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Having worked on large compute intensive projects in both academia and industry I am somewhat sceptical about multi-cloud tools. Normally you do your compute where the data is since egress is so expensive. And it just doesn't seem worth developing against a cloud agnostic API and limiting myself to the lowest common denominator.

If you have a large workload though they may be helpful as a negotiating tactic to play one cloud off against another.

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One big reason people use multiple regions or clouds: higher resource availability.

Allocating scarce resources can be very hard on the cloud. These are things like high-end GPUs (both on-demand and spot; the latter being much harder to get) and also beefy CPU-based instances. We've seen 10s of hours of waiting times or longer.

The natural solution is to have the flexibility to allocate resources in multiple regions (and ultimately, clouds) to increase the total pool size.

I have seen very large jobs that needed to be split up across multiple regions but doing so required replicating large amounts of data. That comes at a cost too so it requires planning to work out which regions you want to use.

Once that is done it is fairly easy to set up spot clusters in each region to process the jobs in the queue.

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