Rate limiting is a technique used to manage the frequency of client requests to a server, typically to prevent abuse or excessive costs associated with API usage, as illustrated by LinkedIn's practice of preventing users from opening an excessive number of profiles in a short time. Different methods for implementing rate limiting include storing all requests for audit purposes, using counters for requests within fixed time windows, and employing the "leaky bucket" algorithm to allow a continuous flow of requests while maintaining a limit. Each approach has its trade-offs related to flexibility, performance, and edge cases, such as race conditions or hitting minute boundaries. The choice of rate limits involves balancing between preventing abuse and allowing legitimate usage, often requiring adjustments based on historical data and ongoing monitoring. Additionally, services like PropelAuth offer built-in rate limiting to simplify the process for API providers.