It makes it very easy to define the environment and conditions in which a process is run, and completely isolate it from the rest of the system. The environment includes all the other software installed in said isolated environment. Since you have complete isolation you can install all the software that comes with what we think if as a linux “distribution”, which means you can do something like run a docker container that is “ubuntu” or “debian” on a “CentOS” or whatever distribution.
When you start a Dockerfile with the statement FROM ubuntu:version_tag you are more or less saying “I want to run a process in an environment that includes all of the3 software that would ship with this specific version of ubuntu”
A linux distro == Kernel + “user land” (maybe not the correct terminology). A docker container is the “user land” or “distro” + whatever you’re wanting to run, but the Kernel is the host system.
I found this pretty helpful in explaining it: https://earthly.dev/blog/chroot/
I’ll also say that folks say pretty nonchalantly deride Docker and other tools as if it’s just “easy” to set these things up with “just linux” and Docker is something akin to syntax sugar. I suspect many of these folks don’t make software for a living, or at least don’t work at significant scale. It might be easy to create an isolated process, it’s absurd to say that Docker (or Podman, etc…) doesn’t add value. The reproducibility, layering, builders, orchestration, repos, etc… are all build on top of the features that allow isolation. None of that stuff existed before docker/other container build/deploy tools.
Note: I’m not a Linux SME, but I am a software dev who uses Docker every day — I am likely oversimplifying some things here, but this is a better and more accurate oversimplification than “docker is like a VM”, which is a helpful heuristic when you first learn it, but ultimately wrong
So true. I’m on an AI product team. None of the engineers know that much about learning/ai — our expertise is in high availability/scalability/distributed systems.
The AI part it when a data scientist hands us a notebook and says: implement this algorithm.