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.
For example, after running web site performance software, the administrator concludes that the average number of concurrent users submitting requests on an online banking web site is 3,000. This number depends on the number of users who have signed up to be members of the online bank, their banking transaction behavior, the time of the day or week they choose to submit requests, and so on.
Therefore, knowing this information enables you to use the requests per minute formula described in this section to calculate how many requests per minute your system can handle for this user base. Since requests per minute and response time become inversely proportional at peak load, decide if fewer requests per minute is acceptable as a trade-off for better response time, or alternatively, if a slower response time is acceptable as a trade-off for more requests per minute.
Experiment with the requests per minute and response time thresholds that are acceptable as a starting point for fine-tuning system performance. Thereafter, decide which areas of the system require adjustment.
Solving for r in the equation in the previous section gives:
r = n/(Tresponse + Tthink)
For the values:
n = 2,800 concurrent users
Tresponse = 1 (one second per request average response time)
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 per minute is 42000.