> You're completely ignoring the other valuable aspects of being in a cloud: you're close to huge amounts of high throughput storage (blob and DB), and can incr

> You're completely ignoring the other valuable aspects of being in a cloud: you're close to huge amounts of high throughput storage (blob and DB), and can increase/decrease the size of your fleet trivially. These are critical to nearly all modern scientific workflows (moreso than the raw compute, IMHO). That has not been my experience. There are lots of scientific workflows that only need 10s of TB at most, yet can still consume lots of cycles. > As for the cost structure for research computing, the argument that the costs are externalized isn't a good one- that overhead that pays for the facility, and the networking, comes out of your grant money, and using grad student time to admin your cluster often just causes your grad students to leave for FAAMG. At the universities I've worked at, equipment (large purchases) is except from overhead, or results in a lower overhead charge. (Researchers balk at paying a ~50% overhead rate on a $1million instrument). Using grad student time to admin your cluster is dumb, but I'm more talking about users who need single-digit numbers of computers. If you need real HPC, you're in the world of queues, national and regional supercomputers, etc. etc.