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Browse 3 real-world technical and behavioral interview questions about Load balancing. Review scenarios, edge cases, and architectural best practices.
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.
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.
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.