一种基于Hadoop的云运维监控模型设计与实现

随着企业信息化在生产实时监测、海量存储和科学分析决策等方面的需求不断提升,运维监控系统已逐渐成为主要的管理手段。采用最新的云计算技术,设计及搭建一个数据规模易扩展、处理速度快、安全性高、成本低的云运维监控系统;针对运维控制系统中海量监控历史数据实时提取响应速度慢的缺点,设计并实现一种基于Hadoop的分布式海量数据处理模型。仿真实验证明,Hadoop在对云监控系统中的海量数据提取效率优于传统方法,随着数据量的快速增长,优势越明显。

Design and Implementation of Cloud Operation and Maintenance Monitoring Model Based on Hadoop

With the rising of enterprise informatization demands in the production of real-time monitoring, massive storage and scientific analysis and decision, the operation and maintenance monitoring systems have gradually become the main management tools. By using the latest cloud computing technology, this paper designs and builds a cloud operation and maintenance monito- ring system, which is easy to expand for data scale, quick for processing speed, high for security, and low for cost. And in the light of the shortcomings of slow response to the real-time extraction of massive and historical monitoring data in operation and ma- intenance control system, the paper designs and implements a distributed massive data processing model based on Hadoop. Simu- lation experiments show that the massive data extraction efficiency of the cloud monitoring system based on Hadoop is superior to traditional methods, and the advantage is more obvious with the rapid growth of the amount of data.