Partitioned Configuration Data Model for Enterprise Systems
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Solution Overview
Problem
Managing configuration data across multiple server systems becomes increasingly complex and resource-intensive as the number of servers and redundancy in data models grow, leading to inefficiencies in data collection and analysis.
Innovation Solution
A configuration management system employing a partitioned data model that breaks down large configuration schemas into logical subcomponents, allowing for hierarchical representation and incremental updates, enabling easier data collection and analysis by processing sub-models in parallel and storing data in a partitioned manner.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional modeling techniques are used to manage configuration data across multiple servers, then comprehensive configuration coverage is achieved, but the complexity of data management and processing time increase significantly
Solution Approach 1:
The patent divides the monolithic configuration data model into multiple independent sub-models, each representing a specific configuration aspect or server component. This segmentation allows administrators to manage and process individual sub-models separately, reducing overall complexity while maintaining complete configuration coverage across the enterprise infrastructure.
2Loss of information
If all configuration data is collected and analyzed from hundreds or thousands of servers, then comprehensive configuration analysis is achieved, but the time and resources required become prohibitive
Solution Approach 1:
By partitioning the configuration data model into sub-models, the system can collect and analyze configuration information in smaller, manageable units across multiple servers simultaneously. This enables parallel processing of configuration data, significantly reducing total collection time while preserving complete configuration information through the aggregation of all sub-models.
Solution Approach 2:
The patent enables incremental updates where only changed configuration elements are re-collected and re-analyzed rather than processing the entire configuration data set. This partial action approach maintains information completeness for changed elements while dramatically reducing the time and resources required for updates.
3Adaptability or versatility
If configuration data models include redundancy to handle diverse server functions, then adaptability to different server types is improved, but the size and complexity of the data model increases
Solution Approach 1:
The configuration data model is divided into specialized sub-models that can be selectively applied to different server types and functions. Each sub-model contains only the configuration elements relevant to its specific purpose, reducing overall data model size while maintaining adaptability through the combination of multiple targeted sub-models rather than one comprehensive monolithic model.
Data Source
AI summary
A configuration management system provides a partitioned data model for collecting and representing configuration information from a diverse set of sources to allow easier modeling of very large, highly redundant sets of enterprise configuration information. The system partitions large configuration schema into logical subcomponents that can be combined, shared, and reused. The system also partitions instantiated data models into logical sub-models that can be combined, shared, reused, and incrementally updated. Each product team can provide its own configuration schema, which allows the domain experts in a particular field to provide reusable models for their products. These models may include sub-models that allow reuse of selected portions of the configuration schema. When the system stores data related to each portion of the model, it stores the data in a partitioned manner that makes incremental updates of each component of the model more straightforward and less resource intensive.