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UC Berkeley launches SkyPilot to help navigate soaring cloud costs

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Re: UC Berkeley launches SkyPilot to help navigate soaring cloud costs

#12
post #6
post #3

From reading this launch post, I'm not convinced this is going to save too much money. The project automatically selects the cheapest cloud to run a job, and does it there - which sounds sensible. In reality though, these jobs presumably need large volumes of input data. If your input data is in cloud A, and you run a job in cloud B, typically any cost saving from running in cloud B will be more than offset by the eg…

They have a project which addresses this concern as well: https://skyplane.org/en/latest/benchmark.html

I'm one of the creators of Skyplane. Skyplane can migrate large datasets between cloud regions at 10s of Gbps while compressing data to reduce egress fees. Happy to chime in!

https://github.com/skyplane-project/skyplane

Re: UC Berkeley launches SkyPilot to help navigate soaring cloud costs

#13
post #3

From reading this launch post, I'm not convinced this is going to save too much money. The project automatically selects the cheapest cloud to run a job, and does it there - which sounds sensible. In reality though, these jobs presumably need large volumes of input data. If your input data is in cloud A, and you run a job in cloud B, typically any cost saving from running in cloud B will be more than offset by the eg…

And isn’t the biggest issue with running potentially large jobs in the cloud the cut off when it’s cheaper to use your own hardware. After a few months or dozens of runs of your large model in the cloud you may have reached the point where purchasing would have been cheaper.

Something that could look at your code, data and budget and say upto X runs use cloud A, for more than Y runs it would be cheaper to buy/lease these GPUs etc. would be interesting.

Re: UC Berkeley launches SkyPilot to help navigate soaring cloud costs

#14
post #7

I feel that the old SETI@home project can use a comeback. Most home machines have powerful GPU these days. The ML problems are embarrassingly parallel and can be distributed to the home machines. Just need to work out the economy for everyone involved.

Single ML job can’t be distributed very well. More often than not they hit network limit, even on single zone 1 GB/s network speed that we normally get. Most of the distributed workloads use something like NVLink.

Re: UC Berkeley launches SkyPilot to help navigate soaring cloud costs

#15
post #4

At some point people will rediscover that "buying" whole sets of equipment through a lease financing company on a lease-to-own plan with $1 end payment, and colocating it the traditional way can often be significantly cheaper than paying endless "cloud" costs. naysayers will say, but the cloud allows you abstract away your salary costs of engineers! look at all the people you aren't hiring! I say: If your needs are s…

I've configured Cisco routers, F5s, LOMs, PDCs, NAS boxes, built servers from parts. And I'd never do it again.

That shit has literally no value, and it's quite difficult to configure, manage, and maintain. And no matter how good your process, you (or your team member) inevitably will forget to go into the BIOS and turn off power saving...or forget to turn off (or on) proxy arp. Or you'll reboot a box and it won't come back.

All costs can be negotiated with up-front commitments. We are small, but we pay .01/GB for egress bandwidth. And we got that price from akamai, fastly, and AWS by asking. I don't remember how much real colo places charge anymore, but it was a whole lot more than that.

Enterprise SSDs, redundant hardware, etc cost money. Does your startup qualify for a lease?

And really, why spend money on something that has no value to your business? Does having 5 data centers add any real value or competitive advantage? Does having that F5 expert on staff make your end-users happier?

If you answer yes, then go for it. But really, it's a total waste of time and money. You might as well make your own pencils and paper for the amount of value it delivers.

Re: UC Berkeley launches SkyPilot to help navigate soaring cloud costs

#16
post #3

From reading this launch post, I'm not convinced this is going to save too much money. The project automatically selects the cheapest cloud to run a job, and does it there - which sounds sensible. In reality though, these jobs presumably need large volumes of input data. If your input data is in cloud A, and you run a job in cloud B, typically any cost saving from running in cloud B will be more than offset by the eg…

I think it’s common to train 100s of models on the same data for experiments. Then you would only need to copy data once to all the cloud storage and run experiments as you wish.

Also most cloud provider don’t charge for ingress so you could move the data from something like R2 to cloud as many times you want..

Re: UC Berkeley launches SkyPilot to help navigate soaring cloud costs

#17
post #15
post #4

At some point people will rediscover that "buying" whole sets of equipment through a lease financing company on a lease-to-own plan with $1 end payment, and colocating it the traditional way can often be significantly cheaper than paying endless "cloud" costs. naysayers will say, but the cloud allows you abstract away your salary costs of engineers! look at all the people you aren't hiring! I say: If your needs are s…

I've configured Cisco routers, F5s, LOMs, PDCs, NAS boxes, built servers from parts. And I'd never do it again. That shit has literally no value, and it's quite difficult to configure, manage, and maintain. And no matter how good your process, you (or your team member) inevitably will forget to go into the BIOS and turn off power saving...or forget to turn off (or on) proxy arp. Or you'll reboot a box and it won't co…

Same here.

At massive scale, sure, it might make sense to run your own infrastructure and data centres. Some may even run their own private cloud and get the benefits we see from the public cloud today from their own IT depts.

The vast majority of us however had nothing in common with the above. Like you we ran the hardware, and to the business, we were never more than a cost centre and anything pitched to the broader business to "improve" outcomes for the development teams were seen as a cost without benefit.

I find a lot of people who are proponents for getting rid of the cloud never had to manage their own infrastructure, and have very rose tinted glasses for a reality that never existed for most.

Re: UC Berkeley launches SkyPilot to help navigate soaring cloud costs

#18
post #4

At some point people will rediscover that "buying" whole sets of equipment through a lease financing company on a lease-to-own plan with $1 end payment, and colocating it the traditional way can often be significantly cheaper than paying endless "cloud" costs. naysayers will say, but the cloud allows you abstract away your salary costs of engineers! look at all the people you aren't hiring! I say: If your needs are s…

This may be an overkill.

But I would argue most projects don't even need a cloud. Just go to Server Hunter, find a server up to your specs, and save 90-95% of your cloud costs.

These days you can scale vertically or horizontally for a long time without moving to a cloud.

Re: UC Berkeley launches SkyPilot to help navigate soaring cloud costs

#19
post #4

At some point people will rediscover that "buying" whole sets of equipment through a lease financing company on a lease-to-own plan with $1 end payment, and colocating it the traditional way can often be significantly cheaper than paying endless "cloud" costs. naysayers will say, but the cloud allows you abstract away your salary costs of engineers! look at all the people you aren't hiring! I say: If your needs are s…

Agree. I had to calculate the cost of running and upgrading an existing HPC infrastructure that was approaching it's end of life vs cloud. In house HPC beat cloud cost in almost all scenarios.

Re: UC Berkeley launches SkyPilot to help navigate soaring cloud costs

#20
I wonder why UC Berkeley doesn't build a proper HPC, they have a Data School and should provide this service for free to their faculties. We have "free" HPC resources at TU Dresden (Germany) (meaning: faculties do not need to pay for using HPC resources and they are not calculated in project budgets). I once applied for a job at University of Virginia, and they didn't have a HPC - everything was bought from AWS. When students accidently left stuff running, the professor had to beg Amazon to reimburse the fees. This was the main reason I was hesitant taking the offer. I even calculated building my own "Cloud" with a Proxmox cluster at home, so that I could teach students the basic stuff.
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