Rate limiting is a key strategy for managing network traffic by controlling the number of requests a client can make to a server, thereby enhancing security and preventing server overload. This guide explores various rate limiting techniques, including fixed window counters, sliding logs, sliding window counters, token buckets, and leaky buckets, each with their own advantages and drawbacks. For practical implementation, the article provides examples using Node.js, employing both a third-party library, Express Rate Limit, and a custom solution with Redis and Moment.js. It also discusses the importance of understanding global rate limit exceeded errors and offers strategies for managing such occurrences effectively, such as monitoring usage patterns and dynamically adjusting limits. Additionally, the guide introduces the rate-limiter-flexible library as a robust alternative for protecting APIs against excessive requests, making it suitable for managing distributed denial-of-service (DDoS) attacks and ensuring the reliability of web services.