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    <p>To provide an answer and prevent people from having to search through the comments, a <a href="https://devcenter.heroku.com/articles/dynos">dyno</a> is like an entire computer. Using the <a href="https://devcenter.heroku.com/articles/procfile">Procfile</a>, you give each of your dynos <em>one command</em> to run, and it cranks away on that command, re-running it periodically to refresh it and re-running it when it crashes. As you can imagine, it's rather wasteful to waste an entire computer running a single-threaded webserver, and that's where <a href="http://gunicorn.org/">Gunicorn</a> comes in. </p> <p>The Gunicorn master thread does nothing but act as a proxy server, spawning a given number of copies of your application (workers), distributing HTTP requests amongst them. It takes advantage of the fact that each dyno actually has multiple cores. As someone mentioned, the number of workers you should choose depends on how much memory your app takes to run.</p> <p>Contrary to what Bob Spryn said in the last comment, there are other ways of exploiting this opportunity for parallelism to run separate servers on the same dyno. The easiest way is to make a separate sub-procfile and run the all-Python <a href="http://ddollar.github.io/foreman/">Foreman</a> equivalent, <a href="https://pypi.python.org/pypi/honcho">Honcho</a>, <em>from your main Procfile</em>, following <a href="http://www.radekdostal.com/content/heroku-running-multiple-python-processes-single-dyno-using-honcho">these directions</a>. Essentially, in this case your single dyno command is a program that manages multiple single commands. It's kind of like being granted one wish from a genie, and making that wish be for 4 more wishes.</p> <p>The advantage of this is you get to take full advantage of your dynos' capacity. The disadvantage of this approach is that you lose the ability scale individual parts of your app independently when they're sharing a dyno. When you scale the dyno, it will scale everything you've multiplexed onto it, which may not be desired. You will probably have to use diagnostics to decide when a service should be put on its own dedicated dyno.</p>
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