Top 4 Load shedding Interview Questions
Browse 4 real-world technical and behavioral interview questions about Load shedding. Review scenarios, edge cases, and architectural best practices.
Traffic is a hundred times normal and some of it is real customers. What do you drop first?
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.
Your rate limiter runs in five regions with a cap of 100 requests a minute per user. One user gets 500 through. Where did the counting go wrong?
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 trigger for the outage is gone and you have restarted the service, and it collapses again within a minute of taking traffic. Why will it not recover on its own?
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.
You need to enforce 100 requests per minute per API key across a fleet of forty servers. Which limiting algorithm, and where does the counter live?
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.