Design and implementation of multi-dimensional situational awareness system for cloud network environment

Abstract

With the rapid development of cloud computing, container cloud technology has become the mainstream deployment model, increasing network complexity and the need for real-time performance monitoring. Real-time monitoring of container network performance and accurately assessing network health are essential for ensuring efficient and stable service operation. To address these challenges, this study designs and implements a multidimensional situational awareness system for container cloud environments.

The system uses tools such as Kubernetes, Prometheus and Kube-OVN to monitor status, performance, resources and traffic in real time. This paper presents a comprehensive health assessment methodology to evaluate clusters, nodes, and Pods through weighted scores and various metrics. The model can be dynamically adapted to improve accuracy and reliability.

Experimental results show that the system performs well in terms of data collection efficiency, resource utilisation and stability. The health assessment method accurately reflects the actual state of the system. This study provides a reliable multi-dimensional situational awareness system that supports real-time monitoring and health assessment of container cloud environments to ensure efficient and secure operation.