One of the key benefits of Cloud computing is elasticity, the ability of the system infrastructure to adapt to the workload changes by automatically adjusting the resources on-demand. Horizontal scaling refers to the method of adding or removing resources from the resource pool. As such it is appealing to enterprises who seek to migrate their legacy systems as it requires no application rewrite or refactoring. Vertical scaling approach offers a mechanism to maintain continuous performance while reducing resource cost through reconfiguration of the resource. The challenge is, however, in being able to automatically identify the right size of the target resource such as a VM or a container. Moreover, choice of scalability policies is not intuitive due to application complexity, topology and variability in system performance parameters that need to be considered. This paper presents a transformation model, FitScale, which provides scalability with minimum price of resources. The paper describes the framework that employs the application functional and operational properties to recommend the target sizing and scalability policies. We evaluate proposed approach in an on-premise and cloud environments, with a dataset of 2023 servers hosting 6737 applications. The experimental results show about 5 times cost reduction with minimum performance impact.
CITATION STYLE
Hwang, J., Vukovic, M., & Anerousis, N. (2016). Fitscale: Scalability of legacy applications through migration to cloud. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9936 LNCS, pp. 123–139). Springer Verlag. https://doi.org/10.1007/978-3-319-46295-0_8
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