How to estimate the average number of concurrent users and the peak concurrent number of the system

1. Classic formula 1:
   In general, the following empirical formulas are used to estimate the average number of concurrent users and peak data of the system

  1) The average number of concurrent users is C = nL/T
  2) The peak number of concurrent users C' = C + 3* Root number C
    C is the average number of concurrent users, n is the number of login sessions, L is the average length of login sessions, T is the time length of the value inspection
    C' is the peak number of concurrent users

  Example 1, assuming system A, the system has 3000 For a typical user, the average time from login to logout is 4 hours in a day, and in a , the user will only use the system within 8 hours.
  Then, the
  average number of concurrent users is: C = 400*4/8 = 200
  The peak number of concurrent users is: C' = 200 + 3* root number 200 = 243

  Example 2, a company designed a compensation system for its 170,000 employees , employees can enter the system to query their salary information, but not everyone will use this system. Assuming that only 50% of people use the system regularly, 70% of these people use it once in the last week of each month The system, and the average system time is 5 minutes.
  Then the average number of concurrent users in the last week of the month is (9 to 5):
  n = 170000*0.5*0.7/5 = 11900
  C= 11900*5/60/8 = 124

  The throughput calculation is: F = Vu * R / T is in units/s
    F is the transaction throughput, Vu is the number of virtual users, R is the number of requests issued by each virtual user, and T is the time spent processing these requests

2. General formula 2:
  For most scenarios, we use (user Total amount/statistical time) * impact factor (usually 3) to estimate concurrency.
  For example, taking the subway as an example, the number of passengers per day is 50,000, the morning peak is 7 to 9, and the evening peak is 6 to 7. According to the 8/2 principle, 80% of passengers will take the subway during peak hours. Then the number of people arriving at the subway ticket gate every second is 50000*80%/(3*60*60)=3.7, about 4 people/S. Considering the factors such as security check and entrance closing, the actual number of people accumulated at the ticket gate must be higher than this. To be large, assuming that everyone needs 3 seconds to enter the station, the actual concurrency should be 4 people/s*3s=12, of course, the impact factor can be increased according to the actual situation!

3. According to the PV calculation formula: For
  example, for a website, the daily PV is about 1000w. According to the 2/8 principle, we can think that 80% of the 1000w PV is completed within 9 hours a day (human energy is limited), then TPS is:
  1000w*80%/(9*3600)=246.92 pieces/s, taking the empirical factor 3, the concurrency should be:
  246.92*3=740

Fourth, according to TPS estimation:
   the formula is C = (Think time + 1 )*TPS

5. Calculated according to the number of system users: the number of
   concurrent users = 8% to 12% of the maximum number of online users in the system