Systematic literature review of metrics for measuring devops success

Ankur Kumar; Mohammad Nadeem; Mohammad Shameem

doi:10.1063/5.0128883

Systematic literature review of metrics for measuring devops success

Ankur Kumar^*, Mohammad Nadeem, Mohammad Shameem

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

DevOps emerged as a better paradigm within the software organization. DevOps software is providing beneficial service for the organizations as it helps in reducing the resources in the terms of money, time and effort. Adopting new technology is not always easy, so is the case with DevOps. Software organizations are hesitant to adopt DevOps because the number of leader organizations in DevOps is very less. This is why the initial organization of DevOps does not follow the leader organization, but follows some maturity model. The maturity model gives an idea of the maturity level of DevOps within the software organization. The DevOps maturity model contain different levels of maturity. The distinguished maturity level is decided through certain parameters or metrics. The primary purpose of this study is to identify some set of priority metrics that influence DevOps adoption in software organizations. The method adopted for this study is systematic literature review (SLR). We extracted 32 metrics from 57 articles identified through systematic literature review. These metrics can be used to evaluate DevOps maturity within organizations. We believe that this study will serve as the basis for the development of maturity models to implement DevOps practices in software organizations. The proposed maturity model will be based on these metrics.

Original language	English
Title of host publication	Computational Intelligence and Network Security
Editors	K. Jairma Naik, Preeti Chandrakar, Dilip Singh Sisodia
Publisher	American Institute of Physics Inc.
ISBN (Electronic)	9780735444560
DOIs	https://doi.org/10.1063/5.0128883
State	Published - 28 Apr 2023
Externally published	Yes
Event	1st International Conference on Computational Intelligence and Network Security 2022, ICCINS 2022 - Raipur, Virtual, India Duration: 3 Mar 2022 → 4 Mar 2022

Publication series

Name	AIP Conference Proceedings
Volume	2724
ISSN (Print)	0094-243X
ISSN (Electronic)	1551-7616

Conference

Conference	1st International Conference on Computational Intelligence and Network Security 2022, ICCINS 2022
Country/Territory	India
City	Raipur, Virtual
Period	3/03/22 → 4/03/22

Bibliographical note

Publisher Copyright:
© 2023 Author(s).

ASJC Scopus subject areas

General Physics and Astronomy

Access to Document

10.1063/5.0128883

Cite this

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title = "Systematic literature review of metrics for measuring devops success",

abstract = "DevOps emerged as a better paradigm within the software organization. DevOps software is providing beneficial service for the organizations as it helps in reducing the resources in the terms of money, time and effort. Adopting new technology is not always easy, so is the case with DevOps. Software organizations are hesitant to adopt DevOps because the number of leader organizations in DevOps is very less. This is why the initial organization of DevOps does not follow the leader organization, but follows some maturity model. The maturity model gives an idea of the maturity level of DevOps within the software organization. The DevOps maturity model contain different levels of maturity. The distinguished maturity level is decided through certain parameters or metrics. The primary purpose of this study is to identify some set of priority metrics that influence DevOps adoption in software organizations. The method adopted for this study is systematic literature review (SLR). We extracted 32 metrics from 57 articles identified through systematic literature review. These metrics can be used to evaluate DevOps maturity within organizations. We believe that this study will serve as the basis for the development of maturity models to implement DevOps practices in software organizations. The proposed maturity model will be based on these metrics.",

author = "Ankur Kumar and Mohammad Nadeem and Mohammad Shameem",

note = "Publisher Copyright: {\textcopyright} 2023 Author(s).; 1st International Conference on Computational Intelligence and Network Security 2022, ICCINS 2022 ; Conference date: 03-03-2022 Through 04-03-2022",

year = "2023",

month = apr,

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doi = "10.1063/5.0128883",

language = "English",

series = "AIP Conference Proceedings",

publisher = "American Institute of Physics Inc.",

editor = "Naik, \{K. Jairma\} and Preeti Chandrakar and Sisodia, \{Dilip Singh\}",

booktitle = "Computational Intelligence and Network Security",

}

Kumar, A, Nadeem, M & Shameem, M 2023, Systematic literature review of metrics for measuring devops success. in KJ Naik, P Chandrakar & DS Sisodia (eds), Computational Intelligence and Network Security., 030005, AIP Conference Proceedings, vol. 2724, American Institute of Physics Inc., 1st International Conference on Computational Intelligence and Network Security 2022, ICCINS 2022, Raipur, Virtual, India, 3/03/22. https://doi.org/10.1063/5.0128883

Systematic literature review of metrics for measuring devops success. / Kumar, Ankur; Nadeem, Mohammad; Shameem, Mohammad.
Computational Intelligence and Network Security. ed. / K. Jairma Naik; Preeti Chandrakar; Dilip Singh Sisodia. American Institute of Physics Inc., 2023. 030005 (AIP Conference Proceedings; Vol. 2724).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Systematic literature review of metrics for measuring devops success

AU - Kumar, Ankur

AU - Nadeem, Mohammad

AU - Shameem, Mohammad

PY - 2023/4/28

Y1 - 2023/4/28

N2 - DevOps emerged as a better paradigm within the software organization. DevOps software is providing beneficial service for the organizations as it helps in reducing the resources in the terms of money, time and effort. Adopting new technology is not always easy, so is the case with DevOps. Software organizations are hesitant to adopt DevOps because the number of leader organizations in DevOps is very less. This is why the initial organization of DevOps does not follow the leader organization, but follows some maturity model. The maturity model gives an idea of the maturity level of DevOps within the software organization. The DevOps maturity model contain different levels of maturity. The distinguished maturity level is decided through certain parameters or metrics. The primary purpose of this study is to identify some set of priority metrics that influence DevOps adoption in software organizations. The method adopted for this study is systematic literature review (SLR). We extracted 32 metrics from 57 articles identified through systematic literature review. These metrics can be used to evaluate DevOps maturity within organizations. We believe that this study will serve as the basis for the development of maturity models to implement DevOps practices in software organizations. The proposed maturity model will be based on these metrics.

AB - DevOps emerged as a better paradigm within the software organization. DevOps software is providing beneficial service for the organizations as it helps in reducing the resources in the terms of money, time and effort. Adopting new technology is not always easy, so is the case with DevOps. Software organizations are hesitant to adopt DevOps because the number of leader organizations in DevOps is very less. This is why the initial organization of DevOps does not follow the leader organization, but follows some maturity model. The maturity model gives an idea of the maturity level of DevOps within the software organization. The DevOps maturity model contain different levels of maturity. The distinguished maturity level is decided through certain parameters or metrics. The primary purpose of this study is to identify some set of priority metrics that influence DevOps adoption in software organizations. The method adopted for this study is systematic literature review (SLR). We extracted 32 metrics from 57 articles identified through systematic literature review. These metrics can be used to evaluate DevOps maturity within organizations. We believe that this study will serve as the basis for the development of maturity models to implement DevOps practices in software organizations. The proposed maturity model will be based on these metrics.

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DO - 10.1063/5.0128883

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BT - Computational Intelligence and Network Security

A2 - Naik, K. Jairma

A2 - Chandrakar, Preeti

A2 - Sisodia, Dilip Singh

PB - American Institute of Physics Inc.

T2 - 1st International Conference on Computational Intelligence and Network Security 2022, ICCINS 2022

Y2 - 3 March 2022 through 4 March 2022

ER -

Systematic literature review of metrics for measuring devops success

Abstract

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