A disk capacity prediction method based on historical monitoring data

Abstract

The invention discloses a method for predicting disc capacity based on historical monitoring datum and an apparatus for using the method. Based on the serializable feature of the historical monitoring datum of a disc, the disc capacity is predicted through disc polling monitoring and serializable disc capacity data storage and analytical processing to the historical monitoring datum of the disc and based on the analytical result of the datum, so the early warning that the disc capacity is about running out is solved; the problems like server downtime and discontinuous business application due to disc capacity fault are avoided; and further the utilization rate of the disc is maximized, thus reducing risk and resources waste due to insufficient disc capacity.

Description

technical field [0001] The invention relates to the fields of disk monitoring and disk capacity prediction, in particular to a disk capacity prediction method based on historical monitoring data. Background technique [0002] With the rapid development of Internet big data, large-scale data centers have become more and more necessary for the development of modern society. This brings great challenges to the difficulty of disk supervision in data centers. The disk supervision of a data center with PB-level storage is already very difficult, not to mention that under the current development trend, data centers with exabyte-level or even larger storage are gradually produce. For example, the monitoring of a data center with 1000PB storage cannot be satisfied by the traditional disk monitoring method. Some disks are idle for a long time, while other disk resources are exhausted, which further increases the cost of disks, that is, wastes resources, and prevents the storage of t...

AI Technical Summary

Problems solved by technology

For example, the monitoring of a data center with 1000PB storage cannot be satisfied by the traditional disk monitoring method. Some disks are idle for a long time, while other disk resources are exhausted, which further increases the cost of disks, that is, wastes resources, and prevents the storage of the entire data center from being fully and reasonably used.

The above challenges have brought great limitations to the disk usage efficiency of large-scale data centers, seriously affecting the further development of large-scale data center storage capacity, so designing a disk capacity prediction method based on historical monitoring data can effectively solve this problem, according to Capacity prediction data maintains and updates disk resources in a timely manner, enabling the data center to provide larger capacity storage

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