Author(s): Premkumar Ganesan* and Geetesh Sanodia
The integration of Artificial Intelligence (AI) with DevOps offers a transformative approach to managing cloud-native infrastructures, addressing the increasing complexity and demands of modern software environments. This paper explores the deep technical aspects of how AI can enhance DevOps practices to create intelligent infrastructure management systems that optimize resource allocation and improve performance. Key AI techniques, including machine learning (ML), deep learning (DL), reinforcement learning (RL), and AI-driven automation, are examined for their role in enhancing infrastructure scalability, reliability, and efficiency. We also provide insights into how these techniques are applied to specific components of DevOps, such as continuous integration and delivery (CI/CD), infrastructure-as-code (IaC), and cloud management. By leveraging AI-driven insights, predictive analytics, and real-time automation, this framework responds to the challenges posed by dynamic cloud-native applications, ensuring efficient, resilient, and scalable cloud environments through automated decision-making and real-time data analysis.
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