Grats on the sale either way.
They’ve got growing revenue but falling profits and they’ve got more debt than assets. They may want to raise their droplet prices, or issue more stock and then refocus on making their business profitable.
[0] valustox.com/DOCN
DigitalOcean is organizationally incapable of making anything in-house anymore.
I want to blame leadership - and to be clear, leadership sucks - but the problems are pervasive through every layer of the organization.
The only significant launches in the last 4-5 years have all been acquisitions or built by partner companies and whitelabeled.
Every system and every team has massively circular dependencies on one another , so it's just a massive circle of "we can't move until they move".
The tech debt is insane. Everything is slowed down by terribly-run and massively underfunded internal "platforms" teams for kubernetes, CI/CD, various internal databases, etc.
If you want to build something useful you basically have to ignore upper management and do it in secret until it's done and so integral to the systems that they have no choice but to allow you to support it.
Asking leadership outright to invest in minor maintenance for systems the entire company depends on is never approved.
The bar for engineering practices, code quality, and system design quality is comically low.
All the systems are massively distributed, but there is no understanding of distributed systems issues.
I was told multiple times that "CAP theorem doesn't apply here" and gaslit that an asynchronously replicated MySQL instance that sometimes spiked to multi-minute replication lag to the read replicas should just be used as if it were completely consistent between master and read replicas.
Tons of stuff was just run as singletons with hand-rolled in-memory rate limiting to avoid having to understand distributed locking or semaphores. These systems inevitably start falling over a few months after creation, but you're not allowed to evolve it into a correct system, you just have to support that garbage forever.
Brain drain everywhere due to low salaries. Even engineers barely capable of committing working code were getting fat raises to leave.
Their DL virtual servers, Core I think you call them is horrible. Very slow internet, takes forever to copy datasets into them. Most of the time, it's an uphill battle to get ssh access to them, they create some pointless virtual console instead and then a GUI to copy datasets, run trainings etc which is confusing and a hassle over simple ssh access. Programmers just want a simple ssh access to a server with a GPU, we are not looking for a WYSWYG like editor! I really don't know who the customer for this is? Marketing execs who want to do deep learning? I tried powering through the documentation, but it was outdated, and was plain wrong at points. It took me a couple of hours just to figure out how to copy a large dataset into my server and find the path to that dataset. Once I discovered, Lambda and Vast ai, I never looked back and forgot Paperspace for good.
Really as a cloud provider, all you need to do is create send a ssh tunnel to a system with a certain amount of compute and memory. Maybe like AWS you can create storage buckets but it's not absolutely neccesary. Don't add GUI, interfaces etc, your customers are engineers and they prefer simple systems that give them control.
One feature I would like in Lambda/ Vast is the opportunity to copy the dataset into the server before the GPU hours start billing. When you have TB's of datasets like me, you end up wasting 8-9 hours just copying the dataset and it feels annoying that I pay for the cloud hours during that time. Amazon kind of solves this, but it slows down data access in return. I would like a cloud provider who just lets me copy everything before starting to bill me.
What’s Nvidia supply chain like with their AI GPUs? Is it constrained or is this a joke :p
So, if by “hysterical,” you mean it is pretty funny and a reflection of the hype cycle, then yes. If you mean that I am being overwrought, I can assure you I am not. Even the hyperscalers do not have enough GPUs
Today, AMD support in PyTorch is minimal. Actually getting anything running is very difficult, and random crashes are common. This is in contrast to NVidia, which spends a lot of money to ensure a full compiler stack and compatibility with AI libraries.
Today, the AMD hardware itself is pretty capable and has a good price/performance ratio. However, actually taking advantage of that performance is difficult because of the poor quality of drivers and software.
It's going to take a big long investment, which people have been arguing about for the past 6 years, and AMD really isn't jumping up take the mantle. It's really a shame too because we need a strong competitor if we ever expect more realistic pricing for the average users/company.
... But in practice, I tore my hair out trying to port an actual Stable Diffusion web UI, until I hit a wall. I needed to upgrade the "Poplar SDK" or something beyond the ancient Python 3.8 version to get things working, but the download was behind some kind of corporate login.
That left a bad taste in my mouth.
... And this might be better now, I have not checked recently.
I shake my head every time when I read startups using AWS and racking up expensive and unpredictable bills to use the same compute that can be had at a fraction of the cost when using Tier 1.5 cloud providers.
As for this acquisition, I think it was a matter of time before GPUs were added to the service offering for Digital Ocean and this would be the best way forward rather than implementing this infrastructure from scratch.
I found about it in the reddit /r/cloudygamer sub and used it temporarily on vacation to play Assassin's Creed Odyssey and it worked pretty well.
Also Paperspace would let you choose how much GPU you needed, which seemed like a nice way to conserve costs if you were playing low-overhead games, some indies or older games, though I never used it as such.
In terms of investor return, I think it's healthy to have some exits like this. A bunch of the money was only in for 2 years, and probably doubled their investment in that time. The rest of the investors got their money back, with something close to NASDAQ returns on top of it. If this was the baseline for the fund instead of going to zero, you wouldn't need unicorns and the questionable growth tactics that go with them.
If founders had 25%, they got "retirement with reasonable luxuries" or "gunpowder to play investor" money of double digit $millions.
If 20-25 employees split an option pool of 15%, it's close to replacing the FAANG opportunity cost.
So totally agree that it's a bit of a "meh" outcome in comparison to financial alternatives, and the pie splitting matters a lot. But it didn't go to zero, and everyone is within a stone's throw of their stock market / FAANG hurdle rates (and it's not like that FAANG career is guaranteed for people who thrive better at startups). And the stories and experiences are a hell of a lot better.
I think exit is timely because there's the dire possibility of fading AI/LLM hype that's where GPU demand would fall off the cliff not only on the server side but also that many devices might have better inference hardware.
Does that mean they have/had lots of hardware investment? Or do they "just" offer a management layer based on other clouds?
Seems it was a win all around. They raised 35M exited at 111M. Not. 10x win but not under water.
However, this company was a few stages before IPO so there could have been less dilution from investors - allowing the founders to get a bigger cut.
On the other hand, some investors have really aggressive terms that can screw founders in situations like this. For example, their contracts could stipulate that an investor gets the first $45m of any exit even if that investor only put $15m into the company.
The "20%" case is typically the best case that happens only in the 1/10,000 chance of extreme fast growth into a new behemoth, OR where the founders are already high net worth individuals or come from high net worth families, and can provide their own money in conjunction with VCs instead of relying on them for most capital.
Because this is all private and not discussed, we tend to only hear of the very exceptional cases, and ignore the vast majority of the non-lottery winners in the startup world.
who locked you out? why did you get the hammer?
The thing that annoyed me most is: they knew the account was locked and I could not used it and still charged me.
