The API Rate Limit pattern controls the rate at which clients make API requests by counting the number of requests in a specified time interval and reacting against abusive clients, in order to protect the limited resources of the API from exhaustion and denial of service attacks. This practice helps service providers to prevent abuse and ensure fair resource allocation, maintain system stability, monitor and control service availability, protect against DDoS attacks. In this research paper, we have identified patterns covering the API Rate Limit pattern adoption starting from its documentation to its implementation. Our objective is to elucidate the trade-offs associated with different identified patterns and offer guidance to developers in making informed decisions when choosing the most suitable Rate Limit method, scope, and granularity for their service. By providing a comprehensive overview of how to adopt the Rate Limit pattern, this paper aims to enhance the understanding of how APIs can be designed to facilitate high scalability, security, reliability, and service availability. Furthermore, we present each pattern along with known uses observed in real-world APIs and technologies.

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