I have a Docker file which creates an image and then I run it using docker compose together with a container built using a Postgres image. (To set up a local environment of Airflow - we use the mwaa local runner).
Recently I got a new M1 pro machine and I’m getting into issues running the container.
The problem is, from my understanding, is that the image is being built and then run using my machine which has a different kind of cpu architecture, which causes pip to look for wheels for this kind of architecture. My college has an intel Mac and he says he doesn’t experience any issues.
The build phase is ok, but when I run the container, we’ve set docker compose to run an entrypoint script that also installs some airflow providers and other dependencies, one of which is plyvel, which fails to install and cause other packages not to install as well. When I remove plyvel from the requirements.txt file, the installation completes but some of my airflow providers are missing some files or attributes which create its own issues.
I tried forcing docker to building and running the image and container using amd64 by changing the build command to:
docker build --platform linux/amd64 --rm --compress $3 -t amazon/mwaa-local:2.2 ./docker which runs but runs very slowly.
Also, added platform: linux/amd64 in docker-compose file to both the postgres and the local-runner containers.
Then, when I spin up the container, it takes a lot of time to get into a working state when I can access the airflow ui in the web browser and then it is very slow in the ui - every link is taking a few seconds to process and direct me to the new place. I believe this is due to some emulation or something.
I then found this article: https://medium.com/nttlabs/buildx-multiarch-2c6c2df00ca2
It says there is a faster way to run without emulation but I didn’t understand how to implement.
In addition, found this Reddit thread: https://www.reddit.com/r/docker/comments/qlrn3s/docker_on_m1_max_horrible_performance/
They suggest building and running the container inside a virtual machine, not sure if that is the way to go in my situation.
I tried both Docker Desktop and Rancher Desktop (with dockerd ) but both shows the same symptoms.