Meta Backend Engineer Interview Questions

I would use an idempotency key and store it with the operation result or processing state. If the same key appears again, the server can return the earlier result instead of repeating the work. The reason I choose this design is that retries are normal and the business flow should stay correct even when the network is unreliable. I would also think about key expiration, partial failures, and what happens if the first request is still in progress when the retry arrives. This matters a lot for payments, order creation, and other state-changing actions.

I would start by asking whether the balancer needs sticky sessions, health checks, or regional routing. A simple version could use round robin, but in practice I would also consider least connections or weighted routing depending on the traffic pattern. The reason I prefer to keep the balancer stateless when possible is that it is easier to scale and recover. I would mention failover, connection draining, and how to avoid sending traffic to unhealthy instances. If the interviewer wants more depth, I would also discuss long-lived connections.

I would use Dijkstra's algorithm. I would keep a priority queue of the next node to visit and relax outgoing edges from the node with the smallest known distance. The reason I choose Dijkstra is that it is the standard solution when all weights are non-negative and it gives the correct shortest path efficiently. The time complexity is O((V + E) log V) with a binary heap. If negative edges are allowed, I would say I need a different algorithm because Dijkstra would no longer be valid.

I would first check whether logging is synchronous and whether each request is generating too much detail. My first fix would be to batch logs and make the logging path asynchronous so the application does less work on the critical path. The reason I choose batching is that logs should help with debugging without becoming the reason the service slows down. I would also consider sampling, log levels, and compression if the volume is still too high. If the interviewer asks, I would mention that observability has to be balanced against runtime cost.

I would first define what 'nearest' means, because it could mean network latency, geography, or cost. My design would use geo-aware routing with health checks so requests go to a nearby region that is actually able to serve traffic. The reason I choose this approach is that latency only helps if the destination can respond reliably. I would also think about failover, routing consistency, and how to avoid traffic bouncing between regions. At scale, monitoring and clear routing rules become very important.