Abstract
One of the main advantages of cloud computing is elasticity, which allows to rapidly expand or reduce the amount of leased resources in order to adapt to load variations, guaranteeing the desired quality of service. Auto-scaling is an extensively studied topic. Making optimal scaling choices is of paramount importance and can help reduce leasing costs, as well as power consumption. This paper analyzes the current status of auto-scaling in the cloud ecosystem, considering recent literature contributions as well as existing auto-scaling solutions. Then it discusses possible research directions in this field, fostering the development of a methodology that, on the basis of suitably-defined performance parameters, can produce an optimal auto-scaling policy to be implemented using existing auto-scaling services and tools.
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Catillo, M., Rak, M., Villano, U. (2020). Auto-scaling in the Cloud: Current Status and Perspectives. In: Barolli, L., Hellinckx, P., Natwichai, J. (eds) Advances on P2P, Parallel, Grid, Cloud and Internet Computing. 3PGCIC 2019. Lecture Notes in Networks and Systems, vol 96. Springer, Cham. https://doi.org/10.1007/978-3-030-33509-0_58
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DOI: https://doi.org/10.1007/978-3-030-33509-0_58
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