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How do you calculate requests per minute?
If you know the number of concurrent users at any given time, the response time of their requests, and the average user think time, then you can calculate the number of requests per minute. Typically, start by estimating the number of concurrent users that are on the system.
How many requests per second is normal?
The from-the-box number of open connections for most servers is usually around 256 or fewer, ergo 256 requests per second. You can push it up to 2000-5000 for ping requests or to 500-1000 for lightweight requests.
How do you do feet per second?
Divide your speed in feet per minute by 60. This is the number of seconds in a minute. Therefore, the result is your speed in feet per second. For example, 5,280 feet per minute divided by 60 seconds in a minute equals 88 feet per second.
How to calculate the number of concurrent users?
Only by knowing the test cases and additional numbers such as visits and page views per time unit can you a) define a number of concurrent users and b) check each number by means of calculation against the other numbers. Oh, and needless to say that 42 is always a good number of concurrent users…
How to calculate number of requests per second?
Tthink= 3, (three seconds average think time) The calculation for the number of requests per second is: r = 2800 / (1+3) = 700 Therefore, the number of requests per second is 700 and the number of requests
What happens to page views when there are 25 concurrent users?
The number of page views stays the same since 1 visit equals 4 page views and the number of visits is constant. These 25 users need to complete their visits simultaneously and in parallel but still independent of one another. We now have 25 concurrent users that produce the exact same traffic simulation as 2 users without a think time.
What do concurrent users mean in load testing?
Most of you probably know the term Concurrent User. In the context of load and performance testing, this metric is often claimed the measure of all things, accompanied by the mentioning of astronomically high numbers we can’t really verify and that sometimes are simply used as sales argument for overpriced software products.