Poisson distributions are sort of like the normal distribution for queuing theory for two main reasons: 1. They're often a pretty good approximation for how we

Poisson distributions are sort of like the normal distribution for queuing theory for two main reasons: 1. They're often a pretty good approximation for how web requests (or whatever task your queuing system deals with) arrive into your system, as long as your traffic is predominantly driven by many users who each act independently. (If your traffic is mostly coming from a bot scraping your site that sends exactly N requests per second, or holds exactly K connections open at a time, the Poisson distribution won't hold.) Sort of like how the normal distribution shows up any time you sum up enough random variables (central limit theorem), the Poisson arrival process shows up whenever you superimpose enough uncorrelated arrival processes together: https://en.wikipedia.org/wiki/Palm%E2%80%93Khintchine_theorem https://en.wikipedia.org/wiki/Palm%E2%80%93Khintchine_theore... 2. They make the math tractable -- you can come up with closed-form solutions for e.g. the probability distribution of the number of users in the system, the average waiting time, average number of users queuing, etc: https://en.wikipedia.org/wiki/M/M/c_queue#Stationary_analysis https://en.wikipedia.org/wiki/M/M/c_queue#Stationary_analysi... https://en.wikipedia.org/wiki/Erlang_(unit)#Erlang_B_formula https://en.wikipedia.org/wiki/Erlang_(unit)#Erlang_B_formula