Storage Capacity Planning

Abstract

A system and methods for capacity planning of electronic systems storage are provided. Features include a non-invasive data discovery and collection mechanism, an adaptive grouping mechanism, a flexible analysis mechanism, predictive modeling and forecasting mechanisms, and a business metric and correlation mechanism. A discovery engine that ascertains the availability of collectable entities. A collection engine in turn gathers information from and about entities discovered by the discovery engine. A grouping module groups together entities according to parameters specified by the user. An analysis and forecasting module allows a user to create, modify and save forecast scenarios from which a model is generated by a modeling module. Correlations can be identified between specified key business metrics and historical data. Once a model has been created, a forecast is generated and can then be analyzed using Bold Freehand Extrapolation, time-series analysis, and business trend-based forecasting.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS [0001] This application claims the benefit of U.S. Provisional Application Ser. No. 60 / 772,280, filed on Feb. 9, 2006, which is incorporated by reference herein in its entirety.BACKGROUND OF THE INVENTION [0002] 1. Field of the Invention [0003] The present invention is directed generally to determining machine storage capacity requirements. In particular, the present invention relates to effective management of future storage capacity needs by tracking current and historical usage and utilization, facilitating a better understanding of existing storage usage and utilization, and enabling scenario planning for prediction of future storage requirements. [0004] 2. Description of the Related Art [0005] Storage usage in general is growing, and growing rapidly. Applications of all types consume ever-increasing amounts of storage, and the consequences of running out of storage—room for an application to store data—can be catastrophic. At a minimum th...

AI Technical Summary

Benefits of technology

[0014] To facilitate ease of deployment and eliminate the possibility of affecting the systems being measured, a system in accordance with the present invention does not require additional new tools persistently located, or resident on the entities from which data is gathered. And, since each customer's environment is different and changing, an adaptive grouping mechanism is provided that is flexible and can mirror the changing environment of the user.

[0015] To help the user achieve a thorough understanding of his environment and a model for its future needs, a flexible query methodology is also provided.

[0016] And, because a focus on obtaining information solely from the storage in question does not provide the level of detail nor an understanding of outside influences required to truly forecast needs in electronic storage, a system of the present invention therefore incorporates business level data in conjunction with the storage environment history to provide accurate levels of prediction and forecast.

Problems solved by technology

Applications of all types consume ever-increasing amounts of storage, and the consequences of running out of storage—room for an application to store data—can be catastrophic.

In a severe case the application will fail, which may, in turn, cause the associated business functions to fail.

Thus, businesses are forced to continually add storage and maintain a safety margin.

Yet the costs for storage must be taken into account—additional storage implies additional dollars.

A challenge, therefore, is to effectively balance the need for more storage with the need to control costs.

While the information gathered by these tools may be broad, they are basic monitoring and reporting tools, limited to providing information about current needs and data.

They provide some basic storage management capabilities, e.g. provisioning, but again, are limited to providing a view of current data only.

While they provide capacity information, they are specific to processor and / or network performance and, again, are limited to a current view.

In addition, conventional approaches lack flexible association mechanisms.

There is no method by which a user can group or associate items to facilitate additional planning and action.

There is a very limited ability, if any, for the user to freely query the tools data to gain information or analysis that is meaningful.

Their information basis is limited to technological data and does not take into account business metrics.

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