Cluster website management system based on cloud computing

Abstract

The invention relates to the technical field of cloud computing, and discloses a cluster website management system based on cloud computing, which comprises a cloud server and a plurality of local physical terminals connected with the cloud server; the cloud server is internally provided with a central server, and a cloud database, a resource collector, a resource pool, a cloud resource monitoring module, a resource scheduling module and a work queue distribution module which are respectively connected with the central server; a microprocessor, and a communication module, a local resource monitoring module and a local resource distribution module which are connected with the microprocessor are respectively arranged in the plurality of local physical terminals, so that the resource optimization configuration of the cluster website is realized.

Description

technical field [0001] The invention relates to the technical field of cluster website management systems, in particular to a cluster website management system based on cloud computing. Background technique [0002] Clustered websites, also known as clustered websites and website clusters, refer to a collection of websites based on unified standards and unified technical framework, hierarchical management, hierarchical maintenance, high degree of coupling, and information that can be shared and presented based on specific permissions. The website cluster system is a multi-site architecture model that supports the generation of independent websites and multiple websites, and completes the construction of horizontally integrated and vertically integrated website groups for each website. The information between the main station, sub-sites, and websites can be shared and interconnected To put it simply, an enterprise / individual can self-build, maintain, update, and distribute li...

AI Technical Summary

Problems solved by technology

After all, the general company system does not change very frequently, but after the advent of the big data era, the number of temporary tasks has increased greatly. Today you need to run this user data, and tomorrow you need to count a report, back and forth temporary needs, and These requirements often require the use of a large number of machines, and manual processing by operation and maintenance is time-consuming, unrealistic, and error-prone.

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