1. A method comprising: calculating confidence values of models; selecting a selected action from among a class of said models, wherein said selecting is based on said confidence values; executing said selected action incrementally using a feedback-based execution engine, wherein said executing said selected action comprises detecting divergent behavior and triggering re-calculation of workload throttling values, wherein said feedback-based execution engine is controlled by said workload throttling values and said workload throttling values are applied incrementally to said feedback-based execution engine during said executing of said selected action, and wherein said executing of said selected action is repeated until an objective function is maximized, wherein said objective function specifies performance goals of workloads; and refining said models by associating a safety margin to said models, wherein said safety margin is based on a difference between predicted and observed values of said models.