Provisioning of Computing Resources for Web Applications under Time-Varying Traffic

Provisioning computing resources for a web application poses a challenge due to the time-varying nature of the application workload. We consider an environment where a subscriber acquires computing resources from an infrastructure provider to deploy a transactional web application. The objective is to acquire sufficient resources to meet a performance target given by Pr[response time ≤ x] ≥ β. Markov-modulated Poisson process (MMPP) has been shown to effectively model time-varying traffic. It has also been shown that service times can be characterized by a hyper-Erlang (HE) distribution. HE is a special case of the phase-type (PH) distribution. We model the application by an MMPP/PH/1 queue and use analytic results of this model to determine the required capacity to meet a given performance target over an extended period of time. An implementation of the TPC-W benchmark is used to verify the effectiveness of the model. We also investigate the relationship between the required capacity and workload parameters.