@Marvin Hi all Just browsed through the

prefect

,

dask

and

ray

documentation and my head is spinning a bit... I'll be needing to run the same simulation multiple times, in parallal (embarassingly so), based on different parametrizations. I'll be doing this at our users' request, so users say go and we queue, say, 70 simulations for that user. In the meantime another user comes along, etc. The simulations will be run within a docker container, so I'm thinking to deploy to Kubernetes, with pods (and underlying nodes) scaling automatically with the number of queued jobs. So far so good. However, I have a hard time figuring out whether each single simulation should be a sub-workflow so that it can be scheduled onto pods via a Kubernetes worker pool by Prefect alone or wether a simulation should be a task, which is then scheduled by

dask

onto a distributed

dask

cluster backed by Kubernetes. At which point I'm wondering why I need prefect in the first place. So I guess my general questions is - excuse the maybe a bit confrontational wording - what benefit does prefect provide over plain

dask

, e.g.? Thanks a bunch!