Unified Storage Analysis for Wasted Space and Capacity Efficiency
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Solution Overview
Problem
Current Enterprise Storage Resource Management (SRM) solutions are inefficient in managing complex storage infrastructures, requiring separate tools for each component, leading to segregated reporting and manual provisioning tasks, resulting in underutilized IT resources and high administrative burdens due to the inability to proactively address storage capacity issues.
Innovation Solution
A system and method for correlated analysis of wasted space and capacity efficiency that consolidates data from various storage infrastructure components into a single 'wasted space pyramid' data structure, enabling automated corrective actions and proactive management by identifying unused logical storage devices and providing automated recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If separate SRM tools are used for each storage infrastructure component, then detailed monitoring and reporting for each component is achieved, but the complexity of correlation and overall view increases significantly
Solution Approach 1:
The patent combines multiple separate SRM tools into a single unified SRM system that monitors and reports on all storage infrastructure components (host servers, networks, storage subsystems) through one integrated platform, eliminating the need for administrators to manually correlate data from multiple separate tools
Solution Approach 2:
The unified SRM system performs multiple functions across different storage components simultaneously - it can monitor host server capacity, network capacity, storage subsystem capacity, and perform correlated analysis all through a single multi-functional tool rather than requiring separate specialized tools for each function
2Measurement precision
If manual capacity management tasks are performed, then detailed control and analysis are possible, but the time consumption and administrative burden increase significantly
Solution Approach 1:
The system automatically performs capacity analysis, generates reports, and provides recommendations without requiring manual intervention - it self-services the capacity management tasks by automatically collecting data from all components, analyzing correlations, and presenting unified reports, freeing administrators from time-consuming manual tasks
Solution Approach 2:
The system continuously monitors storage capacity metrics and provides automated feedback through unified reports and recommendations, enabling administrators to make informed decisions without manual analysis, thus reducing the time and effort required for capacity management while maintaining detailed analytical capabilities
3Extent of automation
If event-based automated actions are implemented, then response to critical events is automated, but proactive prevention capabilities are lost
Solution Approach 1:
The system performs preliminary analysis of capacity trends and correlations across multiple components to predict potential capacity issues before they become critical events, enabling proactive capacity management actions to be taken in advance rather than waiting for events to occur
Solution Approach 2:
The system continuously provides feedback on capacity utilization trends and correlations, enabling both automated event-based responses and proactive preventive actions based on predicted future capacity needs, thus maintaining high automation while reducing reaction time
Data Source
AI summary
A system and method for correlated analysis of wasted space and capacity efficiency in complex storage infrastructures are provided. The system and method of the illustrative embodiments bring together wasted space data from all areas and components of the storage infrastructure into a single set of reports correlating information from these various sources in the storage infrastructure. In addition, correlated analysis of this collected information is performed with regard to wasted space. Logical storage devices of the storage infrastructure which are unused by host systems may be identified and appropriate corrective actions may be automatically taken. Moreover, automated recommendations and other automated corrective actions may be taken based upon the correlated analysis of the correlated data collected from the various components of the storage infrastructure.