Artificial Intelligence-Driven Optimization of DevOps and Cloud Infrastructure: A Comprehensive Review of Intelligent Automation, Predictive Analytics, and IT Service Management
Keywords:
Artificial Intelligence, DevOps, Cloud Computing, Predictive AnalyticsAbstract
The integration of artificial intelligence (AI) within software engineering paradigms has profoundly transformed operational processes, particularly in DevOps and cloud computing environments. This research article presents an extensive review of AI-driven DevOps frameworks, predictive analytics applications, and IT service management (ITSM) automation, synthesizing insights from recent empirical and theoretical studies. AI-empowered DevOps facilitates continuous integration and delivery (CI/CD), automates deployment workflows, and enhances system maintenance efficiency through intelligent decision-making mechanisms. Additionally, the utilization of AI in cloud infrastructure allows for multi-cloud orchestration, workload optimization, and cost reduction, underscoring the necessity of algorithmic governance and adaptive learning systems. Through rigorous literature analysis, this study identifies prevailing challenges in model explainability, risk assessment, and performance monitoring, highlighting opportunities for novel AI integration strategies. Furthermore, the paper explores the implications of AI-driven automation on organizational agility, service reliability, and predictive maintenance, situating these advancements within the broader context of digital transformation. By critically evaluating existing frameworks and methodologies, the research provides actionable insights for scholars, practitioners, and IT strategists seeking to harness AI for operational resilience, innovation, and competitive advantage. The findings demonstrate that while AI offers substantial potential for efficiency gains, careful consideration of ethical, interpretive, and infrastructural constraints is essential for sustainable implementation. This study serves as a reference point for developing scalable, intelligent, and accountable DevOps and cloud management systems, positioning AI as an indispensable catalyst in modern software engineering.
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