Several very big profile names have recently begun moving back to self-hosted, hybrid, or dedicated hosting solutions.
Cloud computing never was good in terms of value, however, it was only good in terms of scalability. AI solutions built on top of 'the cloud' will always be even worse.
Note that I pay a certain "third tier" cloud provider less than $100/mo total for hosting large websites that would cost me more than 10 grand a month on AWS/Azure/Google...while having better uptime. (the biggest differences? the complete lack of IO and bandwidth charges, and much lower storage charges)
That should tell you all you need about these types of bubbles, but then again, most of us that watched the entire tech field unfold since the pre-internet phase already knew this.
Could you provide some examples?
Some random survey from ESG found 60% of respondents repatriated at least some workloads. Who knows what the N was though.
Source: https://www.sdxcentral.com/articles/thinking-about-cloud-rep...
Frankly, it makes sense that companies are deciding what works best and where. But the death knell of cloud providers is simply not happening.
The prime selling point for cloud for large enterprises was (and still is):
- a signatory that shares blame on several core security issues (iso stuff) - high amount of flexibility for individual teams used to asking for a vm then waiting four weeks for the itops dept to bring it online
Now the vast majority of cloud moves for large enterprises ends up as a shitshow due to poor implementation sure, but the key points for getting it sold are still there.
And ofc you CAN still cost optimize with cloud, its just harder.
Context: Worked in post and pre sales over some years in MSFT in the enterprise segment.
I got out before the downturn and everyone talking about cost, but my approach in selling azure to the c-suite would be fairly similar today I reckon.
Learning aws vs learning how to operate a vps are of comparable complexity
It took me less then a day to setup infra for my startup (more than 10 years ago)
But tell me what third tier cheap provider has managed scale-to-zero-or-infinity functions? Managed storage with S3-like API? Where can I get an API gateway cheaper than Amazon? What about managed databases? These tools allow me to develop insanely scalable software incredibly easily.
Agreed - all the big clouds are very expensive VPS hostings. Don't use it for that.
You can scale from 1 thread 512MB RAM, to 500 threads and 12TB of RAM (off the shelf). Which is good enough for almost everyone who isn't planet scale.
Auto scaling also comes with auto billing. Oops, your accidental infinite loop spawning functions has bankrupted your company. You don't have that risk starting with a VPS.
What's third tier here? Pretty much all of them offer S3 compatibility it's basically table stakes
I try to not use anything else if I can avoid it on a new project.
Ingress gives you the ability to load balance and is threaded and will scale with network transfer and cpu. Database should scale with a bump in VM specs as well, CPU and disk IOPS.
If you keep your app server stateless you can simply multiply it for the number of copies you need for your load.
Systemd can keep your app server running, it you docker it up and use that
This right here so many times over.
I'm not going to spend time worrying about scaling, I'm going spend time figuring out how to make stuff stateless.
For new small systems I suggest you start with a cloud VPS. If traffic is low, cost of downtime is low, and system requirements are high then a cheap mini PC ($150) at the home or office can keep your bill microscopic. If your app server and database are small then you can just throw them on the VPS too.
I run light traffic stuff at home in a closet so it doesn't occupy more costly cloud RAM. Production ready saas offerings I'm trying to sell right now are all in the cloud. Hosting all my stuff in the cloud would cost me hundreds per month. My home SLA is fine for the extras. I don't need colocation at this time, but I have spoken with data centers to understand my upgrade path.
You can run a live backup server at a second location and have pretty good redundancy should the primary lose power or connectivity.
When system requirements elevate (SLA, security, etc) you probably want to move into a data center for better physical security, reliable power and network. Bigger VPS is fine if it is big enough. Can also do a colocation if you don't want to rent, and you contract directly with a data center. I wouldn't look at colocation until your actual hosting needs exceed at least $100/mo and you're ready for a year long commitment.
> Cloud infra may be a comparable market, since computation is a big share of AI costs. Did consumers win big from competition between AWS, Azure, and GCP? Not sure. I see an uptick in write ups saying “We switched off cloud and reduced costs by 2/3rds.” Not a scientific sample but may leave the question open.
(Probably also less reliable than "cloud", but who cares if you're a startup.)
Margin is a function of stickiness/cost of switching (among other things).
I suspect eventually we will enter a world where migrating cloud providers is mostly a click of a button, but we're a long ways off from that. Requires vendor agnostic and portable apis/containers/WASM runtimes everywhere.
Swapping an LLM, at least in the current state, is about as close to updating a pointer as you can get
Especially given that many orgs use managed or cloud specific solutions that have no 1:1 mapping between vendors
As someone who worked on a similar project recently, I'm getting that idea that you obviously don't know what you're talking about.
You need to plan ahead, sure. Portability was one of my main concerns (including the possibility to go self-hosted). But it's definitely not impossible, nor too hard to do.
And Kubernetes? It goes way beyond containers, you can replace many cloud provider-specific resources with Kubernetes resources. What alternative gives you that?
This will almost certainly lead to a prompt rebuild, to better accommodate new model idiosyncrasies.
If you are unlucky- your use case may be one where Evals require human review.
Unless you are YOLOing it without evals. In that case this is relevant.
If the cloud had not existed, those that claim they saved money switching away from cloud might never have been in business in the first place.
Cloud infra may be a comparable market, since computation is a big share of AI costs. Did consumers win big from competition between AWS, Azure, and GCP? Not sure. I see an uptick in write ups saying “We switched off cloud and reduced costs by 2/3rds.” Not a scientific sample but may leave the question open.