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> And those requirements kept growing. If my calculations are correct, the standard setup for engineers now is a machine with 20 or more gigabytes of RAM just to RUN the software.

Close. In 2011, all the engineer desktops got upgraded to 36Gigs. At the time, the eng department still hadn't figured out how to deploy without duplicating hundreds of jar files everywere.



Hah, I bet all the new engineers were like, SWEET! I get a system with 36 gigs of RAM!

Then their hearts sank when they realized why.


Wow, that sounds like fun. What exactly is in the LinkedIn stack that requires so much memory?


Systems actually come standard with 48 gigs :) As it turns out, that's really useful for the part of my job requiring data modeling.

Somebody suggested LinkedIn is one large application, which is absolutely false. It's composed of many small applications, each deployed as a WAR file since the non-Node.js part of the site is on the JVM. There's a lot of overhead that comes from deploying this way. It doesn't matter in production or staging, but it adds up on a desktop.

At this point in time though, dev machines have stopped growing because we have shared stacks you can deploy a couple pieces of the application against if you want to test the whole thing.


Speculation, but it sounds like the main webapp you see at linkedin.com is a single monolithic application.


Even if it is a single monolithic application, it in no way could explain the use of that much RAM.


Nowadays I get OOM while running only FireFox and Netbeans - and I am not even running software I develop on my box :P




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