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Browse 4 real-world technical and behavioral interview questions about Load shedding. Review scenarios, edge cases, and architectural best practices.
A DDoS or 100x traffic spike needs load shedding that separates real users from abusive or low-value work. Absorb volume at the edge, serve cacheable requests, protect checkout paths and reject expensive new work quickly before queues amplify retries.
Global rate limiting fails when each region owns a local counter, because five regions each allowing 100 requests creates a 500-request ceiling. Use one atomic shared counter, route each user to an owning region, or lease regional budget deliberately. It also connects distributed counters to the point an interviewer is testing.
The system is being held down by effects it now generates itself: accumulated client retries, an empty cache multiplying database load, and a queue of requests whose callers have already given up. Recovery needs shed load and a controlled ramp, not more capacity.
Fixed windows permit twice the limit across a boundary; the two sliding windows fix that at a memory or an accuracy cost; token bucket permits a bounded burst and leaky bucket smooths output instead. Across a fleet the counter must sit in one store mutated atomically, or each node silently enforces its own limit.