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Exploring the impact of chaos engineering with various user loads on cloud native applications: an exploratory empirical study

Al-Said Ahmad, Amro; Al-Qora’n, Lamis F.; Zayed, Ahmad

Authors

Lamis F. Al-Qora’n

Ahmad Zayed



Abstract

One of the most popular models that provide computer resources today is cloud computing. Today’s dynamic and successful platforms are created to take advantage of various resources available from service providers. Ensuring the performance and availability of such resources and services is a crucial problem. Any software system may be subject to faults that might propagate to cause failures. Such faults with the potential of contributing to failures are critical because they impair performance and result in a delayed reaction, which is regarded as a dependability problem. To ensure that critical faults can be discovered as soon as possible, the impact of such faults on the system must be tested. The performance and dependability of cloud-native systems are examined in this empirical study using fault injection, one of the chaos engineering techniques. The study explores the impacts and results of injecting various delay times into two cloud-native applications with diverse user numbers. The performance of the applications with various numbers of users is measured in relation to these delays, which accordingly reflects measuring the dependability of those systems. Firstly, the systems’ architecture were identified, and serverless with two Lambda functions and containerised microservices applications were chosen, which depend on utilising and incorporating cloud-native services. Secondly, faults are injected in order to quantify performance attributes such as throughput and latency. The results of several controlled experiments carried out in real-world cloud environments provide exploratory empirical data, which promoted comparisons and statistical analysis that we utilised to identify the behaviour of the application while experiencing stress. Typical results from this investigation include an overall reduction in performance that is embodied in an increase in latency with injecting delays. However, a remarkable result is noticed at a particular delay in which defects and availability problems appear out of nowhere. These findings assist in highlighting the value of using chaos engineering in general and fault injection in particular to assess the dependability of cloud-native applications and to find unpredicted failures that could arise quickly from defects that aren’t supposed to spread and result in dependability issues.

Citation

Al-Said Ahmad, A., Al-Qora’n, L. F., & Zayed, A. (2024). Exploring the impact of chaos engineering with various user loads on cloud native applications: an exploratory empirical study. Computing, https://doi.org/10.1007/s00607-024-01292-z

Journal Article Type Article
Acceptance Date Apr 22, 2024
Online Publication Date May 5, 2024
Publication Date May 5, 2024
Deposit Date May 5, 2024
Publicly Available Date May 9, 2024
Journal Computing
Print ISSN 0010-485X
Electronic ISSN 1436-5057
Publisher Springer Verlag
Peer Reviewed Peer Reviewed
DOI https://doi.org/10.1007/s00607-024-01292-z
Public URL https://keele-repository.worktribe.com/output/824713
Additional Information Received: 12 September 2023; Accepted: 22 April 2024; First Online: 5 May 2024; : ; : We declare no Conflict of interest.; : Not applicable; : Not applicable.; : All Authors approved the Manuscript.

Files

S00607-024-01292-z (2.8 Mb)
PDF

Licence
https://creativecommons.org/licenses/by/4.0/

Publisher Licence URL
https://creativecommons.org/licenses/by/4.0/

Copyright Statement
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.




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