Design a Simple API Throttling Mechanism

To design a simple service-level throttling mechanism, I would start by defining the core constraint: preventing any single client from overwhelming our resources. Since this is not a distributed system, we can rely on local in-memory storage. My primary recommendation is the Fixed-Window algorithm due to its extreme simplicity. We maintain a counter for each client ID within a fixed time bucket, say 60 seconds. When a request arrives, we increment the counter; if it exceeds the threshold, we reject the request immediately. However, I must highlight a known edge case: the 'boundary problem' where a client sends maximum requests at the end of one second and the start of the next, effectively doubling their throughput. To address this without adding significant complexity, I would propose a hybrid Sliding Window Counter. This divides the time window into smaller sub-windows, allowing us to interpolate the count based on the current sub-window's progress. For implementation, since Java is common in enterprise environments like IBM's, I would use ConcurrentHashMap with atomic increments to handle concurrent threads safely. Finally, the API response should strictly return a 429 status code with a Retry-After header to inform the client when they can retry, ensuring predictable behavior for consumers.