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Scalability resilience framework using application-level fault injection for cloud-based software services

Al-Said Ahmad, Amro; Andras, Peter


Amro Al-Said Ahmad

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Prof Peter Andras
Dean of School of Computing Engineering and the Built Environment


This paper presents an investigation into the effect of faults on the scalability resilience of cloud-based software services. The study introduces an experimental framework using the Application-Level Fault Injection (ALFI) to investigate how the faults at the application level affect the scalability resilience and behaviour of cloud-based software services. Previous studies on scalability analysis of cloud-based software services provide a baseline of the scalability behaviour of such services, allowing to conduct in-depth scalability investigation of these services. Experimental analysis on the EC2 cloud using a real-world cloud-based software service is used to demonstrate the framework, considering delay latency of software faults with two varied settings and two demand scenarios. The experimental approach is explained in detail. Here we simulate delay latency injection with two different times, 800 and 1600 ms, and compare the results with the baseline data. The results show that the proposed approach allows a fair assessment of the fault scenario’s impact on the cloud software service’s scalability resilience. We explain the use of the methodology to determine the impact of injected faults on the scalability behaviour and resilience of cloud-based software services.

Journal Article Type Article
Acceptance Date Dec 16, 2021
Online Publication Date Jan 3, 2022
Publication Date 2022
Deposit Date Jan 13, 2022
Publicly Available Date Jan 13, 2022
Journal Journal of Cloud Computing
Publisher Springer
Peer Reviewed Peer Reviewed
Volume 11
Issue 1
Article Number 1
Keywords Resilience, Scalability, Software-as-a-service (SaaS), Application-level fault-injection
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