A Polymorphic Model for Event Associated Workload Bursts

How many cloud resources does an application provider require to manage workload bursts that often accompany events of public interest, (like product announcements or sporting events), and when will these resources be required? The availability and performance qualities of systems from numerous domains have often been compromised by such bursts, highlighting the importance of these questions. Earlier work begins to address these concerns by presenting burst models, which are parameterized by a single set of burst feature types, to describe bursts that can be associated with different event types from different domains. In this paper we argue that the profile of a burst can differ for different event types, and will depend on a variable number of feature types that describe the burst´s associated event. We contribute a method for creating a workload model that is polymorphic based on event characteristics. Our evaluation uses real world data sets for two different event types, and compares our event-based model to one of the most recent, state of the art models, for workload bursts. Results highlight the polymorphic model´s superior accuracy to the other model assessed, and the dependence of a burst´s profile on its associated event definition.