Bare equipment disaster tolerance method, system and equipment and medium

Abstract

The invention discloses a bare equipment disaster tolerance method. The method comprises the following steps of obtaining a virtual machine configuration file in a metadata management volume; determining a first identifier of the disk according to path information of the disk recorded in the virtual machine configuration file; obtaining a second identifier of the disk in the metadata management volume according to the first identifier; and starting the corresponding virtual machine according to the data in the disk corresponding to the second identifier. The invention further discloses a system, computer equipment and a readable storage medium. The method is advantaged in that through the disaster recovery scheme after the computing equipment fails, disaster recovery can further be carriedout on the virtual machine of the user even if only the storage equipment is left, so data security of the user is ensured, and a high-performance disk can be provided for the client 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, storage methods include local storage, centralized storage, and distributed storage; the traditional method is to format the storage as a file system, and provide virtual disks for virtual machines through the file system, but this scenario It depends on the file system, and more usage methods can be supported on the basis of the file system. 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 The performance of the disk, so the file system will become a bottleneck under the improvement of storag...

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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