An elastically stretchable cloud computing monitoring platform

Abstract

The invention discloses an elastically stretchable cloud computing monitoring platform which comprises a management assembly, a root monitoring server and a sub-monitoring server, the management assembly and the root monitoring server are deployed on a platform control node, and the sub-monitoring server is deployed on any physical node which can be reached by a network. The management assembly isresponsible for managing the root monitoring server and the sub-monitoring servers and forwarding monitoring routes; the root monitoring server is responsible for platform service, control node monitoring, switch monitoring and sub-monitoring server monitoring; and the sub monitoring servers are responsible for monitoring the computing nodes and the virtual machines. According to the invention, the dynamic expansion of the monitoring server can be realized, so that the load monitoring capability is improved, the horizontal expansion can be carried out all the time without an upper limit, andthe monitoring requirements of existing cloud manufacturers are met. The monitoring servers can be dynamically added or reduced according to the scale of the cloud platform, so that the monitoring bottleneck problem of the existing cloud platform is solved.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to an elastically scalable cloud computing monitoring platform. Background technique [0002] In recent years, cloud computing has developed by leaps and bounds, and many cloud computing service providers and operators have emerged to provide continuous and stable cloud computing services for different users in various industries. The stability of cloud computing is a priority for all manufacturers. In order to ensure the stability and continuity of user business, monitoring is an integral part of the cloud computing platform. By monitoring the usage and performance of cloud computing resources, an alarm can be generated when the resource usage reaches the threshold, so that measures can be taken in advance to deal with it without affecting the user's business. [0003] At present, with the increasing scale of the cloud platform, there are more and more monitoring indicators. As...

AI Technical Summary

Problems solved by technology

[0003] At present, with the increasing scale of the cloud platform, there are more and more monitoring indicators. As a result, the load of the monitoring server and the data generated by the monitoring itself have become a bottleneck for the expansion of cloud vendors.

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