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There is nothing like the rush of solving Good Problems (tm) in the middle of the night with a lit firecracker down your pants.

However I doubt all these problems are as unpredictable as the article makes them out to be. There's a whole field of science devoted solely to modeling large systems of interconnected stochastic processes and identifying bottlenecks.

This science is so old a mandatory semester-long class was devoted to it in 2nd year of my comp sci undergrad.

I do wonder how many developers who aren't working on government-backed systems actually use that science though ...



There is a big difference between theory and practice. :)

While it is possible to model the large system, usually as a startup you don't have the time to make the model, nor the data to feed the model.

Part of the problem is that you don't know what the inputs to the system will be and which inputs will grow exponentially.


There's a whole field of science devoted solely to modeling large systems of interconnected stochastic processes and identifying bottlenecks.

These models need to be fed known inputs and parameters such as component limits.

Neither can be specified in advance for your average, public-facing, constantly changing webapp.


Exactly. And when you're pumping out half a dozen titles, each with wildly different performance charactistics and no idea which will bomb and which will be a huge hit, it's not really worthwhile to be overly thorough with any single title until the shit hits the fan...

However, I do think the case could be made that trying to roll your own infrastructure in this kind of scenario is perhaps not the best use of your time, when solutions to scalabilty problems already exist and are so well tested.

(Edit: what I mean by that is, if you use something like App Engine, you really don't need to be concerned with scalability all that much -- as long as you're working sensibly and within the constraints of the platform)




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