How to convert concurrent users into hits per second?

concurrency requirements
yegor256 picture yegor256 · Feb 20, 2011 · Viewed 10.2k times · Source

SRS for the system I'm currently working on includes the following non-functional requirement: "the SuD shall be scalable to 200 concurrent users". How can I convert this statement to a more measurable characteristic: "hits per second"?

Answer

Neville Kuyt picture Neville Kuyt · Feb 21, 2011

Assuming you're talking about a web application (based on your desire to estimate "hits" per second), you have to work on a number of assumptions. - How long will a user spend between interactions? For typical content pages, that might be 10 seconds; for interactive web apps, perhaps only 5 seconds. - Divide the number of users by the "think time" to get hits per second - 200 concurrent users with a think time of 10 seconds gives you 20 concurrent users on average. - Then multiply by a "peak multiplier" - most web sites are relatively silent during the night, but really busy around 7PM. So your average number needs to take account of that - typically, I recommend a peak of between 4 and 10 times. This gives you a peak page requests per second - this is usually the limiting factor for web applications (though by no means always - streaming video is often constrained by bandwidth, for instance). If you really want to know "hits", you then need to work through the following: - How many assets on your page? Images, stylesheets, javascript files etc. - "hit" typically refers to any kind of request, not just the HTML page (or ASPX or PHP or whatever). Most modern web apps include dozens of assets. - How cacheable are your pages and/or assets? Most images, CSS, JS files etc. should be set to cacheable by the browser.

Multiply the page requests by the number of non-cacheable assets. Add to this the number of visitors multiplied by the number of assets if you want to be super precise.

All of this usually means you have to make lots and lots of assumptions - so the final number is an indicator at best. For scalability measurements, I usually spend more time trying to understand the bottlenecks in the system and observing the system under load.

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