Log File Reduction via Problem Space Topology
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Solution Overview
Problem
In complex computing systems, troubleshooting system faults is challenging due to voluminous log files, where keyword searching often yields irrelevant results, making it difficult to pinpoint the source of the fault amidst a sea of irrelevant events.
Innovation Solution
A method and system for log file reduction based on problem space topology, which involves receiving a fault report, extracting relevant resources, filtering log files to a subset related to those resources, and displaying them for keyword searching, optionally including intermediate resources in the communications pathway.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If keyword searching is performed on all log files in the system, then comprehensive fault detection is possible, but the search becomes inefficient due to the voluminous amount of irrelevant log data
Solution Approach 1:
The patent segments the entire log file system into multiple subsets based on problem space topology. Each subset contains log files relevant to specific resources or components mentioned in the fault report. This segmentation allows the search to be confined to smaller, relevant portions of the log data rather than searching all log files system-wide, thereby maintaining comprehensive fault detection while significantly reducing search time.
Solution Approach 2:
The patent applies local quality by creating customized log file subsets tailored to each specific fault report. Instead of using a uniform search approach across all logs, the system selectively includes only those log files that are locally relevant to the particular resources, components, or problem areas mentioned in the fault report, thereby optimizing search efficiency for each specific troubleshooting scenario.
2Loss of information
If all log files are presented for review, then complete information is available for analysis, but the volume of data makes it difficult to identify relevant fault information
Solution Approach 1:
The patent extracts and presents only the relevant log files from the complete set of system logs. By analyzing the fault report to identify specific resources, components, or problem areas, the system extracts only those log files that contain information pertinent to the fault, excluding all irrelevant logs. This extraction process maintains complete fault information while dramatically improving analysis ease by eliminating distracting irrelevant data.
3Speed
If traditional database indexing is used for log file management, then fast access and keyword searching are enabled, but irrelevant log entries still dominate the search results
Solution Approach 1:
The patent performs preliminary action by pre-filtering and organizing log files into problem-space-specific subsets before the actual keyword search is executed. By using the fault report to pre-identify which log files are relevant to the specific fault scenario, the system prepares the search environment in advance, ensuring that when keyword searching is performed, it operates only on the pre-selected relevant subset rather than the entire log repository, thus reducing the quantity of search results while maintaining fast access speed.
Data Source
AI summary
Embodiments of the invention provide a method, system and computer program product for log file reduction according to problem space topology. A method for log file reduction according to problem space topology can include receiving a fault report for a fault in a solution executing in memory of one or more computers of a computer data processing system. The method further can include extracting references to at least two resources of the computer data processing system from the fault report. The method yet further can include filtering a set of all log files for the computer data processing system to only a subset of log files related to the at least two resources. Finally, the method can include displaying the subset of log files in a log file analyzer.