A Hybrid Machine Learning and Control-Theoretic Framework for Stability-Assured Resource Management in Large-Scale Cloud Computing Environments
A hybrid design can reduce elastic lag, control oscillatory scaling behavior, preserve bounded latency error, and support auditable resource governance more effectively than purely reactive autoscaling or unconstrained learning policies.