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Cloud Run GPUs, now GA, makes running AI workloads easier for everyone

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Re: Cloud Run GPUs, now GA, makes running AI workloads easier for everyone

#121
post #57

Earlier quoted context omitted.

Your local computer is not powerful enough, and that's why you must welcome those brand new mainframes... I mean, "cloud services."

It is funny how using a Web IDE, and a cloud shell, is such a déjà vu from when I used to do development on a common UNIX server shared by the whole team.

Telnet from a Wyse terminal.

Re: Cloud Run GPUs, now GA, makes running AI workloads easier for everyone

#122
post #20

The pricing doesn't look that compelling, here are the hourly rate comparisons vs runpod.io vs vast.ai: 1x L4 24GB: google: $0.71; runpod.io: $0.43, spot: $0.22 4x L4 24GB: google: $4.00; runpod.io: $1.72, spot: $0.88 1x A100 80GB: google: $5.07; runpod.io: $1.64, spot: $0.82; vast.ai $0.880, spot: $0.501 1x H100 80GB: google: $11.06; runpod.io: $2.79, spot: $1.65; vast.ai $1.535, spot: $0.473 8x H200 141GB: google:…

Where did you get the pricing for vast.ai here? Looking at their pricing page, I don't see any 8xH200 options for less than $21.65 an hour (and most are more than that).

I think it’s a typo, looks pretty close to their 8xH100 prices.

Re: Cloud Run GPUs, now GA, makes running AI workloads easier for everyone

#123

Earlier quoted context omitted.

Does Cloud Run still use a fake Linux kernel emulated by Go, rather than a real VM? Does Cloud Run give you root?

You're thinking of gvisor. But no, the "gen2" runtime is a microvm ala firecracker and performs a lot better as a result.

Ah, that's great.

And it looks like Cloud Run can do something Lambda can't: https://cloud.google.com/run/docs/create-jobs . "Unlike a Cloud Run service, which listens for and serves requests, a Cloud Run job only runs its tasks and exits when finished. A job does not listen for or serve requests."

Re: Cloud Run GPUs, now GA, makes running AI workloads easier for everyone

#124
post #121
post #57

Earlier quoted context omitted.

It is funny how using a Web IDE, and a cloud shell, is such a déjà vu from when I used to do development on a common UNIX server shared by the whole team.

Telnet from a Wyse terminal.

My first experience with such a setup was connecting to DG/UX, via the terminal application on Windows for Workgroups, or some thin client terminals in a mix of green or ambar phosphor, spread around the campus.

The only time I used a Pascal compiler in ISO Pascal mode, it had the usual extensions inspired on UCSD, but we weren't allowed to use them on the assignments.

Re: Cloud Run GPUs, now GA, makes running AI workloads easier for everyone

#125

Earlier quoted context omitted.

Cloud Run is a great service. I find it much easier to work with than AWS's equivalent (ECS/Fargate.)

AWS AppRunner is the closest equivalent to Cloud Run. Its really not close though, AppRunner is an unloved service at AWS and is missing a lot of the features that make Cloud Run nice.

AppRunner was Amazon's answer to AppEngine a full decade+ later. Cloud Run is miles ahead.

Re: Cloud Run GPUs, now GA, makes running AI workloads easier for everyone

#126

All the cruft of a big cloud provider, AND the joy of uncapped yolo billing that has the potential to drain your creditcard overnight. No thanks, I'll personally stick with Modal and vast.ai

I never used modal or vast.ai and from their pages it was not obvious how they solve the yolo billing issue? Are they pre-paid or do they support caps?

Engineer from Modal here: we support caps. They kick in within ~2s if your usage exceeds the configured limit.

Re: Cloud Run GPUs, now GA, makes running AI workloads easier for everyone

#127
post #66

Earlier quoted context omitted.

Cloud Run is great but no billing limits is too scary. No idea why they don't address this. They must know if they support individuals we'll eventually leave our saases there.

Setting max instances effectively caps your spend right?

Yes. CR has had this feature since day 1, people just don't bother to read the docs and would rather write long blog posts blaming their cloud provider for manufacturing the gun they shot themself in the foot with.

Re: Cloud Run GPUs, now GA, makes running AI workloads easier for everyone

#129
post #54

I love Google Cloud Run and highly recommend it as the best option[1]. The Cloud Run GPU, however is not something I can recommend. It is not cost effective (instance based billing is expensive as opposed to request based billing), GPU choices are limited, and the general loading/unloading of model (gigabytes) from GPU memory makes it slow to be used as server less. Once you compare the numbers it is better to use a…

The problem is you can't reliably get VMs on GCP.

All the major clouds are suffering from this. AWS you can't ever get an 80gb gpu without a long term reserve and even then it's wildly expensive. GCP you can sometimes but its also insanely expensive.

These companies claim to be "startup friendly", they are anything but. All the neo-clouds somehow manage to do this well (runpod, nebius, lambda) but the big clouds are just milking enterprise customers who won't leave and in the process screwing over the startups.

This is a massive mistake they are making, which will hurt their long term growth significantly.

Re: Cloud Run GPUs, now GA, makes running AI workloads easier for everyone

#130

Earlier quoted context omitted.

Does Cloud Run still use a fake Linux kernel emulated by Go, rather than a real VM? Does Cloud Run give you root?

You're thinking of gvisor. But no, the "gen2" runtime is a microvm ala firecracker and performs a lot better as a result.

https://github.com/cloud-hypervisor/cloud-hypervisor or something else?
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