this post was submitted on 07 Jul 2024
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If the storage "crashes" it doesn't matter if it's in the cloud or on-prem.
With the cloud you get two substantial advantages:
Of course all this costs big bucks, but technically it's superior, easier and less risky.
AWS engineers' first responsibility is to shareholders
Mike's responsibility is to your same boss.
They are not the same.
Bonus: you can see Mike's certs are real.
It's not about responsibility (and only the c suite reports to the shareholders, not Mike), it's about capability, visibility, tooling and availability.
That's easily mitigated just following established standards. Redundancy is cheaper than anything else in the aftermath and documentation can be done easy with automation.
You don't, you rent rack space in a location far enough away but close enough to get the data in a few hours.
It's neither superior, easier or less risky, it's just a shift in responsibility. And in most cases, it's so expensive that a second or third on site engineer is payed for.
And what is simpler and faster, renting rack space in another continent (and buying, shipping, racking and initializing) or editing your terraform file?
Why on another continent? Except maybe VDI, some direct calls to some LLM or some insane scales, there's nothing really that needs those round trip times.
Also data rules / data privacy. Some things need to have the original in Europe; China & Russia also need their data separated from others.
Because the customer demands it.
Not OP, but they are comparable efforts, especially since it's a relatively infrequent activity. You can rent dedicated boxes with off-the-sheld hardware almost instantly, if you don't want to deal with the hardware procurement, and often you can do that via APIs as well. And of course both options are much, much, much cheaper than the Cloud solution.
For sure speed in general is something Cloud provide. I would say it's a very bad metric though in this context.
Full-ACK.
My last customer (global insurance company) provisions several systems a day. Now moving to hundreds via Jenkins. Frequency is environment dependent.
If your compute needs expand that much everyday, and possibly shrink in others, than your use-case is one that can benefit from Cloud (I covered this in the post).
That said, if provisioning means recycle, then it's obviously not a problem.
This is a very rare requirement. Most companies' load is fairly stable and relatively predictable, which means that with a proper capacity planning, increasing compute resources is something that happens rarely too. So rarely that even a lead time for hardware is acceptable.
So if I may ask (and you can tell), what is the purpose of provisioning that many systems each day? Are they continuously expanding?
Agree to disagree. Banking, telecommunications, insurance, automotive, retail are all industries where I have seen wild load fluctuations. The only applications where I have seen constant load are simulations: weather, oil&gas, scientific. That's where it makes sense to deploy your own hardware. For all else, server less or elastic provisioning makes economic sense.
Edit to answer the last question: to test variable loads, in the last one. Imagine a hurricane comes around and they have to recalculate a bunch of risk components. But can be as simple as running CI/CD tests.
Systems are always overspecced, obviously. Many companies in those industries are dynosaurs which run on very outdated systems (like banks) after all, and they all existed before Cloud was a thing.
I also can't talk for other industries, but I work in fintech and banks have a very predictable load, to the point that their numbers are almost fixed (and I am talking about UK big banks, not small ones).
I imagine retail and automotive are similar, they have so much data that their average load is almost 100% precise, which allows for good capacity planning, and their audience is so wide that it's very unlikely to have global spikes.
Industries that have variable load are those who do CPU intensive (or memory) tasks and have very variable customers: media (streaming), AI (training), etc.
I also worked in the gaming industry, and while there are huge peaks, the jobs are not so resource intensive to need anything else than a good capacity planning.
I assume however everybody has their own experiences, so I am not aiming to convince you or anything.
Banking is extremely variable. Instant transactions are periodic, I don't know any bank that runs them globally on one machine to compensate for time zones. Batches happen at a fixed time, are idle most of the day. Sure you can pay MIPS out of the ass, but you're much more cost effective paying more for peak and idling the rets of the day.
My experience are banks (including UK) that are modernizing, and cloud for most apps brings brutal savings if done right, or moderate savings if getting better HA/RTO.
Of course if you migrate to the cloud because the cto said so, and you lift and shift your 64 core monstrosity that does 3M operations a day, you're going to 3nd up more expensive. But that should have been a lambda function that would cost 5 bucks a day tops. That however requires effort, which most people avoid and complain later.
Ofc they don't run them on one machine. I know that UK banks have only DCs in UK. Also, the daily pattern is almost identical everyday. You spec to handle the peaks, and you are good. Even if you systems are at 20% half the day everyday, you are still saving tons of money.
Between banks, from customer to bank they are not. Also now most circuits are going toward instant payments, so the payments are settled more frequently between banks.
I want to see this happening. I work for one and I see how our company is literally bleeding from cloud costs.
One of the most expensive product, for high loads at least. Plus you need to sign things with HSMs etc., and you want a secure environment, perhaps. So I would say...it depends.
Obviously I agree with you, you need to design rationally and not just make a dummy translation of the architecture, but you are paying for someone else to do the work + the service, cloud is going to help to delegate some responsibilities, but it can't be cheaper, especially in the long run since you are not capitalizing anything.
Not only it can be cheaper, it is cheaper in most cases... when designed correctly. And if you compare TCO, not hardware vs IaaS.
It can also be much more expensive of course, but that's almost always a skill issue.
In most cases! Sorry, I simply don't believe it. Once you operate for 5, 10, 20 years not having capitalized anything is expensive as hell, even without the skill issue (which is not a great argument, as it is the case for almost anything).
It's almost always the case with rent vs invest.
Do you have some numbers?
I cite a couple of articles in the post, and here is a nice list of companies and orgs that run outside the Cloud (it's a bit old!) or decided to move away. Many big companies with their own DC, which is not surprising, but also smaller (Wikipedia!).
37signals also showed a huge amount of savings (it's one of the two links in the post) moving away from the cloud. Do you have any similar data that shows the opposite (like we saved X after going cloud)? I am genuinely curious
Edit: here is another one https://tech.ahrefs.com/how-ahrefs-saved-us-400m-in-3-years-by-not-going-to-the-cloud-8939dd930af8 Looking solely at the compute resources, there was an order of magnitude of difference between cloud costs and hosting costs (x11). Basically a value comparable (in reality double) to the whole revenue of the company.