Dcycle Blog

Docker PHP on the M1 chip, example with Static Analysis on Drupal: 9 times faster

November 17, 2021

In 2020, Apple unveiled a new chip, M1, which uses a different architecture than the Intel chips widely used in servers and laptops.

Docker calls the intel architecture “linux/amd64”, and the M1 architecture “linux/arm64” (can also be linux/arm64/v7, linux/arm64/v8, etc.).

We will attempt to look at a speed test for a typical Dockerized PHP processs.

Our test

I have used a Dockerized version of PHPStan for Drupal that I am maintaining, in order to run the tests.

The goal of this project is to perform static analysis of PHP code, making sure it has an internal logic, without actually running the code (I think of it as a lazy person’s automated testing).

I use Jenkins to rebuild this Docker image weekly to make sure it is always up-to-date. My Jenkins job uses the DigitalOcean API to create a new virtual machine, then uses the technique described by Artur Klauser in his article Building Multi-Architecture Docker Images With Buildx, Artur Klauser, Medium, Jan 18, 2020 to create a multi-architecture image. I have also created a GitHub project which helps set this up on the VM.

The image is available on the Docker Hub.

On a weekly basis, I push a tag 4 which is always the latest version, I also push a tag with the day’s date and time, for example:

  • the tag “4.2021-10-21-20-15-31-UTC” only has the linux/amd64 architecture
  • the tag “4.2021-11-17-13-45-26-UTC” has both linux/amd64 and linux/arm64.

Our test consists of running the static analysis agains the node module, part of the Drupal project.

We have run our tests on the latest version of Docker Desktop:

  • on a mid-2014 dual-core Intel i7 chip Macbook Pro;
  • and on a 2021 M1 Max MacBook Pro.

In both cases, we allocated 10 Gb RAM to Docker; for our Intel mac, we allocate 2 CPUs; and on M1 we allocated 5 CPUs.

Results using emulation

We will start by using a Docker image built only for the linux/amd64 architecture, forcing our M1 Mac to use emulation:

docker pull dcycle/phpstan-drupal:4.2021-10-21-20-15-31-UTC
time docker run --rm dcycle/phpstan-drupal:4.2021-10-21-20-15-31-UTC /var/www/html/core/modules/node --memory-limit=-1

On our 2014 Intel Macbook, we get 1:27.258; and on M1, we get 1:25.16, not a speed increase you’d write to your mother about (not that she’d understand if you did).

In this case M1 warns us:

WARNING: The requested image's platform (linux/amd64) does not match the detected host platform (linux/arm64/v8) and no specific platform was requested

(For these tests, we’re not interested in the actual static analysis test results, although there are some interesting tidbits in there; you can see you this can be useful for your own projects.)

Results with a native ARM image

Recall that the tag “4.2021-11-17-13-45-26-UTC” was optimized for both Intel and M1 chips.

docker pull dcycle/phpstan-drupal:4.2021-11-17-13-45-26-UTC
time docker run --rm dcycle/phpstan-drupal:4.2021-11-17-13-45-26-UTC /var/www/html/core/modules/node --memory-limit=-1

Now we have a more eyebrow-rising speed increase: 9.782 seconds for the M1. Unsurprisingly, the above has very little variation on the Intel chip.


If you’re using PHP Docker images in emulation module, there is virtually no speed increase between a 2014 Intel-based Macbook Pro and and a M1 Max-based Macbook Pro.

However, if you invest in using M1-optimized images, like I did with my PHPStan Drupal image, you can reap very interesting speed increases for your PHP, and other, Docker jobs.