Storage Entity Migration Impact Prediction via Shared Data Metrics

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Solution Overview

Problem

Conventional tools for storage administrators lack the necessary information for fully informed decision-making regarding the migration or management of storage entities in multi-array storage systems, particularly in terms of predicting the impact of data migration.

Innovation Solution

A method that collects data on storage characteristics from multiple storage entities, allowing administrators to select entities and providing a value indicative of the predicted impact of migration based on shared data between entities, enabling informed decision-making through graphical and textual representations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If conventional storage management tools are used, then the system is simple to operate, but the information provided is insufficient for informed decision-making regarding storage entity migration

Engineering Contradiction:

Improveinformation completeness for migration decisionsVSAvoidsystem complexity

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The system performs preliminary analysis of storage entity relationships and migration impacts before the administrator makes a decision. It pre-calculates shared data metrics, relationship scores, and potential consequences, presenting this information in advance to enable informed decision-making without adding operational complexity.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system introduces an intermediary analysis layer between the storage entities and the administrator. This intermediary component automatically computes relationship metrics, shared data correlations, and migration impact assessments, translating complex storage system data into actionable insights for the administrator.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Measurement precision

If detailed migration impact analysis is provided, then decision-making quality improves, but the time required for analysis increases

Engineering Contradiction:

Improvemigration impact prediction accuracyVSAvoidanalysis time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system pre-computes relationship metrics and shared data correlations between storage entities during normal operation, storing these results for rapid retrieval. When migration analysis is requested, the pre-calculated data is immediately available, providing accurate predictions without requiring time-consuming real-time analysis.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system replaces manual or sequential analysis methods with automated computational algorithms that rapidly calculate migration impacts. The use of automated scoring systems and relationship metrics substitutes time-intensive manual assessment with fast, precise computational evaluation.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS10482071B1Systems and methods for providing metrics for a plurality of storage entities of a multi-array data storage system

Publication Date: 2019.11.19 PURE STORAGE INC

AI summary

Methods for providing metrics for a plurality of storage entities of a multi-array data storage system are disclosed. As a part of a method, data representing storage characteristics from one or more storage entities is collected and a selection of a storage entity of the one or more storage entities is allowed. Responsive to the selection, a value is presented that is indicative of a predicted impact on the selected storage entity when data migration is performed. The predicted impact is determined based on the amount of shared data between the selected entity and at least one other storage entity.