Don't rent the cloud, own instead

This is an industry we're[0] in. Owning is at one end of the spectrum, with cloud at the other, and a broadly couple of options in-between:

1 - Cloud – This is minimising cap-ex, hiring, and risk, while largely maximising operational costs (its expensive) and cost variability (usage based).

2 - Managed Private Cloud - What we do. Still minimal-to-no cap-ex, hiring, risk, and medium-sized operational cost (around 50% cheaper than AWS et al). We rent or colocate bare metal, manage it for you, handle software deployments, deploy only open-source, etc. Only really makes sense above €$5k/month spend.

3 - Rented Bare Metal – Let someone else handle the hardware financing for you. Still minimal cap-ex, but with greater hiring/skilling and risk. Around 90% cheaper than AWS et al (plus time).

4 - Buy and colocate the hardware yourself – Certainly the cheapest option if you have the skills, scale, cap-ex, and if you plan to run the servers for at least 3-5 years.

A good provider for option 3 is someone like Hetzner. Their internal ROI on server hardware seems to be around the 3 year mark. After which I assume it is either still running with a client, or goes into their server auction system.

Options 3 & 4 generally become more appealing either at scale, or when infrastructure is part of the core business. Option 1 is great for startups who want to spend very little initially, but then grow very quickly. Option 2 is pretty good for SMEs with baseline load, regular-sized business growth, and maybe an overworked DevOps team!

[0] https://lithus.eu, adam@

I would suggest to use both on-premise hardware and cloud computing. Which is probably what comma is doing.

For critical infrastructure, I would rather pay a competent cloud provider than being responsible for reliability issues. Maintaining one server room in the headquarters is something, but two servers rooms in different locations, with resilient power and network is a bit too much effort IMHO.

For running many slurm jobs on good servers, cloud computing is very expensive and you sometimes save money in a matter of months. And who cares if the server room is a total loss after a while, worst case you write some more YAML and Terraform and deploy a temporary replacement in the cloud.

Another thing between is colocation, where you put hardware you own in a managed data center. It’s a bit old fashioned, but it may make sense in some cases.

I can also mention that research HPCs may be worth considering. In research, we have some of the world fastest computers at a fraction of the cost of cloud computing. It’s great as long as you don’t mind not being root and having to use slurm.

I don’t know in USA, but in Norway you can run your private company slurm AI workloads on research HPCs, though you will pay quite a bit more than universities and research institutions. But you can also have research projects together with universities or research institutions, and everyone will be happy if your business benefits a lot from the collaboration.

This also depends so much on your scaling needs. If you need 3 mid-sized ECS/EC2 instances, a load balancer, and a database with backups, renting those from AWS isn’t going to be significantly more expensive for a decent-sized company than hiring someone to manage a cluster for you and dealing with all the overhead of keeping it maintained and secure.

If you’re at the scale of hundreds of instances, that math changes significantly.

And a lot of it depends on what type of business you have and what percent of your budget hosting accounts for.

The reason companies don’t go with on premises even if cloud is way more expensive is because of the risk involved in on premises.

You can see it quite clearly here that there’s so many steps to take. Now a good company would concentrate risk on their differentiating factor or the specific part they have competitive advantage in.

It’s never about “is the expected cost in on premises less than cloud”, it’s about the risk adjusted costs.

Once you’ve spread risk not only on your main product but also on your infrastructure, it becomes hard.

I would be vary of a smallish company building their own Jira in house in a similar way.

At scale (like comma.ai), it's probably cheaper. But until then it's a long term cost optimization with really high upfront capital expenditure and risk. Which means it doesn't make much sense for the majority of startup companies until they become late stage and their hosting cost actually becomes a big cost burden.

There are in between solutions. Renting bare metal instead of renting virtual machines can be quite nice. I've done that via Hetzner some years ago. You pay just about the same but you get a lot more performance for the same money. This is great if you actually need that performance.

People obsess about hardware but there's also the software side to consider. For smaller companies, operations/devops people are usually more expensive than the resources they manage. The cost to optimize is that cost. The hosting cost usually is a rounding error on the staffing cost. And on top of that the amount of responsibilities increases as soon as you own the hardware. You need to service it, monitor it, replace it when it fails, make sure those fans don't get jammed by dust puppies, deal with outages when they happen, etc. All the stuff that you pay cloud providers to do for you now becomes your problem. And it has a non zero cost.

The right mindset for hosting cost is to think of it in FTEs (full time employee cost for a year). If it's below 1 (most startups until they are well into scale up territory), you are doing great. Most of the optimizations you are going to get are going to cost you in actual FTEs spent doing that work. 1 FTE pays for quite a bit of hosting. Think 10K per month in AWS cost. A good ops person/developer is more expensive than that. My company runs at about 1K per month (GCP and misc managed services). It would be the wrong thing to optimize for us. It's not worth spending any amount of time on for me. I literally have more valuable things to do.

This flips when you start getting into the multiple FTEs per month in cost for just the hosting. At that point you probably have additional cost measured in 5-10 FTE in staffing anyway to babysit all of that. So now you can talk about trading off some hosting FTEs for modest amount of extra staffing FTEs and make net gains.

Datacenters need cool dry air? <45%

No, low isn't good perse. I worked in a datacenter which in winters had less than 40%, ram was failing all over the place. Low humidity causes static electricity.

It would be interesting to hear their contingency plan for any kind of disaster (most commonly a fire) that hits their data center.

> Self-reliance is great, but there are other benefits to running your own compute. It inspires good engineering.

It's easy to inspire people when you have great engineers in the first place. That's a given at a place like comma.ai, but there are many companies out there where administering a datacenter is far beyond their core competencies.

I feel like skilled engineers have a hard time understanding the trade-offs from cloud companies. The same way that comma.ai employees likely don't have an in-house canteen, it can make sense to focus on what you are good at and outsource the rest.

Same thing. I was previously spending 5-8K on DigitalOcean, supposedly a "budget" cloud. Then the company was sold, and I started a new company on entirely self-hosted hardware. Cloudflare tunnel + CC + microk8s made it trivial! And I spend close to nothing other than internet that I already am spending on. I do have solar power too.

I love articles like this and companies with this kind of openness. Mad respect to them for this article and for sharing software solutions!

The #1 reason I would advocate for using AWS today is the compliance package they bring to the party. No other cloud provider has anything remotely like Artifact. I can pull Amazon's PCI-DSS compliance documentation using an API call. If you have a heavily regulated business (or work with customers who do), AWS is hard to beat.

If you don't have any kind of serious compliance requirement, using Amazon is probably not ideal. I would say that Azure AD is ok too if you have to do Microsoft stuff, but I'd never host an actual VM on that cloud.

Compliance and "Microsoft stuff" covers a lot of real world businesses. Going on prem should only be done if it's actually going to make your life easier. If you have to replicate all of Azure AD or Route53, it might be better to just use the cloud offerings.

I’m impressed that San Diego electrical power manages to be even more expensive than in the UK. That takes some doing.

Even at the personal blog level, I'd argue it's worth it to run your own server (even if it's just an old PC in a closet). Gets you on the path to running a home lab.

Working at a non-tech regional bigco, where ofc cloud is the default, I see everyday how AWS costs get out of hand, it's a constant struggle just to keep costs flat. In our case, the reality is that NONE of our services require scalability, and the main upside of high uptime is nice primarily for my blood pressure.. we only really need uptime during business hours, nobody cares what happens at night when everybody is sleeping.

On the other hand, there's significant vendor lockin, complexity, etc. And I'm not really sure we actually end up with less people over time, headcount always expands over time, and there's always cool new projects like monitoring, observability, AI, etc.

My feeling is, if we rented 20-30 chunky machines and ran Linux on them, with k8s, we'd be 80% there. For specific things I'd still use AWS, like infinite S3 storage, or RDS instances for super-important data.

If I were to do a startup, I would almost certainly not base it off AWS (or other cloud), I'd do what I write above: run chunky servers on OVH (initially just 1-2), and use specific AWS services like S3 and RDS.

A bit unrelated to the above, but I'd also try to keep away from expensive SaaS like Jira, Slack, etc. I'd use the best self-hosted open source version, and be done with it. I'd try Gitea for git hosting, Mattermost for team chat, etc.

And actually, given the geo-political situation as an EU citizen, maybe I wouldn't even put my data on AWS at all and self-host that as well...

> We use SSDs for reliability and speed.

Hey, how do SSDs fail lately? Do they ... vanish off the bus still? Or do they go into read only mode?

> Cloud companies generally make onboarding very easy, and offboarding very difficult. If you are not vigilant you will sleepwalk into a situation of high cloud costs and no way out. If you want to control your own destiny, you must run your own compute.

Cost and lock-in are obvious factors, but "sovereignty" has also become a key factor in the sales cycle, at least in Europe.

Handing health data, Juvoly is happy to run AI work loads on premise.

The company I work for used to have a hybrid where 95% was on-prem, but became closer to 90% in the cloud when it became more expensive to do on-prem because of VMware licensing. There are alternatives to VMware, but not officially supported with our hardware configuration, so the switch requires changing all the hardware, which still drives it higher than the cloud. Almost everything we have is cloud agnostic, and for anything that requires resilience, it sits in two different providers.

Now the company is looking at doing further cost savings as the buildings rented for running on-prem are sitting mostly unused, but also the prices of buildings have gone up in recent years, notably too, so we're likely to be saving money moving into the cloud. This is likely to make the cloud transition permanent.

I cancelled my digital ocean server of almost a decade late last year and replaced it with a raspberry pi 3 that was doing nothing. We can do it, we should do it.

This quote is gold:

The cloud requires expertise in company-specific APIs and billing systems. A data center requires knowledge of Watts, bits, and FLOPs. I know which one I rather think about.

I used to colocate a 2U server that I purchased with a local data center. It was a great learning experience for me. Im curious why a company wouldn't colocate their own hardware? Proximity isnt an issue when you can have the datacenter perform physical tasks. Bravo to the comma team regardless. It'll be a great learning experience and make each person on their team better.

Ps... bx cable instead of conduit for electrical looks cringe.

Interesting that they go for no redundancy

> Maintaining a data center is much more about solving real-world challenges. The cloud requires expertise in company-specific APIs and billing systems. A data center requires knowledge of Watts, bits, and FLOPs. I know which one I rather think about.

I find this to be applicable on a smaller scale too! I'd rather setup and debug a beefy Linux VPS via SSH than fiddle with various propietary cloud APIs/interfaces. Doesn't go as low-level as Watts, bits and FLOPs but I still consider knowledge about Linux more valuable than knowing which Azure knobs to turn.

> Cloud companies generally make onboarding very easy, and offboarding very difficult.

I reckon most on-prem deployments have significantly worse offboarding than the cloud providers. As a cloud provider you can win business by having something for offboarding, but internally you'd never get buy-in to spend on a backup plan if you decide to move to the cloud.

Microsoft made the TCO argument and won. Self-hosting is only an option if you can afford expensive SysOps/DevOps/WhateverWeAreCalledTheseDays to manage it.

15-years ago or so a spreadsheet was floating around where you could enter server costs, compute power, etc and it would tell you when you would break-even by buying instead of going with AWS. I think it was leaked from Amazon because it was always three-years to break-even even as hardware changed over time.

There's the HN I know and love

I'm thinking about doing a research project at my university looking into distributed "data centers" hosted by communities instead of centralized cloud providers.

The trick is in how to create mostly self-maintaining deployable/swappable data centers at low cost...

> San Diego power cost is over 40c/kWh, ~3x the global average. It’s a ripoff, and overpriced simply due to political dysfunction.

Mind anyone elaborate? Always thought this is was a direct cause of the free market. Not sure if by dysfunction the op means lack of intervention.

Realistically, it's the speed with which you can expand and contract. The cloud gives unbounded flexibility - not on the per-request scale or whatever, but on the per-project scale. To try things out with a bunch of EC2s or GCEs is cheap. You have it for a while and then you let it go. I say this as someone with terabytes of RAM in servers, and a cabinet I have in the Bay Area.

I just read about Railway doing something similar, sadly their prices are still high compared to other bare metal providers and even VPS such as Hetzner with Dokploy, very similar feature set yet for the same 5 dollars you get way more CPU, storage and RAM.

https://blog.railway.com/p/launch-week-02-welcome

This was one of the coolest job ads that I've ever read :). Congrats for what you have done with your infrastructure, team and product!

Look the bottom of that page:

An error occurred: API rate limit already exceeded for installation ID 73591946.

Error from https://giscus.app/

Fellow says one thing and uses another.

The observation about incentives is underappreciated here. When your compute is fixed, engineers optimize code. When compute is a budget line, engineers optimize slide decks. That's not really a cloud vs on-prem argument, it's a psychology-of-engineering argument.

Well, their comment section is fore sure not running on premises, but on the cloud:

"An error occurred: API rate limit already exceeded for installation ID 73591946."

This is a great solution for a very specific type of team but I think most companies with consistent GPU workloads will still just rent dedicated servers and call it a day.

In case anyone from comma.ai reads this: "CTO @ comma.ai" the link at the end is broken, it’s relative instead of absolute.

Looks insanely daunting imo

Not long ago Railway moved from GCP to their own infrastructure since it was very expensive for them. [0] Some go for a Oxide rack [1] for a full stack solution (both hardware and software) for intense GPU workloads, instead of building it themselves.

It's very expensive and only makes sense if you really need infrastructure sovereignty. It makes more sense if you're profitable in the tens of millions after raising hundreds of millions.

It also makes sense for governments (including those in the EU) which should think about this and have the compute in house and disconnected from the internet if they are serious about infrastructure sovereignty, rather than depending on US-based providers such as AWS.

[0] https://blog.railway.com/p/data-center-build-part-one

[1] https://oxide.computer/

I like Hotz’s style: simply and straightforwardly attempting the difficult and complex. I always get the impression: “You don’t need to be too fancy or clever. You don’t need permission or credentials. You just need to go out and do the thing. What are you waiting for?”

Chatgpt:

# don’t own the cloud, rent instead

the “build your own datacenter” story is fun (and comma’s setup is undeniably cool), but for most companies it’s a seductive trap: you’ll spend your rarest resource (engineer attention) on watts, humidity, failed disks, supply chains, and “why is this rack hot,” instead of on the product. comma can justify it because their workload is huge and steady, they’re willing to run non-redundant storage, and they’ve built custom GPU boxes and infra around a very specific ML pipeline. ([comma.ai blog][1])

## 1) capex is a tax on flexibility

a datacenter turns “compute” into a big up-front bet: hardware choices, networking choices, facility choices, and a depreciation schedule that does not care about your roadmap. cloud flips that: you pay for what you use, you can experiment cheaply, and you can stop spending the minute a strategy changes. the best feature of renting is that quitting is easy.

## 2) scaling isn’t a vibe, it’s a deadline

real businesses don’t scale smoothly. they spike. they get surprise customers. they do one insane training run. they run a migration. owning means you either overbuild “just in case” (idle metal), or you underbuild and miss the moment. renting means you can burst, use spot/preemptible for the ugly parts, and keep steady stuff on reserved/committed discounts.

## 3) reliability is more than “it’s up most days”

comma explicitly says they keep things simple and don’t need redundancy for ~99% uptime at their scale. ([comma.ai blog][1]) that’s a perfectly valid trade—if your business can tolerate it. many can’t. cloud providers sell multi-zone, multi-region, managed backups, managed databases, and boring compliance checklists because “five nines” isn’t achieved by a couple heroic engineers and a PID loop.

## 4) the hidden cost isn’t power, it’s people

comma spent ~$540k on power in 2025 and runs up to ~450kW, plus all the cooling and facility work. ([comma.ai blog][1]) but the larger, sneakier bill is: on-call load, hiring niche operators, hardware failures, spare parts, procurement, security, audits, vendor management, and the opportunity cost of your best engineers becoming part-time building managers. cloud is expensive, yes—because it bundles labor, expertise, and economies of scale you don’t have.

## 5) “vendor lock-in” is real, but self-lock-in is worse

cloud lock-in is usually optional: you choose proprietary managed services because they’re convenient. if you’re disciplined, you can keep escape hatches: containers, kubernetes, terraform, postgres, object storage abstractions, multi-region backups, and a tested migration plan. owning your datacenter is also lock-in—except the vendor is past you, and the contract is “we can never stop maintaining this.”

## the practical rule

*if you have massive, predictable, always-on utilization, and you want to become good at running infrastructure as a core competency, owning can win.* that’s basically comma’s case. ([comma.ai blog][1]) *otherwise, rent.* buy speed, buy optionality, and keep your team focused on the thing only your company can do.

if you want, tell me your rough workload shape (steady vs spiky, cpu vs gpu, latency needs, compliance), and i’ll give you a blunt “rent / colo / own” recommendation in 5 lines.

[1]: https://blog.comma.ai/datacenter/ "Owning a $5M data center - comma.ai blog"

Am I the only one that is simply scared of running your own cloud? What happens if your administrator credentials get leaked? At least with Azure I can phone microsoft and initiate a recovery. Because of backups and soft deletion policies quite a lot is possible. I guess you can build in these failsafe scenarios locally too? But what if a fire happens like in South Korea? Sure most companies run more immediate risks such as going bankrupt, but at least Cloud relieves me from the stuff of nightmares.

Except now I have nightmares that the USA will enforce the patriot act and force Microsoft to hand over all their data in European data centers and then we have to migrate everything to a local cloud provider. Argh...

Stopped reading at "Our main storage arrays have no redundancy". This isn't a data center, it's a volatile AI memory bank.

One thing I don't really understand here is why they're incurring the costs of having this physically in San Diego, rather than further afield with a full-time server tech essentially living on-prem, especially if their power numbers are correct. Is everyone being able to physically show up on site immediately that much better than a 24/7 pair of remote hands + occasional trips for more team members if needed?

Having worked only with the cloud I really wonder if these companies don't use other software with subscriptions. Even though AWS is "expensive" its a just another line item compared to most companies overall SaaS spend. Most businesses don't need that much compute or data transfer in the grand scheme of things.

Or better; write your software such that you can scale to tens of thousands of concurrent users on a single machine. This can really put the savings into perspective.

capex vs opex the Opera.

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