One of the most interesting features of cloud environments is the possibility to deploy scalable applications, which can automatically modulate the amount of leased resources so as to adapt to load variations and to guarantee the desired level of quality of service. As auto-scaling has severe implications on execution costs, making optimal choices is of paramount importance. This paper presents a method based on off-line black-box load testing that allows to obtain performance indexes of a web application in multiple configurations under realistic load. These indexes, along with available resource cost information, can be exploited by auto-scaler tools to implement the desired scaling policy, making a trade-off between cost and user-perceived performance.

Black-box load testing to support auto-scaling web applications in the cloud / Catillo, M.; Ocone, L.; Villano, U.; Rak, M.. - In: INTERNATIONAL JOURNAL OF GRID AND UTILITY COMPUTING. - ISSN 1741-847X. - 12:2(2021), pp. 139-148. [10.1504/IJGUC.2021.114823]

Black-box load testing to support auto-scaling web applications in the cloud

Rak M.
2021

Abstract

One of the most interesting features of cloud environments is the possibility to deploy scalable applications, which can automatically modulate the amount of leased resources so as to adapt to load variations and to guarantee the desired level of quality of service. As auto-scaling has severe implications on execution costs, making optimal choices is of paramount importance. This paper presents a method based on off-line black-box load testing that allows to obtain performance indexes of a web application in multiple configurations under realistic load. These indexes, along with available resource cost information, can be exploited by auto-scaler tools to implement the desired scaling policy, making a trade-off between cost and user-perceived performance.
2021
Black-box load testing to support auto-scaling web applications in the cloud / Catillo, M.; Ocone, L.; Villano, U.; Rak, M.. - In: INTERNATIONAL JOURNAL OF GRID AND UTILITY COMPUTING. - ISSN 1741-847X. - 12:2(2021), pp. 139-148. [10.1504/IJGUC.2021.114823]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/986096
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