AI-Augmented DevOps: The Future of Automated Security and Governance in Cloud Infrastructure
DOI:
https://doi.org/10.63282/3050-9262.IJAIDSML-V5I2P108Keywords:
AI-Augmented DevOps, Cloud Infrastructure, Security Automation, Governance, Machine Learning, Compliance Auditing, Vulnerability Management, Predictive AnalyticsAbstract
As cloud infrastructure has become an essential component of modern IT environments, the need for effective security and governance has grown exponentially. The integration of artificial intelligence (AI) into DevOps processes, commonly referred to as AI-Augmented DevOps, offers promising solutions to address these challenges. AI technologies, including machine learning and predictive analytics, enhance DevOps by automating key tasks such as security threat detection, vulnerability management, compliance auditing, and cost governance. This paper explores the potential of AI-Augmented DevOps in the automation of security and governance within cloud environments, focusing on how AI can streamline operations, reduce risks, and ensure compliance with regulatory standards. The benefits of AI in enhancing cloud security and governance are analyzed in the context of existing challenges such as data privacy, integration issues, and the need for human oversight. Furthermore, case studies of AI-powered DevOps implementations are discussed to provide practical insights into the real-world applications of these technologies. Finally, the paper examines the future of AI-Augmented DevOps and its impact on the evolution of cloud infrastructure, security, and governance practices
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