Business-Driven Long-Term Capacity Planning for SaaS Applications

Abstract

Capacity Planning is one of the activities developed by Information Technology departments over the years, it aims at estimating the amount of resources needed to offer a computing service. This activity contributes to achieving high Quality of Service levels and also to pursuing better economic results for companies. In the Cloud Computing context, one plausible scenario is to have Software-as-a-Service (SaaS) providers that build their IT infrastructure acquiring resources from Infrastructure-as-a-Service (IaaS) providers. SaaS providers can reduce operational costs and complexity by buying instances from a reservation market, but then need to predict the number of instances needed in the long-term. This work investigates how important is the capacity planning in this context and how simple business-driven heuristics for long-term capacity planning impact on the profit achieved by SaaS providers. Simulation experiments were performed using synthetic e-commerce workloads. Our analysis show that proposed heuristics increase SaaS provider profit, on average, at $9.6501$ percent per year. Analysing such results we demonstrate that capacity planning is still an important activity, contributing to the increase of SaaS providers profit. Besides, a good capacity planning may also avoid bad reputation due to unacceptable performance, which is a gain very hard to measure.