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
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