API Rate Limiting: A Guide for Identity Verification (1)

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API rate limiting controls how many requests clients can make within a defined period, helping identity verification platforms prevent DDoS attacks, credential stuffing, accidental overloads, service disruptions, and unnecessary costs while maintaining fair access. Common approaches include token bucket, leaky bucket, fixed window, sliding window log, and sliding window counter algorithms, with token bucket and sliding window counter often balancing performance and accuracy for high-volume services. Limits may be enforced by IP address, API key, authenticated user, or application, and Didit says it uses layered IP-, API key-, and user-based controls to manage peak traffic averaging 1,500 requests per second. The platform also uses real-time monitoring, machine-learning-driven dynamic throttling based on server load, endpoint activity, and client reputation, alongside customizable limits, dashboards, error messages, load testing, and integration support.

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