Storage performance prediction method and device

By executing performance prediction models on computer devices, predicting the storage performance of new services for storage devices running in different computing resource configurations solves the problem of degradation in storage performance when deploying new services, improving evaluation accuracy and reducing the risk of business interruption.

CN119718852APending Publication Date: 2025-03-28CHENGDU HUAWEI TECH CO LTD
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Patent Information

Application Number
CN202311287925.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2023-09-28
Publication Date
2025-03-28

AI Technical Summary

Technical Problem

When enterprises deploy new services to storage devices running on the current network, they often fail to support new services, resulting in sharp decline in storage performance or service interruption, and it is difficult for the prior art to accurately evaluate the storage performance of storage devices.

Method used

Provides a storage performance prediction method, through the computer device, to predict the storage performance of the target device using different computing resources to run new services. The method includes the user configuring business requirements, inputting a performance prediction model to obtain prediction results, and evaluating whether the target device can deploy new services.

Benefits of technology

Improves the accuracy of evaluating whether storage devices can deploy new services, reduces the risk of business interruption, and does not rely on manual experience, and is suitable for a variety of scenarios and storage systems.

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Abstract

The invention discloses a storage performance prediction method and device, and the method comprises the steps: obtaining a business demand inputted or selected by a user in a configuration interface, and the business demand comprises a feature parameter of a to-be-deployed business and a specification parameter of a target device used for deploying the business; the feature parameters of the business included in the acquired business demand and the number of computing resources used by the target equipment are used as input data of a performance prediction model, so that a prediction result output by the performance prediction model is obtained, and the prediction result is used for indicating the storage performance of the business operated by the target equipment; wherein the performance prediction model is used for predicting the storage performance of the target device running the service based on different numbers of computing resources.
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