A bare device disaster recovery method, system, device and medium

Abstract

The invention discloses a bare device disaster recovery method, comprising the following steps: acquiring a virtual machine configuration file in a metadata management volume; determining the first identifier of the disk according to the path information of the disk recorded in the virtual machine configuration file character; acquire the second identifier of the disk in the metadata management volume according to the first identifier; start the corresponding virtual machine according to the data in the disk corresponding to the second identifier. The invention also discloses a system, computer equipment and readable storage medium. The solution proposed by the invention can adopt a disaster recovery solution after a computing device fails, and even if only storage devices are left, the user's virtual machine can be recovered from the disaster, which not only ensures the security of user data, but also provides high-performance disks for the customer's virtual machine.

Description

technical field [0001] The present invention relates to the field of disaster recovery, in particular to a bare device disaster recovery method, system, device and storage medium. Background technique [0002] In the cloud computing scenario, the storage methods include local storage, centralized storage and distributed storage; the traditional storage method is to format storage as a file system, and provide virtual disks for virtual machines through the file system. It depends on the file system, and can support more usage methods on the basis of the file system. However, in large-scale scenarios, the file system may be the performance bottleneck of storage. Therefore, with the raw device storage pool, the performance of the local disk is limited, so it is not in the optimization sequence, but centralized storage and distributed storage can exert multiple blocks. Therefore, with the improvement of storage performance, the file system will become a bottleneck. Therefore, t...

AI Technical Summary

Problems solved by technology

However, in large-scale scenarios, the file system may be the bottleneck of storage performance. Therefore, with a raw device storage pool, local disk performance is limited, so it is not in the optimization sequence. However, centralized storage and distributed storage can play multiple blocks Disk performance, so the file system will become a bottleneck under the improvement of storage performance, so use the raw device storage pool to bring out the performance of the raw device

However, there is no file system for buffering on the raw device storage pool, which cannot provide more functions

Although the storage end generally provides functions such as snapshots at this stage, there is limited support for functions such as disaster recovery.

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