Some things simply don't scale. You can't do some things in real-time. You have to do it in batch-jobs or avoid them. If you know about the O-notation, you will probably know certain algos don't scale. Friendster insisted to calculate the friends-of-friends-of-friends relationship in real-time and was not able to scale it. MySpace and Facebook did the same calc in the early days too, but both scrapped the feature as they were not able to scale it. Other examples are big data (e.g. log analysis), if you choose the wrong software stack (database) or wrong indexes you won't be able to scale it (especially if it's real time. You will bleed money in no time for cloud servers with TBs of RAM, when you could do it with a couple of servers with a normal sharded SQL database and one hand tuned index.
Re:Does it scale? Who cares (2011)
by user5994461 on Sunday April 09, 2017 @08:57AM
(#14072054)
> The technology to do so is all so good.
Mistake #1: Took the wrong technologies.
For every technology that can scale, there is a bunch of other that will give a lot of troubles.
Re:Does it scale? Who cares (2011)
by graphememes on Sunday April 09, 2017 @01:47AM
(#14070699)
Depends on what you're doing, easy to fail when you do analytics or something like datadog.
These days there would be hardly any way to fail to scale given a large budget. The technology to do so is all so good. However, back in the day it wasn't always so. I'd say Friendster was an example of a company that failed due to scaling issues.