve released another preview of Docker Desktop for Apple M1 chips, which you can download from our Docker Apple M1 Tech Preview page. The most exciting change in this version is that Kubernetes now works.

First, a big thank you to everyone who tried out the previous preview and gave us feedback. We’re really excited to see how much enthusiasm there is for this, and also really grateful to you for reporting what doesn’t yet work and what your highest priorities are for quick fixes. In this post, we want to update you on what we’ve done and what we’re still working on.

Some of the biggest things we’ve been doing since the New Year are not immediately visible but are an essential part of eventually turning this into a supported product. The previous preview was built on a developer’s laptop from a private branch. Now all of the code is fully integrated into our main development branch. We’ve extended our CI suite to add several M1 machines, and we’ve extended our CI code to build and test Docker Desktop itself and all our dependencies for both architectures in parallel. With the whole pipeline now automated, from now on we will be able to issue new previews on a more regular basis and have more confidence that our changes have not broken anything.

As for feature changes and bug fixes since the last preview, here are some of the highlights:

• Kubernetes now works (although you might need to reset the cluster in our Troubleshoot menu one time to regenerate the certificates).
• The host.docker.internal and vm.docker.internal DNS entries now resolve.
• We removed hard-coded IP addresses: it now dynamically discovers the IP allocated by macOS.
• osxfs file sharing now works.
• We made a configuration change that should improve disk performance.
• The Restart option in the Docker menu works.

The last major thing that we’re still working on is:

• HTTP proxy support. At the moment the HTTP proxy configured on the host is ignored.

Finally, we are aware of the following items which are unfortunately out of our control. Here are our best recommendations for now:

• Some corporate security or VPN software blocks the connection between the host and the VM, or the VM and the outside world. This can happen even if it doesn’t happen on Intel Macs because we had to switch to a new connection method with Apple’s new virtualization framework. There are some possible workarounds posted by users on our github issue, https://github.com/docker/for-mac/issues/5208.
• If you are trying to run Intel-based containers on an M1 machine, they can sometimes crash. We are using a piece of software called qemu to emulate Intel chips on M1 but it occasionally fails to run the container. Where possible we recommend sticking to arm64 containers on M1 machines; they will also be faster.

If you have an M1 Mac, then we invite you to download this new build and try it out. (Just bear in mind that it’s still a preview, so expect some rough edges.) If you encounter any bugs, please let us know on our GitHub repo. If you filed a bug against the previous preview, now would be a good time to retest it and let us know either that it’s now fixed or that it isn’t. You can chat with other users on the #docker-desktop-mac channel on our community Slack. And finally, if you’re the sort of user who wants to be the first to try out early versions of our software (not just M1) we invite you to join our Developer Preview Program.

No one enjoys waiting, and waiting for your software to build and tests to run isn’t fun either—in fact, it’s quite expensive.And if you’re building your Docker image in a CI system like GitHub Actions with ephemeral runners—where a new environment gets spinned up for every build—by default your builds are going to be extra slow.

In particular, when you spin up a new VM with a new Docker instance, the cache is empty, so when you run the Docker build your image has to be built from scratch.

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Luckily, Docker includes some features to allow you to warm up the cache, by pulling previous versions of the image.And the newer BuildKit build system improves this even further—but also requires some changes, otherwise caching will stop working.

Let’s see how you can speed up your Docker builds in CI with classic Docker, and then the improvements (and pitfall) provided by BuildKit.

Why building Docker images in CI can be slow

When you rebuild an existing image, Docker can look in its local cache for existing layers and reuse those if nothing has changed.This allows for faster builds.

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However, in many cases CI runs on a new virtual machine or environment on every run.For example, whenever you run a task in GitHub Actions by default you will be using a new virtual machine.A new virtual machine means a new Docker install, and a new Docker install has an empty cache.

An empty cache means your image will be rebuilt from scratch—and that’s slow.

Speeding up CI builds in classic Docker

In order to make it easier to test things, I’m going to spin up a Docker registry on my computer, equivalent to hub.docker.com or a cloud image registry:

Here’s the Dockerfile we’re going to be building; it’s set up so that if the code changes but requirements.txt is the same, Docker will be able to use the cached layer with the installed dependencies:

Note: Outside the very specific topic under discussion, the Dockerfiles in this article are not examples of best practices, since the added complexity would obscure the main point of the article.

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To ensure you’re writing secure, correct, fast Dockerfiles, consider my Python on Docker Production Handbook, which includes a packaging process and >70 best practices.

In order to simulate building in an ephemeral, newly created VM, we’re going to use the following script to clear the cache in between builds:

Here’s out first pass at a build script: Download catalina os dmg high sierra.

Let’s run this a couple of times; if caching was working correctly this would run really quickly the second time:

As expected, because we’re simulating a new VM with an empty cache, the second build is no faster.

Warming the cache

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In order to speed up the builds, we need to “warm” the cache.In classic Docker we do this by:

1. pulling the image.
2. Using the --cache-from flag to tell docker build to use the pulled image as a source of cached layers.

We modify build.sh appropriately:

Now if we run the script:

That’s a lot faster!

BuildKit: faster, but with pitfalls

Let’s consider how classic caching works: we need to retrieve the whole image.If for example our code has changed, we don’t actually need to download the layer where the code is installed, since we’re not going to reuse it.

Ideally we could just point Docker at the image registry as part of the build, and it would only download the layers it was actually going to reuse.Technically this was possible with classic Docker, but apparently it was buggy and unreliable.

With BuildKit, the new build system for Docker, this is a built-in feature: you can skip the docker pull and just have the build pull the layers it needs.

There is a pitfall, though: by default BuildKit doesn’t include the information needed to reuse images for caching.In order to do so, you have to add an extra flag, --build-arg BUILDKIT_INLINE_CACHE=1, otherwise caching won’t work at all, whether or not you’ve pulled.

Here’s our new build script:

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Let’s try it out:

The first build doesn’t use any of the classic Docker caching so it takes the full amount of time.The second build is sped up—but we didn’t have to do an explicit pull!

In many cases that can speed up builds, as BuildKit can pull only the layers it needs.If you’re using multi-stage builds BuildKit will do some of the build in parallel, giving more opportunities for a speed-up.

Go faster!

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If you’re building Docker images in CI, and each CI run starts with an empty cache, make sure you’re using these techniques to keep your cache warm.You’ll get faster builds, save a little money, and save a little CO₂ too.