We have games & apps that connect to services such as Facebook and Twitter to fetch information. These services have various rate-limit caps that you cannot exceed - typically based on a 15 minute window of time. If we exceed this rate - the service blocks for a while. This makes my users sad. For a concrete example - you can only fetch a users tweets about 300 times per 15 minute window.
I would like to estimate how many users it might take before I could reasonably expect to hit this quota of 300 events in any given 15 minute window. This is so I can look ahead from our usage trends and maybe cache this data or pool it or whatever.
- A user can be expected to use the app for 5 minutes then quit
- There is a 1/5 any given user will access this twitter feed during a session (based on actual usage)
- I would restrict this usage to daylight hours (Not yet concerned about lower levels of - users at night - most of our gamers are in the US mainland and not night owls)
- I assume usage is evenly spread across this time.
I see it is connected to questions such as this: ( How to calculate the probability of two events happening within a certain time period using exponential distribution ) but I can't quite connect the dots :)
Thanks for any input!