Analyzing incoming workload in Cloud business services

Abstract

A recent trend, movement of software applications to Cloud, provides among numerous benefits, an important model for infrastructure cost reduction using the pay-as-you-go concept. In our experiments, we noticed that software distribution may significantly influence cost benefits achieved in Cloud. Software distribution optimization requires a continuous information influx on key metrics characterizing incoming workload. In this paper we propose a method for modeling workloads of business applications characterized by nonuniform distribution over the day. Two important properties are described: (1) modeling and forecasting repeatable patterns observed in the business context, and (2) modeling the inter-arrival time distribution of service requests. While former is important for constructing automated capacity planning controllers, latter is required for describing the amount of traffic variability. We analyzed these properties on a two-month workload collected from a production business services used by several thousand customers in retail domain in Croatia. Based on this analysis, we propose a high-level design of a quality of service controller applicable to business services in cloud environment.