Multi-Vendor Storage Dashboards for Standardized Data Management
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Solution Overview
Problem
Current data storage management systems fail to provide a unified interface for managing heterogeneous vendor storage systems, requiring specialized personnel to interpret varying data formats, leading to increased costs and delays in receiving critical information, and lack self-healing and end-to-end business process integration.
Innovation Solution
A management system with a data collection script, business logic script, and graphical user interface that standardizes data across multiple vendor systems, enabling a unified interface for monitoring and managing heterogeneous vendor storage systems, including self-healing capabilities and integration with ticketing tools.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a unified management interface is implemented for heterogeneous vendor storage systems, then ease of operation and management efficiency are improved, but device complexity and integration challenges increase
Solution Approach 1:
The patent introduces a management interface that acts as an intermediary layer between users and heterogeneous vendor storage systems. This interface standardizes data collection from multiple vendors into a common format, allowing unified monitoring and management without requiring users to understand vendor-specific complexities. The intermediary translates and normalizes data from different storage systems, resolving the contradiction by hiding integration complexity while providing ease of operation.
Solution Approach 2:
The patent applies homogeneity by standardizing the data format and structure across heterogeneous vendor storage systems. By converting vendor-specific storage parameters into a unified data model with consistent fields and formats, the system presents a homogeneous interface to users regardless of the underlying vendor diversity. This standardization enables simplified management while accommodating multiple vendor types.
2Measurement precision
If specialized personnel are used to interpret vendor-specific data formats, then measurement precision and data interpretation accuracy are improved, but loss of time and operational costs increase
Solution Approach 1:
The management interface performs self-service by automatically collecting, standardizing, and presenting storage data from multiple vendors in a unified format. Instead of requiring specialized personnel to manually interpret vendor-specific formats, the system autonomously handles data normalization and presents ready-to-analyze information. This eliminates the need for expert intervention while maintaining data accuracy, thereby reducing time delays and operational costs.
3Measurement precision
If vendor-specific custom solutions are used to access storage parameters, then measurement precision and vendor compatibility are improved, but adaptability and system versatility deteriorate
Solution Approach 1:
The management interface embodies universality by designing a standardized data model that can accommodate parameters from multiple vendor storage systems. The interface collects vendor-specific data using precise vendor-appropriate methods but then translates all data into a universal format with consistent field names, data types, and structures. This allows the same management interface to work with different vendors while maintaining both measurement precision and multi-vendor adaptability.
4Productivity
If manual data collection and interpretation processes are used, then ease of operation is maintained for simple systems, but productivity and management efficiency deteriorate for heterogeneous systems
Solution Approach 1:
The patent applies segmentation by dividing the data collection and management process into distinct modular components: vendor-specific data collection modules, a central standardization layer, and a unified presentation interface. Each vendor storage system is accessed through its own collection script that gathers data independently, then all data is routed through the standardization layer that applies uniform transformation rules. This segmented architecture enables automated high-throughput management of heterogeneous systems while keeping each component relatively simple and maintainable.
Data Source
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AI summary
A method for monitoring and managing heterogeneous vendor storage systems may include performing, by a management system, operations including: sending instructions to a vendor storage system among the heterogeneous vendor storage systems to cause the vendor storage system to generate a vendor answer file on the vendor storage system, sending instructions to the vendor storage system to copy vendor data from the generated vendor answer file to volatile memory of the management system, tracking and logging events associated with the copying of the vendor data, validating the copied vendor data based on the logged events, determining standardized reporting data from the validated vendor data in the volatile memory of the management system, saving the standardized reporting data in a data structure formatted for the heterogeneous vendor storage systems, receiving a user query regarding the saved standardized reporting data, and displaying the saved standardized reporting data in a user interface.