I'm sure LinkedIn could have cut servers without switching to node. Take your first, crappy implementation and rewrite it in the same language and you'll probably still see at least 10x improvement, if not 20.
In most cases, you're not. You're mostly making a big logic spaghetti mess on both the client and the server AND make your pages load slower, especially for the initial load (client performance, js loading times, etc).
>What makes you think refactoring code is going to give you a 10x improvement in efficiency?
Because even correctly implementing just the caching layer, with nested/micro-caching, can give you up to 1000x improvement in efficiency in the first place.
When you have real data on the client instead of just a bunch of markup, you can be a lot smarter about how and when you make additional AJAX requests. Optimistic updates can make a huge difference in perceived performance.
You will probably will get the same mess. There is plenty of literature about that. I.e: A complete rewrite is what killed Netscape
That's a meme started by a Joel Spolsky article, and maybe an allusion to the "second system effect" (which is about something else altogether). Hardly "plenty of literature about that".
Actually, the complete rewrite might killed Netscape, but it saved Mozilla and Firefox. And Netscape was a multi-million line web browser engine, with a javascript interpreter, a full mail client and a wysiwyg editor thrown in. And multi-platform in C/C++ to boot.
That is, something an order of magnitude more difficult than LinkedIn or 99% of web properties out there.
There have been TONS of successful rewrites. Especially in the web space, it's almost trivial to rewrite your webapp or parts of it. To name but a few:
Twitter, the new Digg, SoundCloud, Basecamp, etc etc.
"That's a meme started by a Joel Spolsky article, and maybe an allusion to the "second system effect" (which is about something else altogether)."
That said, the "second system effect" is not about merely rewriting risks, but especially about architecture and design choices. From the very wikipedia article:
"""People who have designed something only once before, try to do all the things they "did not get to do last time," loading the project up with all the things they put off while making version one, even if most of them should be put off in version two as well."""
That is, if you design your rewrite _without_ wanting to build a bigger, more involved product, but merely a cleaner and more cleanly made product, this does not apply.
Another quote from the very article: """The second-system effect refers to the tendency of small, elegant, and successful systems to have elephantine, feature-laden monstrosities as their successors."""
This is not the case we refer to here. The Netscape got by version 4 had gotten an ungodly mess (and even before that), not a "small, elegant" system. And Mozilla/Firefox, the rewrite, is cleaner and more elegant than Netscape was.
Consider a 100 line Python script. People can rewrite it from scratch in 100 different ways, while improving upon it with no problem. At some point of complexity this stops being true, but Brooks was talking about huge projects, built by enormous teams, like OS/360 and such. Not some 20K - 100K line web project.
What do you mean?
We wouldn't have those if it wasn't for the rewrite. The old code was a mess even before version 4 (by its developers own admission), and it could never get to the point of competing in the engine space ever again.
That is, with the old Netscape rendering engine it would not be possible to extend it to compete in the modern HTML5/Canvas/GPU acceleration/CSS3/add-ons/separate contexts for each tab/etc era.
Biggest improvements came from persistant connections to redis/mongodb and polling for updated information independently of requests so there was no cached-or-fetch shenanigans at all in some areas.
I'd actually be very surprised if NodeJS running on Heroku (which is built on EC2) performs better than compiled .NET code running on dedicated Windows hardware.
The equivalent in .NET I guess would be BackgroundWorkers that are independently prefetching the data required most of the time but I could never get them to Just Work.
Specifically for my use case 99+ percent of requests receive some data, do some light manipulations and then push the data to redis about 8,000 to 12,000 times a second. With .NET I could only push to locally running software instances because anything remote couldn't keep up with the connection volume (without throwing even more hardware at the problem).
It's really just like using any memcached or the built in .net caching rather than a write through one, new data reaches each dyno either via the periodic refresh or when it tries to create that record and finds it already exists. Writes are done immediately and the caches don't get updated because there's 8 - 16 dynos and why bother updating the single dyno that created it.
I did originally use redis pub/sub to push out updates to everything but I ended up removing it because it was unnecessary.
Here's some example code, it pre-fetches all the leaderboards (not scores) every 30 seconds: http://pastebin.com/asq6eExu
Higher up in the same script is the api for the leaderboard data with stuff like: http://pastebin.com/gsfvsZsv
I'm really puzzled by this. A single dedicated large .NET box (16GB RAM and 6 Core Processor, 1TB raid, etc.) runs $150 a month. When I was looking at PaaS, Heroku came in more than five times that much for similar capability. $1,000 a month gets me SIX of these dedicated boxes that can be tied together as needed.
Why was your setup so much more for dedicated that you could _save_ that much, much less why you would be spending that much in the first place?
http://ikaisays.com/2012/10/04/clearing-up-some-things-about...
This is hardly surprising.