A minimal working setup for apple container

With macOS 26, Apple released an open-source container CLI. It aims at providing a lightweight solution to run Linux containers on Mac. Instead of running every container inside a single shared Linux VM (as Docker Desktop and Colima do), the Apple framework gives each container its own lightweight Linux VM, which isolates containers and optimizes performance on macOS.

A minimal container compose setup

I was curious to try it out, but the apple framework does not support the compose feature yet. There is quite some demand on the official github repository, but it would require some work to ship the framework with a fully compatible compose service.

For my purposes, I don’t need that many features from compose to run a container. In most of my projects, I would usually create a slim docker-compose.yml with a service, a few volumes and an environment file attached to it. A typical docker compose file would look like:

services:
  api-server:
    image: connectors-api-server
    build:
      context: .
      dockerfile: ./docker/api-server/Dockerfile
    volumes:
      - ./data:/data
    env_file:
      - aws.env
    ports:
      - "8000:8000"

The goal for me, was then to create a small python script that would parse the yml file, extract the volumes, environment files and ports, and map them correctly to the container CLI. It is relatively straightforward to write and allows a drop-in replacement of docker compose in most of my personal projects.

The script would simply map container-compose-build api-server to the corresponding container build call. Alternatively, I also use container-compose-run api-server bash that would run container run -v ./data:/data --env-file aws.env -p 8000:8000 api-server-image bash.

You can find a working example in my dotfiles.

Conclusion

With some minor scripting, apple container can be used in some trivial compose use cases, and can definitely be used in simple projects. For more complex projects which require a greater number of compose features, I’m afraid I’ll have to fall back to my docker colima setup.

I am however quite happy with the performance of apple container, I usually find the building and running of containers to be faster, and the memory footprint of the docker system running in the background has been reduced.