r/cloudcomputing • u/Fear73 • 13d ago

Do AI workloads really belong in the same cloud as everything else?

Something I've been thinking about a lot lately like regular web apps putting everything under one cloud account makes things pretty simple but AI workloads have very different needs like GPUs, high-speed storage, special networking setups, specific regions and different types of hardware.

I've seen people use services like AWS, Azure, GCP, CoreWeave, Lambda, Yotta Labs and others in all sorts of ways so just wanna know how people view this problem here

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2

u/Anxious-Average-748 13d ago

We run a mixed setup at work and it's a pain honestly. AI stuff needs GPU instances that regular cloud regions don't always have, so you end up with workloads spread across different zones anyway. The billing gets messy fast when you mix compute types in same account.

2

u/Efficient_Loss_9928 13d ago

Depends on what you are doing, if you are processing terabytes of data, moving from one cloud to another and keeping things in sync can cost you millions. And get a worse experience.

I have worked directly with customers to ingest and sync data to our cloud because they are with another hyperscaler. The invoice is not pretty.

1

u/jboogyoogy 13d ago

Separating ai workflows can make a lot of sense esp when GPU costs and infra requirements become significant

With smaller projects keeping everything in one cloud might be simpler. Using specialized providers for ai while keeping the rest of the stack elsewhere could be much more cost effective and flexible

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u/Admirable_Window8128 12d ago

I think it makes sense to separate them when the workload actually needs specialized hardware. Keeping everything in one cloud is simpler, but AI workloads can have very different cost and performance needs, so using multiple providers can be worth the extra complexity.

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u/stevefan1999 11d ago

I remember in uni because the term "cloud" means anything that can be software defined, so it is literally anything

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u/Suspicious_Pizza9529 11d ago

I think it makes sense to separate them when the workloads have very different requirements. AI workloads can need specialized hardware and networking that regular apps don't, so using multiple providers can sometimes be more practical than forcing everything into one cloud.

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u/Phytocosm 13d ago

Yes, the same cloud as the entire industry. The cloud of forgotten human history. The clouds of heaven.