• DocumentCode
    739817
  • Title

    Business-Driven Long-Term Capacity Planning for SaaS Applications

  • Author

    Candeia, David ; Araujo Santos, Ricardo ; Lopes, Raquel

  • Author_Institution
    Cienc. e Tecnol. da Paraiba, Inst. Fed. de Educ., Campina Grande, Brazil
  • Volume
    3
  • Issue
    3
  • fYear
    2015
  • Firstpage
    290
  • Lastpage
    303
  • 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.
  • Keywords
    cloud computing; profitability; IaaS providers; SaaS applications; business-driven heuristics; business-driven long-term capacity planning; cloud computing context; computing service; electronic commerce; information technology departments; infrastructure-as-a-service; quality-of-service levels; software-as-a-service; synthetic e-commerce workloads; Capacity planning; Cloud computing; Contracts; Measurement; Planning; Quality of service; Capacity Planning; Capacity planning; Cloud Computing; Software-as-a-Service; cloud computing; software-as-a-service;
  • fLanguage
    English
  • Journal_Title
    Cloud Computing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    2168-7161
  • Type

    jour

  • DOI
    10.1109/TCC.2015.2424877
  • Filename
    7090976