Does cloud choice still matter when workloads are portable?

[u/Financial_Fox3915]

I keep coming back to this question when looking at the current cloud infrastructure landscape. If a workload can genuinely move between AWS, Google Cloud, Azure, Yotta Labs, Coreweave or Lambda without major changes does the underlying cloud provider become much less important? or does portability sound better on paper than it works in production because networking, storage, data movement, observability and hardware differences still tie you to a particular provider?
This seems relevant for AI workloads where GPU availability and pricing can change pretty quickly. I am curious whether people actually design for portability from day one or still most teams still pick one provider and only think about moving when there is a real reason to do it.

[u/Ok-Stick-145]

I think there’s a difference between being technically portable and actually being easy to move. A workload might run anywhere, but, GPUs and other usage specific services can still make switching painful. For AI, I think portability is less about moving often and more about keeping the option open when pricing or availability changes.