Big-O is often used for speed, but it applies to anything satisfying Blum's axioms. API requests are a good example, especially when using a throttled or pay-fo

Big-O is often used for speed, but it applies to anything satisfying Blum's axioms. API requests are a good example, especially when using a throttled or pay-for API. I was in a design discussion this morning for some new functionality which requires hitting a pay-for API; and much of the design was based on minimising how many calls we'll make. A naive polling approach would require O(t×e×u) requests, where t is time, e is the number of the events we care about and u is the number of users affected by those events. The design we came up with uses a separate data source to identify when those events occur, which removes the factor of t. We also came up with some de-duplication logic which reduces the constants.