Top 3 Load balancing Interview Questions
Browse 3 real-world technical and behavioral interview questions about Load balancing. Review scenarios, edge cases, and architectural best practices.
Your autoscaling is configured exactly as designed and the service still browns out every Monday at nine. Where is the time going?
Reactive scaling has a latency of its own — metric window, evaluation, provisioning, warm-up, health checks — and a surge that arrives faster than that latency is served entirely by the capacity you already had. The fix is a scheduled floor plus a saturation-based signal, not a more aggressive policy.
You move an internal service to gRPC behind the same load balancer your REST services use, and one pod ends up serving most of the traffic. What is happening, and what do you change?
gRPC multiplexes many calls over one long-lived HTTP/2 connection, so a balancer that distributes connections pins each client to one backend for its lifetime. Balance per request with an HTTP/2-aware proxy or client-side subchannels, and bound connection age so scaling out actually moves traffic.
When do you scale out instead of up, and what does that force you to change?
Scale up while one machine can still hold the workload, because it costs no distributed complexity; scale out once you need redundancy or exceed the largest instance. Scaling out only works if the tier is stateless, which means externalising session state rather than pinning users to a node.