The Synergistic Impact of Artificial Intelligence on DevOps: A Comprehensive Review

Authors

  • Kowshik Sakinala Trine University, USA Author

DOI:

https://doi.org/10.32628/CSEIT251112343

Keywords:

AI-Assisted DevOps, Predictive Pipeline Management, DevSecOps, Human-AI Collaboration, Automated Code Generation

Abstract

This article explores the transformative impact of Artificial Intelligence (AI) on DevOps practices, examining how AI-driven innovations are revolutionizing software development and operations. It delves into key areas where AI is making significant contributions, including AI-assisted development, predictive pipeline management, and enhanced security measures. The article discusses how AI-powered tools are augmenting human capabilities in coding, automating workflow management, and providing real-time threat detection and remediation. Through case studies in the financial services and e-commerce sectors, the article illustrates the real-world applications and benefits of AI integration in DevOps. It also addresses the challenges and limitations of AI adoption, such as potential biases and the need for continuous learning. The discussion concludes with an outlook on prospects, highlighting the evolving landscape of human-AI collaboration in DevOps and the potential for AI to take on more complex roles in software development processes. Overall, this comprehensive article review underscores the pivotal role of AI in driving efficiency, reliability, and innovation in modern software delivery practices, while emphasizing the continued importance of human expertise in guiding these technological advancements.

Downloads

Download data is not yet available.

References

Christof Ebert; Gorka Gallardo et al. (25 April 2016). DevOps. IEEE Software, 33(3), 94-100. https://ieeexplore.ieee.org/document/7458761

Eirini Kalliamvakou, GitHub. (May 21, 2024). "Research: quantifying GitHub Copilot's impact on developer productivity and happiness." GitHub Blog. https://github.blog/2022-09-07-research-quantifying-github-copilots-impact-on-developer-productivity-and-happiness/

Mario Rodriguez, GitHub. (2023). "Research: Quantifying GitHub Copilot’s impact on code quality." GitHub. https://github.blog/news-insights/research/research-quantifying-github-copilots-impact-on-code-quality/

Leonardo Leite, Carla Rocha, et al., (14 November 2019 ). A survey of DevOps concepts and challenges. ACM Computing Surveys, 52(6), 1-35. https://dl.acm.org/doi/10.1145/3359981

Ponemon Institute. (2019). "2019 Cost of a Data Breach Report." IBM Security. https://insights.integrity360.com/hubfs/2019-cost-of-a-data-breach-report-04_03025203USEN.pdf

Gartner. (2021). "Gartner Identifies Top Security and Risk Management Trends for 2021." Gartner. https://www.gartner.com/en/newsroom/press-releases/2021-03-23-gartner-identifies-top-security-and-risk-management-t

Nigel Kersten, Puppet. (July 20, 2021). "Top DevOps Trends: 2021 State of DevOps Report." Puppet. https://www.puppet.com/blog/devops-trends

Amazon Web Services. (2022). "Customer Success Stories." AWS. https://aws.amazon.com/solutions/case-studies/?customer-references-cards.sort-by=item.additionalFields.sortDate&customer-references-cards.sort-order=desc&awsf.customer-references-location=*all&awsf.customer-references-industry=*all&awsf.customer-references-use-case=*all&awsf.language=language%23english

GitLab. (2023). "The Role of AI in DevOps" https://about.gitlab.com/topics/devops/the-role-of-ai-in-devops/

Downloads

Published

25-02-2025

Issue

Section

Research Articles

How to Cite

The Synergistic Impact of Artificial Intelligence on DevOps: A Comprehensive Review. (2025). International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 11(1), 3498-3506. https://doi.org/10.32628/CSEIT251112343