Resource Database for Instrumentation Data Management
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Solution Overview
Problem
Current information handling systems face scalability issues and performance blocks due to high memory utilization and complexity when managing instrumentation data, particularly as more management interfaces request access to devices, which hinders interoperability and requires extensive troubleshooting.
Innovation Solution
A method for managing instrumentation data involves receiving requests from a resource management interface, retrieving data from a resource database, identifying and converting the data into a schema associated with the interface, and transmitting it, using an event manager to update data upon change events, and storing it in a database with multiple data tables in formats like CMPI or SQL, ensuring efficient data representation and access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a lightweight server is used to direct access to managed elements, then memory utilization is reduced, but performance blocks occur and scalability is limited due to restrictions on parallel requests
Solution Approach 1:
The system segments the data access architecture by introducing a resource database that stores instrumentation data separately from the management interfaces. This allows multiple management interfaces to access the same data simultaneously without blocking each other, as each interface can retrieve data from the database in parallel rather than queuing for access to a single lightweight server.
Solution Approach 2:
The resource database acts as an intermediary between management interfaces and managed elements. Instead of management interfaces directly accessing managed elements through a lightweight server, they access the resource database which contains pre-retrieved instrumentation data. This intermediary layer enables parallel access while reducing the load on any single component.
2Device complexity
If instrumentation data is retrieved through the instrumentation layer using a lightweight server, then system complexity is reduced, but latency increases and computational power requirements increase
Solution Approach 1:
The system performs preliminary action by pre-retrieving and storing instrumentation data in the resource database before it is actually needed. The instrumentation layer retrieves data from managed elements and stores it in the database in advance, so when management interfaces need the data, it is already available in the database, eliminating the need for real-time retrieval through the instrumentation layer and reducing latency.
3Adaptability or versatility
If schema conversion is performed for each management interface request, then interoperability is enhanced, but computational power requirements and processing time increase
Solution Approach 1:
The system applies local quality by storing instrumentation data in multiple schema formats within the resource database. Different portions of the same data are maintained in different schemas (e.g., XML, JSON, CSV) to match the specific requirements of different management interfaces. This allows each interface to access data in its preferred format without requiring real-time conversion, reducing computational overhead while maintaining interoperability.
Data Source
AI summary
Methods, systems, and computer programs encoded on computer storage medium, for receiving a request for instrumentation data describing one or more devices in the computing environment, the request received from a resource management interface; retrieving the instrumentation data describing the one or more devices from a resource database; identifying a schema associated with the resource management interface; converting the instrumentation data describing the one or more devices based on the identified schema associated with the resource management interface; and transmitting the instrumentation data describing the one or more devices to the resource management interface.


