Log-Based Resource Scoring Visualization for System Health
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Solution Overview
Problem
As system scale increases, the vast amount of log data becomes unmanageable for users to visually confirm, making it difficult to understand the health and reserve capacity of the system.
Innovation Solution
An information processing apparatus that extracts actual measurement values of system resources from log files, calculates scores based on these values and their upper limits, and generates visual representations of these scores to assess system health and reserve capacity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users visually check log data to determine system health, then system health assessment is possible, but the method becomes impractical when system scale increases and log data becomes enormous
Solution Approach 1:
The patent replaces the manual visual inspection method (mechanical human operation) with an automated computational system that extracts metrics from log files, calculates health scores, and generates visualizations. This substitution enables processing of enormous log data volumes that are impossible for human users to manually analyze while maintaining assessment accuracy.
2Loss of information
If log data collection is comprehensive to capture all system metrics, then measurement completeness is improved, but data volume becomes unmanageable for visual confirmation
Solution Approach 1:
The patent extracts only the essential and relevant metrics from the comprehensive log data through automated parsing and filtering. Instead of presenting all raw log data, the system extracts key performance indicators, error rates, and resource utilization metrics, thereby maintaining information completeness for health assessment while reducing the data volume to manageable visualizations.
Solution Approach 2:
The patent segments the enormous log data into structured metric categories (CPU usage, memory usage, error counts, response times, etc.) and processes each segment independently. This segmentation allows the system to handle large data volumes by breaking them into manageable units that can be analyzed and visualized separately, preventing information loss while maintaining operational feasibility.
3Measurement precision
If detailed log analysis is performed to identify trouble causes, then diagnostic accuracy is improved, but the complexity of processing enormous log data increases
Solution Approach 1:
The patent replaces complex manual log analysis with automated computational algorithms that parse, filter, and analyze log data systematically. The system uses structured query language (SQL) and pattern matching algorithms to identify trouble causes automatically, maintaining high diagnostic accuracy while reducing processing complexity compared to manual methods.
Solution Approach 2:
The patent transforms raw log data into standardized metric parameters with defined thresholds and weightings for health score calculation. By changing the data representation from unstructured text to structured numerical parameters, the system simplifies the analysis process while maintaining the ability to accurately identify trouble causes through quantitative comparison against threshold values.
Data Source
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AI summary
An information processing apparatus includes an extraction unit that extracts an actual measurement value of a resource used by a function included in a system from a log file acquired from the system a calculation unit that calculates a score of the function on a basis of the actual measurement value of the resource used by the function and an upper limit value of the resource available by the function and a score display unit that generates and displays information visualizing the score of the function.