

Cost Analysis: TripAdvisor's and Pinterest's costs on the AWS cloud - bussetta
http://highscalability.com/blog/2012/11/1/cost-analysis-tripadvisor-and-pinterest-costs-on-the-aws-clo.html

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benjaminwootton
270 front end servers sounds absurd for the TripAdvisor model.

700k requests per minute is ~12k requests per second.

I've had a sustained 4k-5k on a single un-optimised instance of nginx.

TripAdvisor pages are obviously hugely more complex but a lot of the
processing will be happening in the middle tier / back end servers. Most of
these front-end requests should be trivially cacheable - static content served
to anonymous users, images, CSS and the like.

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bradleyland
Is it really fair to take a cursory look at someone's architecture and call
them out like that? It's especially unfair to throw out something like "I've
had a sustained 4k-5k on a single un-optimised instance of nginx." Serving
what? Is your problem in any way similar to theirs? Do you have a full
understanding of their problem?

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eropple
I used to work at TripAdvisor, and I don't think he's wrong. TA is a fun
company with a lot of really sharp engineers on the payroll--it was a
privilege to work with the folks I worked with. But the business focus is on
time-to-market, and 10+ years of that can lead to technical debt, which can
often present in ways like "requires enough AWS instances to calculate _every
digit of pi_ to not fall over." That focus is a conscious decision on their
part, though, and their success speaks for itself.

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bradleyland
I'm not saying he's wrong about their efficiency. I'm saying it sucks to come
behind someone and make blanket statements about their efficiency of
utilization without knowing any details. If you worked there, you're in a much
better place to comment.

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herge
I wonder how may developers 1.7 million per year buys you? A team of 15? Even
less if you count office space, managerial costs, etc.

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SystemOut
Not sure how that is relevant unless you plan on the engineers handling all
the web requests.

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knightni
I assume it's a reference to the cost of hiring engineers to make the code
more efficient, versus just throwing hardware at the problem.

