Auto Scaling Architecture and Operations Questions

Designing and operating automatic scaling systems to elastically handle variable load. Topics include architecture patterns such as cloud auto scaling groups, cluster autoscalers, orchestration driven scaling, and automation of scaling decisions. Candidates should be able to select and justify metric based policies using processor utilization, memory usage, request rate, latency, and custom application signals; set thresholds, hysteresis, cooldown periods, and other safeguards to avoid scaling thrash; and compare horizontal scaling versus vertical resizing and proactive predictive scaling versus reactive strategies. Coverage includes scaling application tiers versus data stores and the special considerations for stateful systems and databases, including read replicas, partitioning and sharding, connection draining, session management, and approaches to isolate or make stateful components responsive to changing load. Also includes complementary operational techniques and trade offs such as caching, circuit breakers, load shedding, warm pools, capacity planning, monitoring and alerting, cost and reliability trade offs, safe degradation when limits are reached, testing autoscaling behavior under realistic load, and interactions with deployment and monitoring pipelines.