[philliphaydon]

Nope. We have no information of the OPs setup, bill, or anything. This entire thread is based on assumptions. I common examples of developers screwing up and generating large bills. Explain to me how machine learning is any different.

Do we know if the instances used for MLing are running 24/7 idle until customers use them? Do we know if the utilisation is optimal for the workloads?

We know nothing. So claiming that cloud providers are not good is very far from the problem and not helpful.

[rumanator]

> So claiming that cloud providers are not good

The statement is not that AWS is "not good". The statement is that AWS is very expensive, specially for computational tasks, and there are cheaper alternatives around.

AWS is notorious for positioning their services as a way to convert capex into opex, specially if your scenario involves a SaaS that might experience unexpected growth and must be globally available. Training ML models has zero to do with those usecases. It makes no sense to mindlessly defend AWS as being the absolute best service around for a job it was not designed for and with a pricing model that capitalizes on added value on things that are not applicable.

[philliphaydon]

I never defended AWS as being the absolute best. I said high bills are almost always due to developers and not the cloud provider. Which you haven’t argued against.

As I said I have examples of how Developers often cause large bills.

And I explained why we can’t help with the OPs large bill.

You’re saying that with ML there is absolutely 0 way to reduce costs on AWS which is absolute rubbish.

[rumanator]

> I said high bills are almost always due to developers and not the cloud provider.

I feel that's where you keep missing the whole point. Somehow you're stuck on thinking that an expensive service is not a problem if you can waste time micromanaging and constantly monitoring expenditures to shave off a bit of cost from the invoice. Yet, somehow you don't register in your universe the fact that there are services out there that are both far cheaper and arguably better for this use case.

Therefore, why do you keep insisting on the idea of wasting time and effort micromanaging a deployment like pets to shave off some trimmings off a huge invoice if all you need to do to cut cost to a fraction of AWS's price tag is to.... switch vendor?

[philliphaydon]

So what you’re saying is because developers can’t control what they build they need to be stuck with services that limit what they can do so they don’t end up with big bills.

And that for cases like MLing it’s impossible to optimise costs.

Got ya.

[rumanator]

> So what you’re saying is because developers can’t control what they build they need to be stuck with services that limit what they can do so they don’t end up with big bills.

No, I'm pointing you the fact that developers are able to do exactly what they want with less work and far cheaper by simply moving away from AWS and picking pretty much any vendor. Why do you have a hard time understanding what others are telling you and understand anything that points that AWS is not the best solution for all usecases, specially those they were not designed for?

[philliphaydon]

Rubbish, you're saying that it's impossible to run on cloud cheaply. Therefore no one should use cloud for any reason.

"I don't know how to use cloud so cloud is bad"