Sustainable Optimization of the CI/DC Cycle through Artificial Intelligence: An Efficient and Green Approach to DevOps Practices

This article discusses the impact of artificial intelligence (AI) on optimizing the continuous integration and delivery (CI/CD) cycle, with an emphasis on sustainable and green practices in DevOps environments. As demands for software increase, so does the energy consumption of technology infrastructures. This study proposes an AI-based approach to improve operational efficiency and reduce the carbon footprint in DevOps environments, integrating predictive models, intelligent automation, and sustainability metrics. A quantitative methodology was applied through experimentation in continuous integration environments, evaluating energy consumption, performance and deployment time. The results show that the implementation of AI can reduce the energy consumption of the CI/DC cycle by up to 25%. This research contributes to the development of greener and more resilient software engineering.

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Publication Details

Journal
International Journal of Environmental Sciences
Published
2025-05-23
DOI
https://doi.org/10.64252/prggan54
Primary Topic
Advancements in Semiconductor Devices and Circuit Design
Type
article
Field-Weighted Citation Impact
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article

Sustainable Optimization of the CI/DC Cycle through Artificial Intelligence: An Efficient and Green Approach to DevOps Practices

William Emmanuel Castillo Ortega
International Journal of Environmental Sciences
Advancements in Semiconductor Devices and Circuit Design
article

Sustainable Optimization of the CI/DC Cycle through Artificial Intelligence: An Efficient and Green Approach to DevOps Practices

William Emmanuel Castillo Ortega
article en

Abstract

This article discusses the impact of artificial intelligence (AI) on optimizing the continuous integration and delivery (CI/CD) cycle, with an emphasis on sustainable and green practices in DevOps environments. As demands for software increase, so does the energy consumption of technology infrastructures. This study proposes an AI-based approach to improve operational efficiency and reduce the carbon footprint in DevOps environments, integrating predictive models, intelligent automation, and sustainability metrics. A quantitative methodology was applied through experimentation in continuous integration environments, evaluating energy consumption, performance and deployment time. The results show that the implementation of AI can reduce the energy consumption of the CI/DC cycle by up to 25%. This research contributes to the development of greener and more resilient software engineering.

International Journal of Environmental SciencesVol. 11(6s)
Openalex Percentile: Top 86%
Advancements in Semiconductor Devices and Circuit Design
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Sustainable Optimization of the CI/DC Cycle through Artificial Intelligence: An Efficient and Green Approach to DevOps Practices — William Emmanuel Castillo Ortega · International Journal of Environmental Sciences (2025) | TGRS Research Map | TGRS