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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

#71
post #61
post #58

SkyPilot devs here, happy to answer any questions. GitHub repo (Apache 2 license): https://github.com/skypilot-org/skypilot Getting started is easy: $ pip install "skypilot[aws,gcp,azure]" # Pick your clouds $ sky check $ sky launch

Looks great! Do you anticipate any pushback from cloud providers, who might one day decide to restrict access to stop people getting a better price elsewhere?

We don't anticipate this will happen for a few reasons. When the usage of SkyPilot (or a SkyPilot-like "intercloud broker" system) is small, it probably doesn't warrant the dominant clouds' attention.

When the usage gets bigger, I'm not sure how providers can restrict access anyway (curious if there are precedents). There are quite a few large multicloud platforms like Snowflake or Databricks heavily utilizing AWS/GCP/Azure already. (Granted, these platforms are not meta-cloud, in the sense of moving their customer workloads transparently across clouds.)

Ultimately we see such a system to grow the pie for the whole cloud market. The incumbents' relative shares may drop, but their absolute volume will grow.

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

#72
post #58

SkyPilot devs here, happy to answer any questions. GitHub repo (Apache 2 license): https://github.com/skypilot-org/skypilot Getting started is easy: $ pip install "skypilot[aws,gcp,azure]" # Pick your clouds $ sky check $ sky launch

I’m curious how this affects network and data storage costs. Maintaining data storage and private fiber to all the clouds has its own costs.

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

#73
post #45
post #31

Earlier quoted context omitted.

why....that sounds like Web3! (I kid I kid...)

Actually it's a good use of Web3, handling of the billing and revenue sharing portion of the problem.

Yeah, in theory it's a great idea. In practice, it always ends up as a challenge for economies of scale. Just look at Bitcoin, we can all mine it, but it's not worth it unless you scale. In the end, someone will build a data center, just to gather profits from whatever Web3 implementation you think of. Because their energy cost is lower, relatively, it will become too expensive to 'mine' at home.

It's the circle of capitalism.

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

#74
I remember when the "cloud" hype was first beginning to make a splash. A pillar selling point was "savings".

"Reduce your costs", they said. "Don't worry about those expensive hardware costs", or management. "Only pay for what you need", they said.

Until everyone was hooked and the tooling was everywhere.

Even just putting the pricing for hardware/services aside, the bandwidth charges alone are quite amazing. Most have it at $80 per TB per month. That's $80 a month for a 3mbit connection. [3mbps * 3600 seconds an hour * 24 hours * 30 days ~= 1TB]. Even if you pretended it was 6mbps for double the redundancy, that's still $80 for a 6mbit connection. I understand there's more to it than just transfer amount/speed, but this is in a place where bandwidth is supposed to be cheaper, as it's "purchased" in wholesale, yet a 1GBit upload connection could transfer 330TB in a month, which would cost over $23,000 at Microsoft/Google/Amazon.

I am not saying the cloud doesn't make sense. I love me some Firebase. CDN's are game changers. And GPU's per hour is the only way some scientists/researchers can afford to do work [although it does contribute to the NVIDIA's focusing on manufacturing high price/low volume].

That said, it's not for everyone. A cheap VPS can do a lot.

Specifically for a university or an institution with a lot of cheap/free bandwidth, on-site would not only be cheaper, but also have lower latency for its campus users and more control wise.

Also, if done right, there's a possibility of teaching the students relevant real-world solutions using the knowledge gained/within the university.

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

#75

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…

I too have been surprised by the poor state of research compute at American universities. Of course it's hard: that's why it needs some smart and expensive people who do research on computing to run it (but that's what universities are all about). But maybe it's a cultural thing: in the US organizations including universities like to rely on commercial services when they can instead of seeing the value of doing it in-house.

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

#76

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…

Berkeley has at least one cluster, probably more.

https://docs-research-it.berkeley.edu/services/high-performa...

University HPC clusters are typically managed and owned departmentally. My former employer had two clusters in two different departments. I worked directly with a few other universities who also had departmental HPC clusters, and I’ve read a boatload of HPC docs from different unis and labs. Sharing clusters for many types of workloads seems to happen more at the regional level (like Archer cluster in Edinburgh, or PNNL in WA).

Ours is a fairly small cluster of maybe 60 or 80 job nodes. All compute networking travels over Infiniband—-I think we bought HDR for the new cluster, but price may held us to EDR—-which is probably why the cluster was so expensive to build (around $2M). Our storage cluster was another $1-$2M project.

All that is to preface this: cloud usage doesn’t mean they’re only using cloud resources. Our goal, for instance, was to build a hybrid cluster (and their continued goal, as far as I know). The first step was to offload low priority work with low resource requirements and wall times, and comparatively long timelines to the cheapest possible, compliant cloud provider (some of our researchers have specific data sharing and privacy requirements).

Let’s say a job is submitted on Monday morning at 9 am. It needs 2 CPUs and 4 GB of RAM, and a wall time of five minutes. The researcher can wait until next Monday at 10 am for the results. There’s at least a chance that running this job in the on-prem cluster is less cost efficient than offloading the job to another resource, whether the cost is direct (i.e. 5 minutes on-prem costs $0.10, and the cloud costs $0.05 or whatever real values would look like).

Ideally, we would have some method by which you could compare the cost to run a job in the cluster vs another resource, and it would automatically offload jobs of up to $X to the cloud, whether as a very low priority queue, or as overflow in times of full utilization. There are several other conditions that would need to be met, as well, but you get the idea (just for example, one consideration is if the work be interrupted. If the job has to run start to finish, the cloud is likely not suitable for that work).

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

#77

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…

It really depends on the workload. GPU clusters are usually cheaper to run in house since Nvidia let you use regular GPUs for research which end up cheaper than cloud GPUs. And often Universities will charge less overhead for capital expenses on a grant which can artificially reduce the cost of running it yourself. The big downside of institutional HPC is it can be difficult to get stuff running on the ancient distri…

> I also kind of object to the term HPC... with the exception of a small number of shared memory clusters used for physics simulations they're usually just a bunch of standard servers often with incredibly slow network storage. Nothing high performance about them.

I’m sure there are plenty of places who have production clusters equivalent to our “test cluster” that we ran in VMWare (which we only used to check version compatibility during upgrades), but in my experience working on an HPC team at a research university is that most universities are using real HPC clusters. They’re not all equally built and managed, but they have 50+ compute nodes using Infiniband (or equivalent) for interconnectivity between nodes, and to connect to the back end SAN, which runs a distributed, parallel file system (usually GPFS, sometimes Lustre, or BeeGFS).

Apptainer (formerly Singularity) is aimed at containerizing HPC workloads. You can build it with Docker commands, and then convert to Apptainer’s format, so it’s pretty easy to use. You don’t run Docker directly, in any case.

Correct that compatibility is a huge issue. It got ugly at the end of our EL6 cluster’s life. It didn’t run containers well, and our cluster was so entrenched in the old way of managing software (modules and Conda envs) that converting would have been a massive effort, and it may not have worked at all! There was a lot that had to get rescheduled or find a different place to run while we dealt with supply chain slowness.

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

#78
post #74

I remember when the "cloud" hype was first beginning to make a splash. A pillar selling point was "savings". "Reduce your costs", they said. "Don't worry about those expensive hardware costs", or management. "Only pay for what you need", they said. Until everyone was hooked and the tooling was everywhere. Even just putting the pricing for hardware/services aside, the bandwidth charges alone are quite amazing. Most ha…

Most people don’t bother refactoring their application and leave whatever IIS garbage they have running on windows 20xx in a cloud instance (to say nothing about the windows licensing cost).

Also universities don’t have the same cost models as companies. Their labs have less money - except those institutions with large endowments - but they all have access to near limitless “slave” labor in the form of grad students and post docs.

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

#79
post #68

Aren't AWS, Azure and GCP all comparatively expensive? They are good for certain workloads and it's good that this project exists, but if you wanted cheap cloud resources, you'd probably need to look at one of the smaller cloud vendors: Hetzner, Scaleway, DigitalOcean, Vultr, Contabo and others. Of course, if you need GPUs, things can get limiting.

For infrequent, unpredictable workloads using something like spot instances on AWS and scaling as needed (including to zero) will likely be cheaper. I think Hetzner and other budget cloud providers are excellent choices for use cases that require always on, reasonably predictable workloads like webservers.

The thing is they are so much cheaper, especially for egress, that it takes really extreme spikes or batch jobs for it to be cheaper to use AWS vs. leaving an excess number of server running permanently on somewhere like Hetzner. Very few sites have variable enough traffic that scaling up and down with usage saves enough to even get close.

There certainly are genuine cases where AWS will come out ahead, but they're rare. E.g. if you suddenly need several hundred instances for on average a few days a month, it's probably worth it. Very few people do that, and paying for the capacity to be able to offer that is part of the reason for why AWS is so expensive. Peoples belief that AWS is cheap is another reason.

Ironically, the ability to run a hybrid setup that scales up in AWS when you genuinely need rapid extra capacity changes the maths even further in favour of dedicated servers from places like Hetzner (as does the fact most places like Hetzner now have their own cloud offerings) because it means you can go closer to the wire on your dedicated servers.

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

#80
post #74

I remember when the "cloud" hype was first beginning to make a splash. A pillar selling point was "savings". "Reduce your costs", they said. "Don't worry about those expensive hardware costs", or management. "Only pay for what you need", they said. Until everyone was hooked and the tooling was everywhere. Even just putting the pricing for hardware/services aside, the bandwidth charges alone are quite amazing. Most ha…

"Simplify to succeed and Complicate to profit"

-- (likely) Tim Ferris.

I sat out of the cloud hoopla and it cost me opportunities - Now, I am dragging my feet into it to be employable.. but the Anti-Cloud (River?) is going to be a concept. 39 signals already did a blog post and change in strategy.

I look forward to the economically lean years of 2023 and 2024 and HN front page articles about how moving away from Cloud and owning your own server is saving 'millions'.

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