The most important thing as part of requirement gathering
for a performance testing engagement is to measure the concurrency that has to
be simulated/generated. A performance tester needs to get access to the server
logs / Analytical data to perform this action.
Let us take a small example of a restaurant which says they
server around 1500 customers a day for lunch, where the lunch hours being 12:00
– 3:00 PM. This translates to 500 customers every hour during their lunch time.
Now the key factor here is the average duration of a customer.
If people spend an hour for their lunch, it means that the
restaurant has to accommodate 500 people in one slot. Assuming that the average
time spent at lunch is 30 minutes, now the restaurant has to accommodate only
250 users.
Now the number either 500 or 250 is the number of customers
having their lunch at the same time, which is also known as concurrency.
This is exactly the same way that we calculate the number of
concurrent users on the system. The important factors to be considered while
calculating the concurrency are:
- The average duration of a visitor on the application
- Total number of visits on a peak day / peak hour
Now to get the above said statistics, one can either
configure Google analytics on the application or refer to Web server logs that
have the information about the user session start time and end time. The third
alternative is to get these statistics from the Business analyst in case if the
target load is a forecast or prediction for the future (like the coming thanks
giving day / Christmas Eve / Memorial Day/ Super bowl day etc.)
The scientific way of calculating the concurrency is to use little’s
law. The little’s law says “The long-term average number of customers in a stable system L is equal to the long-term average effective arrival rate, λ, multiplied by the
average time a customer spends in the system, W; or expressed algebraically: L = λW.” For more details on little’s law refer wiki (http://en.wikipedia.org/wiki/Little's_law
)
The total number of users on a web application can be
determined by the average arrival rate (100 users / hour and average time spent
in the application 1/10 hours (i.e. 6 minutes). Now the concurrency at any
point of time L = 100*1/10 = 10 users.
Hope this information is helpful in determining the target
user load for an application.
