Leveraging Large Language Models for Intelligent Cloud Network Management

Abstract

The integration of large language models (LLMs) into cloud network management offers a transformative approach to optimizing network performance, enhancing fault detection, and ensuring efficient resource allocation. This paper explores the application of LLMs in intelligent cloud network management, focusing on their capabilities in real-time performance monitoring, predictive maintenance, dynamic scaling, and security enhancement. By leveraging the advanced natural language processing and analytical capabilities of LLMs, cloud networks can achieve higher reliability, scalability, and efficiency. The study highlights the benefits and challenges of deploying LLMs in cloud environments and presents case studies demonstrating their practical impact. This research aims to provide insights into the future of cloud network management, emphasizing the potential of LLMs to drive innovation and improve operational efficiency.