Leveraging AI-Enabled Cloud-Native Frameworks for Secure Resilient Enterprise Computing and Cyber Intelligence
DOI:
https://doi.org/10.15680/IJCTECE.2023.0606033Keywords:
Artificial intelligence, cloud-native computing, enterprise resilience, cybersecurity, machine learning, microservices, containerization, DevSecOps, intelligent automation, cloud security, adaptive infrastructureAbstract
The rapid evolution of digital enterprises has created an increasing demand for intelligent, scalable, and resilient technology ecosystems capable of addressing complex cybersecurity challenges, operational disruptions, and dynamic business requirements. AI-enabled cloud-native frameworks represent a transformative approach that integrates artificial intelligence, machine learning, automation, containerization, microservices, serverless architectures, and advanced security mechanisms to enhance enterprise agility and resilience. These frameworks enable organizations to develop adaptive infrastructures that can continuously monitor threats, predict failures, optimize resource utilization, and support rapid recovery from disruptions. This research explores the role of AI-driven cloud-native technologies in establishing secure and resilient enterprise environments. It examines how artificial intelligence enhances cloud-native security through automated threat detection, behavioral analytics, anomaly identification, and intelligent incident response while cloud-native principles improve scalability, portability, and operational efficiency. The study investigates architectural approaches, implementation strategies, security practices, and governance models required for successful adoption. A qualitative research methodology based on extensive analysis of academic literature, industry frameworks, and enterprise technology practices is applied to evaluate the effectiveness of AI-enabled cloud-native ecosystems. The findings indicate that organizations integrating AI capabilities with cloud-native architectures can achieve improved cybersecurity posture, operational continuity, and business adaptability. However, challenges related to data governance, model transparency, integration complexity, and regulatory compliance must be effectively managed. The research highlights the importance of adopting holistic frameworks that combine artificial intelligence, cloud engineering, and cybersecurity principles to build future-ready resilient enterprises
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