GitOps and AI-Driven Security: A Future-Proof Approach for Cloud Automation
DOI:
https://doi.org/10.63282/3050-9416.IJAIBDCMS-V3I3P106Keywords:
GitOps, AI-Driven Security, Cloud Automation, Machine Learning in Security, Infrastructure as Code (IaC), DevSecOps, Continuous Deployment, Threat Detection and ResponseAbstract
GitOps and AI-driven security have emerged as key enablers of efficient and secure cloud automation. GitOps, an operational model based on Git repositories as the source of truth for both application code and infrastructure, facilitates a streamlined and scalable approach to managing cloud resources. Meanwhile, AI-driven security enhances cloud environments by automating threat detection and response, utilizing machine learning and predictive analytics to prevent and mitigate risks. By combining these two approaches, organizations can ensure a secure and resilient infrastructure capable of adapting to the rapidly evolving security landscape. This paper explores the integration of GitOps and AI-driven security, highlighting the benefits, challenges, and future directions for cloud automation. We discuss how AI can enhance the security of GitOps workflows, improve the automation of security practices, and facilitate compliance. As cloud adoption grows and security threats become more sophisticated, the combination of GitOps and AI-driven security presents a future-proof solution for cloud automation that meets the demands of modern IT infrastructure
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