I’ve been building Docker images for a few years now, but the concept of a “pet container workstation” is relatively new. I’m planning to run Silverblue 29 and Antergos in a dual-boot on my workstation and sticking with Windows 10 Pro and Antergos on my gamer laptop.
My main workload is data science, specifically R / RStudio and PostgreSQL. So it lends itself well to a container environment - this project was in part inspired by Silverblue: https://github.com/znmeb/data-science-pet-containers.
The gotcha with a pet container workflow is that it doesn’t really work on Windows 10 Pro or MacOS. Docker on those systems is done inside a full virtual machine running Linux. That machine has a virtual disk drive and is typically allocated a fraction of the RAM the system has.
For example, on my gamer laptop, the Docker VM gets 2 GB of RAM out of the 8 GB the laptop has. This kind of inefficiency is intolerable for data science, so I run native binaries on Windows.
Advice for setting up a Silverblue workstation: I’d say do as much as you can with pre-built images from the Docker Store / Docker Hub. For example, Data Science Pet Containers is built on the official PostgreSQL and pgAdmin images along with the official “Rocker” RStudio image. I’m still using Docker Compose for orchestration but the trend is clearly towards Kubernetes.
And do as much as you can on the desktop with Flatpaks. In my case, the only apps I have on my desktop that are available as Flatpaks but installed from the Silverblue repos are stable Firefox and GNOME Boxes.