I would say it’s a very bad metric though in this context.
Full-ACK.
Comment on I hate Clouds - a personal perspective on why I think Clouds suck
loudwhisper@infosec.pub 2 months agoNot 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.
nexusband@lemmy.world 2 months ago
Tja@programming.dev 2 months ago
My last customer (global insurance company) provisions several systems a day. Now moving to hundreds via Jenkins. Frequency is environment dependent.
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?
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.
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 Many companies in those industries are dynosaurs which run on very outdated systems (like banks) after all, and they all existed before Cloud was a thing.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.