IMPACT OF ARTIFICIAL INTELLIGENCE ON DEVOPS ENGINEERING

DevOps engineering has improved to a great extent the delivery of software and system performance through automation, continuous feedback, and cross-functional collaboration.However, as software systems see increased adoption of cloud-native architectures, microservices, and continuous deployment, the scope of operations undermines the effectiveness of traditional DevOps practices.In light of this, artificial intelligence has surfaced as an essential facilitator for DevOps practices. This article conducts reviews of why artificial intelligence is important in DevOps engineering. It does so by synthesizing existing literature on DevOps performance, AIOps, and AI-enabled IT operations, together with an analysis of AI-powered DevOps tools. A conceptual framework is developed to clarify the relationship between DevOps practices, artificial intelligence, and AIOps. In this framework, DevOps is taken as the foundation, while AIOps serves as the means by which artificial intelligence is woven into usual DevOps workflows. The later sections also look into how AI-powered tools operationalize different approaches throughout the DevOps lifecycle.The reviews highlight that artificial intelligence elevates DevOps workflows by extensively upgrading proactive and predictive system management.In parallel, the article points out some drawbacks connected to the data quality, model drift, explainability, and organizational readiness.This article sets up a well-defined understanding of how artificial intelligence extends DevOps engineering beyond basic automation.It merges theoretical points of view with functional suites of day-to-day DevOps tools.It shows how AI supports a shift toward more intelligent operational practices.These insights have relevance for both researchers and practitioners working in DevOps and software engineering.