A method of server collaborative monitoring for large-scale cloud data centers

Abstract

The invention discloses a large-scale-cloud-data-center-oriented server cooperative monitoring method. The mode that servers sense and monitor each other replaces a monitoring mode of a centralized structure, the self-managing capacity of the servers is improved, the monitoring burden of the monitoring servers is effectively lowered, and performance bottlenecks and singe point failure risks are removed. A cooperative monitoring mechanism and a functional component are provided, and the working steps of the cooperative monitoring mechanism are given when data servers are added into a system and a single data server and a group of data servers lose efficacy. The method is used in a large-scale cloud data center, system response time is obviously shorter than the response time of a centralized monitoring mechanism, load balance is effectively achieved, low updating expenditure is achieved, and under the situations that the data servers lose efficacy in a discrete mode and in a group mode, all the data servers which lose efficacy can be detected effectively.

Description

technical field [0001] The present invention relates to the application field of information technology system management, in particular to a server collaborative monitoring method for large-scale cloud data centers. Background technique [0002] Based on the centrally constructed cloud data center, cloud computing provides users with dynamic, cost-effective, and elastically scalable computing, storage, and various information services, which has changed the system architecture and operation mode of the traditional information technology industry. great attention from academia and industry. Governments of major countries in the world and influential corporate organizations have built large-scale cloud data centers; Google, Baidu, IBM, Microsoft, Yahoo, Amazon, VMware, Salesforce, Huawei, etc. have all proposed their own cloud computing solutions; Facebook , YouTube, Taobao, Wanwang, Sina and other popular network systems are also based on cloud computing platforms. [0003...

AI Technical Summary

Problems solved by technology

However, in large-scale cloud data centers, it is obvious that the simple heartbeat mechanism cannot be used, because a large number of data servers send periodic heartbeat information to the monitoring server, which will bring a lot of additional network communication burden, and easily consume a large amount of monitoring server resources. system and network resources, causing system performance bottlenecks and monitoring server failures, resulting in effects similar to distributed denial-of-service attacks

[0005] In order to solve the above problems, the current method is to configure a monitoring server with high performance and high availability, supplemented by functional modules such as log recovery or dual-machine backup, which also increases the cost of the system and does not fundamentally Solve the problem

Images