It's still used in edu and research. Haven't seen it in working environments in quite some time as well.

At least on my cluster, few if any workloads are containerized. We also have an EKS where folks run containerized, but that's more inference and web serving, rather than training.

Very common in education/research systems. Even the things which are containerised often have conda in them.

> I work professionally in ML and have not had to touch conda in the last 7 years. In an ML cluster, it is hopefully containerized and there is no need for that?

I wish my life had been like this. Unfortunately I always appear to end up needing to make this stuff work for everyone else (the curse of spending ten years on Linux, I suppose).

But then ML is a very broad church, and particularly if you're a researcher in a bigger company then I could see this being true for lots of people (again, i wish this was me).