A data center physical resource floating method

Abstract

The present invention provides a method for floating physical resources in a data center, which includes the following steps: use a network interface of all physical hosts in each computing cluster as a mirror network to connect to a mirror switch, and use other networks as a host network to connect to a host switch; in a computing cluster Select a physical host, set it as a mirror network startup, and clone the operating system of the physical host into a mirror template through the mirror network; save the switch configuration file of the network required by the computing cluster to the host switch to make a network configuration template; Restore the aforementioned mirror templates in batches to idle physical hosts in another computing cluster through the mirroring network; load the aforementioned network configuration templates to the host switch of the computing cluster to which the idle physical hosts belong. Physical resources can be quickly and elastically scaled among computing clusters in batches to achieve the floating effect of physical resources, thereby improving resource utilization.

Description

technical field [0001] The invention relates to the field of IT, in particular to a method for floating data center physical resources. Background technique [0002] In recent years, the vigorous development of cloud computing technology has brought great changes to the entire IT industry. As the infrastructure of cloud computing and the innovation platform of next-generation network technology, the research on data center resources has become a hot spot in the academic and industrial circles in recent years. In the new application mode, there are multiple systems and cloud computing clusters in the data center. The traditional hierarchical data center network topology construction method is rigid, and there are many deficiencies in scale, scalability, utilization and cost, and cannot support multiple Rapid elastic scaling between computing clusters has been difficult to meet the growing demand for high performance, high cost performance, and high utilization under the new ...

AI Technical Summary

Problems solved by technology

In the new application mode, there are multiple systems and cloud computing clusters in the data center. The traditional hierarchical data center network topology construction method is solidified, and there are many deficiencies in scale, scalability, utilization and cost, and cannot support multiple Rapid elastic scaling between computing clusters has been difficult to meet the growing demand for high performance, high cost performance, and high utilization under the new situation

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