I think there are some things this misses about the scientific ecosystem in Universities/etc. that can make the cloud more attractive than it first appears:

* If you want to run really big jobs e.g. with multiple multi-GPU nodes, this might not even be possible depending on your institution or your access. Most research-intensive Universities have a cluster but they’re not normally big machines. For regional and national machines, you usually have to bid for access for specific projects, and you might not be successful.

* You have control of exactly what hardware and OS you want on your nodes. Often you’re using an out of date RHEL version and despite spack and easybuild gaining ground, all too often you’re given a compiler and some old versions of libraries and that’s it.

* For many computationally intensive studies, your data transfer actually isn’t that large. For e.g. you can often do the post-processing on-node and then only get aggregate statistics about simulation runs out.