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

Authors: Marta Catillo; Luciano Ocone; Umberto Villano; Massimiliano Rak

Addresses: DING, Università del Sannio, Benevento, Italy ' DING, Università del Sannio, Benevento, Italy ' DING, Università del Sannio, Benevento, Italy ' Dipartimento di Ingegneria Industriale (DII), Università della Campania Luigi Vanvitelli, Caserta, Aversa, Italy

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.

Keywords: auto-scaling; cloud computing; load testing.

DOI: 10.1504/IJGUC.2021.114823

International Journal of Grid and Utility Computing, 2021 Vol.12 No.2, pp.139 - 148

Received: 24 Jan 2020
Accepted: 13 May 2020

Published online: 30 Apr 2021 *

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