Microsoft Backend Engineer Interview Questions

I would first ask whether the limit is per user, per API key, per IP, or per endpoint, because that changes the design. My default choice would be a token bucket because it handles bursts better than a strict fixed window. I would enforce the limit as close to the edge as possible so the backend does not waste resources on requests that should be rejected. The reason I choose this approach is that it keeps the system responsive while still protecting it from overload. I would also talk about where the counter state lives, what happens if that store fails, and whether the system should fail open or fail closed.

I would add an idempotency key to the request and store the result or the processing state alongside that key. If the same request comes again, the service can return the original result instead of doing the work twice. The reason I choose this is that retries are unavoidable in distributed systems, so correctness must not depend on perfect network delivery. I would also think about expiration for stored keys and how to handle a request that fails halfway through. This is especially important for payments, orders, and other state-changing actions.

I would start by clarifying whether the service needs custom aliases, expiration, and analytics. My basic design would store a mapping from short code to original URL in durable storage and use a fast redirect path for reads. To scale under heavy traffic, I would add caching for hot links and shard the backing store so writes and reads spread across nodes. The reason I choose this split is that redirects are usually much more frequent than link creation. I would also mention collision handling, rate limiting, and abuse prevention.

I would first ask how long sessions should live and whether they need to survive server restarts. A common design is to keep session data in a shared store such as a distributed cache or database, with an expiration time attached to each session. The reason I choose shared storage is that any server can validate the session without depending on local memory. I would also think about session invalidation, token rotation, and what should happen when the session store is unavailable. If the interviewer wants more detail, I would compare server-side sessions with stateless tokens.

I would first identify what data is safe to cache and how fresh it needs to be. My default design would use a cache in front of the database, with a clear invalidation strategy and an eviction policy like LRU or LFU. The reason I choose caching is that it can reduce database load dramatically when the same data is read repeatedly. I would also discuss cache stampedes, hot keys, and whether stale reads are acceptable. The answer would depend on whether the business prefers freshness or lower latency.