Comment on I hate Clouds - a personal perspective on why I think Clouds suck

• loudwhisper@infosec.pub ⁨2⁩ ⁨months⁩ ago

  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?

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  • Tja@programming.dev ⁨2⁩ ⁨months⁩ ago

    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.

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    • loudwhisper@infosec.pub ⁨2⁩ ⁨months⁩ ago

      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 Many companies in those industries are dynosaurs which run on very outdated systems (like banks) after all, and they all existed before Cloud was a thing.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.

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      • Tja@programming.dev ⁨2⁩ ⁨months⁩ ago

        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.

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