Current Volume 8
The contribution of intelligent software agents, artificial intelligence (AI), and machine learning (ML) in allowing totally automated DevOps pipelines for continuous delivery is investigated in this review paper. Organisations may automate important software development lifecycle activities—including code integration, testing, deployment, and monitoring—by combining artificial intelligence and machine learning technology. The study looks at the advantages of automation—that is, more efficiency, less time-to-market, better software quality, and proactive issue prediction and resolution capacity. Emphasising key technologies like predictive analytics, intelligent monitoring, and autonomous rollback systems, we show how they maximise DevOps practices. Furthermore covered in the paper are the difficulties integrating several technologies, controlling data quality, and guaranteeing scalability in automated pipelines. It offers chances to enhance cooperation among teams for operations, quality assurance, and development. In the end, our work emphasises how intelligent software agents may transform DevOps, boost output, and inspire software delivery innovation.
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IRE Journals:
Gireesh Kambala
"Intelligent Software Agents for Continuous Delivery: Leveraging AI and Machine Learning for Fully Automated DevOps Pipelines" Iconic Research And Engineering Journals Volume 8 Issue 1 2024 Page 662-670
IEEE:
Gireesh Kambala
"Intelligent Software Agents for Continuous Delivery: Leveraging AI and Machine Learning for Fully Automated DevOps Pipelines" Iconic Research And Engineering Journals, 8(1)