Rate limiting in application design helps define access rules and policies to limit the number of requests an entity, such as a device, IP addresses, or individual users, can perform within a given amount of time. This ensures application security, stability, and sustainable scalability. Rate limiting is essential for improving large-scale web systems' security, performance, and quality by preventing resource starvation, security threats, data flow control, cost optimization, and policy management. A robust rate limiter should ensure system availability, system performance, and respond to all legitimate client requests. When designing a rate limiter, administrators must consider various factors such as request rates, error messages, concurrency, server-level rate limits, location/ID-based rate limiting algorithms, token bucket, leaky bucket, fixed window counter, sliding log, sliding window, throttling, data sharding and caching, and decentralized configuration models. Additionally, Edge Stack API Gateway provides an inbuilt Rate Limit Service that enforces a decentralized configuration model for independent management of rate limits by multiple teams, minimizing manual overhead.