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Review Papers | Computer Science and Information Technology | United States of America | Volume 12 Issue 7, July 2023
Role of ML and AI in DevOps Transformation
Abstract: The stream of DevOps has evolved as a set of practices that help organizations to deliver and operate software applications and services more rapidly, reliably, and efficiently on various infrastructures in different environments. DevOps practices generally include processes such as Continuous Integration, Continuous Delivery, Infrastructure Management, Configuration Management, Monitoring, Governance, Communication, and Collaboration. However, with the dynamically evolving business and technology landscape, the DevOps processes require a transformation. The transformation is driven by several factors like the evolution of cloud computing, increased availability of data, security aspects, growing complexity of applications, and speed and agility required by the digital world. The transformation of DevOps can be greatly enhanced with the help of Artificial Intelligence and Machine Learning concepts helping in addressing business challenges, operational challenges, and technology challenges. Organizations can make use of AI/ML models and techniques to address manual activities like risk management, root cause analysis, monitoring, and alerting. It can also enhance the other aspects of automation with the help of process optimization, maintaining a better sync with the technology stack, and making use of automated bots and virtual assistants. The result is informed decision - making, risk mitigation, and corrective actions. All of these lead to lower costs and better effort utilization. This article dives into the various aspects where AI/ML influences and impacts the DevOps transformation into next - generation solutions.
Keywords: DevOps, Machine Learning, Artificial Intelligence, DevOps Transformation, Automation, Operational Efficiency
Edition: Volume 12 Issue 7, July 2023,
Pages: 1240 - 1243