Research on the monitoring framework of micro service cloud architecture system with extensible integration

Authors

  • Fei WU , FuCai LUO, Qian CHEN

Abstract

Due to the complexity of cloud platform architecture and the unpredictability of workload, cloud monitoring is of great significance to guarantee the high availability of cloud platform. The dynamic nature, diversity and huge scale of resources on cloud platform bring some difficulties to cloud platform monitoring. A scalable multi-level monitoring framework (SHMA) for cloud platform is studied and proposed. SHMA adopts micro-service architecture to build extensible and independent service components in the monitoring system, realizing the monitoring of application services, middleware and infrastructure resources at different levels of cloud platform. The information center in the micro-service cloud architecture system plays an important role in the speed and depth of information diffusion. This paper proposes for the first time a method based on friend graph, complete distribution and privacy protection to identify the backbone, and conducts experiments using Facebook data sets. Experimental results show that the proposed algorithm can accurately identify the k information centers of the micro-service cloud architecture system, and verify the effectiveness of the monitoring framework.

Published

2020-10-16

Issue

Section

Articles