Topology Models from Log Messages
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Tracking changes in the topology of computer systems is challenging due to frequent and major changes, making it difficult to generate and maintain accurate topology models for IT management.
Innovation Solution
Utilizing log messages collected from source components to generate topology models by identifying simultaneous parameter appearances across multiple components, calculating linkage scores, and determining topological linkages based on these scores.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If topology models are generated and maintained to track changes in computer system topology, then IT management capability is improved, but the difficulty of tracking changes increases due to frequent and major topology changes
Solution Approach 1:
The system automatically generates topology models by analyzing log messages from source components without requiring manual intervention. The topology model generation process is self-service, where the system autonomously identifies components, determines their relationships, and updates the topology model based on collected log data, thereby improving IT management capability while avoiding the complexity of manual topology tracking.
Solution Approach 2:
The patent replaces manual or mechanical topology tracking methods with an automated information processing system that analyzes log messages. Instead of physically tracking or manually recording topology changes, the system uses computational analysis of log data to infer topological relationships, substituting mechanical tracking with intelligent automated analysis.
2Measurement precision
If log messages are analyzed to generate topology models, then topology identification accuracy is improved, but computational overhead increases
Solution Approach 1:
The system extracts only the necessary information from log messages for topology model generation, rather than processing all log data. By identifying and extracting specific parameters and patterns relevant to topological relationships, the system achieves accurate topology identification while minimizing computational overhead by focusing only on essential data elements.
Solution Approach 2:
The system performs partial analysis of log messages, focusing on specific patterns and parameters that indicate topological relationships rather than analyzing every aspect of log data. This selective approach achieves sufficient topology identification accuracy without the excessive computational cost of complete log message analysis.
Data Source
AI summary
In some examples, a first pair of parameters in respective first and second log message streams associated with respective first and second source components and a second pair of parameters in the respective first and second log message streams may be identified. The first pair may be identical and the second pair may be identical. It may be determined that first pair of parameters was simultaneously generated and that the second pair of parameters was simultaneously generated in the first and in the second log message streams. A linkage score may be determined between the first and the second source components. The linkage score may be based on the determination that each of the respective first and the second pairs of parameters was simultaneously generated. It may be determined that that the first and second source components are topologically linked based on the linkage score.