Application Programming Interface Design and Rate Limiting Questions
Focuses on designing scalable application programming interfaces that handle high request volumes while protecting infrastructure and preserving developer experience. Topics include API surface design and versioning, idempotency and retry semantics, authentication and authorization impacts, consistency and backward compatibility, and choosing protocols and payload formats. For scaling and protection discuss rate limiting and quota strategies such as token bucket, fixed window, sliding window, leaky bucket, per API key and per user limits, and hierarchical quotas. Cover backpressure, graceful degradation, circuit breakers, throttling responses and headers that communicate limits to clients, retry guidance, and strategies to avoid thundering herd effects. Also include operational concerns: monitoring and observability for request and error rates, metrics for usage and latency, metering and billing implications for usage based pricing, developer platform experience, documentation and developer tooling, testing at scale, and trade offs between strict protection and usability.
EasyTechnical
0 practiced
Design a concise header schema to communicate rate limit information to clients in every 429/200 response. Include headers for limit, remaining, reset, and support for multiple window granularities (minute, hour, day). Explain naming choices (X-RateLimit vs standardized) and how to avoid client clock skew affecting resets.
HardSystem Design
0 practiced
Design an API gateway that enforces distributed rate limiting across multiple regions, supports per-user and per-org quotas, adds minimal latency (<50ms extra), tolerates regional failures, and handles 1M requests per second globally. Describe architecture, state storage choices, consistency model, caching, failover behavior, and how to achieve fairness across regions.
HardTechnical
0 practiced
Design a system to detect and throttle abusive clients while minimizing false positives. Discuss detection signals (sudden request spikes, error patterns, unusual endpoints), adaptive throttling policies, graduated penalties, manual overrides, and privacy concerns when fingerprinting clients.
MediumSystem Design
0 practiced
Design a hierarchical quota system that supports per-organization, per-team, and per-user quotas with pooling and delegation. Describe enforcement points, data model for quota accounting, how to aggregate usage, how to handle overages and delegation, and how to surface per-entity usage to billing systems.
MediumTechnical
0 practiced
Design a sliding-window rate limiter that can be implemented using Redis. Describe the data structure, required Redis commands (ZADD, ZREMRANGEBYSCORE, ZCOUNT), and a Lua script to make checks atomic. Explain how to bound memory usage, eviction policy, and performance considerations when windows are small or clients are numerous.
Unlock Full Question Bank
Get access to hundreds of Application Programming Interface Design and Rate Limiting interview questions and detailed answers.
