Abstract
Cloud Computing has become a new technical and economic model within companies. By virtualizing services, it allowed a more flexible management of datacenters capacities. However, its elasticity and its flexibility led to the explosion of virtual environments to manage. It’s common for a system administrator to manage several hundreds or thousands virtual machines. Without appropriate tool, this administration task may be impossible to achieve. We purpose in this paper a decision support tool to detect virtual machines with atypical behavior. Virtual machines whose behavior is different from other VMs running in the data center are tagged as a typicals. This tool has been validated in production and being used by several companies.
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Dumont, F., Menaud, JM. (2015). Synthesizing Realistic CloudWorkload Traces for Studying Dynamic Resource System Management. In: Qiang, W., Zheng, X., Hsu, CH. (eds) Cloud Computing and Big Data. CloudCom-Asia 2015. Lecture Notes in Computer Science(), vol 9106. Springer, Cham. https://doi.org/10.1007/978-3-319-28430-9_3
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DOI: https://doi.org/10.1007/978-3-319-28430-9_3
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