Probabilistic Modeling of Computing Demand for Service Level Agreement

Cloud computing applications must be allocated sufficient resources to comply with Service Level Agreements (SLAs). This paper considers data-driven probabilistic modeling of application resource demand for resource allocation. The modeling method is focused on peak demand and SLA violations and relies on a branch of statistics known as extreme value theory (EVT). Rigorous statistical validation of the proposed model shows that it generalizes better than the alternative. The paper presents a resource allocation algorithm using the model to ensure a given small SLA violation rate. For resource allocation in Yahoo data center, over 50 percent savings are demonstrated using the proposed approach.