Endpoint Log Analysis for Managed Network Error Diagnosis
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Solution Overview
Problem
Conventional log file analysis systems face challenges in efficiently diagnosing and managing operational problems in network-connected computing devices due to issues like rapid log file deletion, overwhelming amounts of irrelevant data, and inconsistent logging policies across different operating systems, which can lead to delayed analysis and inaccurate data processing.
Innovation Solution
A method involving monitoring log files at managed network endpoints, where error log entries are identified, and relevant log entries are collected over specific time intervals before and after the error occurrence, filtered, and aggregated for analysis, enabling timely and accurate diagnosis and remediation of technical errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If log files are continuously monitored and analyzed in real-time, then diagnostic accuracy is improved, but system resource consumption and processing complexity increase
Solution Approach 1:
The patent segments the log analysis process into distinct phases: real-time error detection, selective log collection, and batch analysis. Only log entries containing errors or exceptions are captured and transmitted for analysis, while normal operation logs are filtered out. This segmentation reduces the volume of data processed and transmitted, lowering system complexity while maintaining diagnostic accuracy for problematic events.
Solution Approach 2:
The patent extracts only the relevant portion of log data - specifically error-containing entries - from the complete log file. By using pattern matching and error detection algorithms to identify and extract only problematic log entries, the system avoids processing the entire log file, thereby reducing computational complexity while preserving diagnostic accuracy for actual issues.
2Loss of information
If all log entries are collected and analyzed, then complete diagnostic information is obtained, but data processing time and computational resources increase
Solution Approach 1:
The patent extracts only error-containing log entries from the complete log file using pattern matching and error detection. This extraction process identifies and isolates only the diagnostically relevant portions of logs, eliminating the need to process thousands of normal operation entries. The result is significantly reduced analysis time while maintaining complete diagnostic information for actual problems.
Solution Approach 2:
The patent applies partial action by collecting and analyzing only the necessary portion of log data - error entries - rather than the complete log file. This selective approach processes a fraction of the total log volume while capturing all diagnostically relevant information, thereby reducing computational resources and analysis time without sacrificing diagnostic completeness.
3Quantity of substance
If log file size is maintained by deleting old entries, then storage space is conserved, but historical diagnostic data becomes unavailable
Solution Approach 1:
The patent extracts and transmits error-containing log entries to remote servers for archival storage. By identifying error entries through pattern matching and extracting them from local logs, the system preserves these diagnostically valuable historical records in centralized storage. This allows local devices to maintain limited storage space while ensuring historical diagnostic data remains accessible for future analysis and trend identification.
4Measurement precision
If comprehensive log collection is performed across multiple time intervals, then diagnostic accuracy is improved, but data volume and processing burden increase
Solution Approach 1:
The patent extracts only error-containing entries from log files collected across multiple time intervals. By using error detection algorithms and pattern matching to identify and extract only problematic log entries from each time period, the system maintains comprehensive temporal coverage for accurate diagnostics while reducing the total data volume to only diagnostically relevant information.
Solution Approach 2:
The patent applies partial action by collecting logs from multiple time intervals but processing only the error-containing portions. This approach captures sufficient temporal context for accurate diagnostic analysis while filtering out vast amounts of normal operation data, thereby maintaining diagnostic accuracy without proportionally increasing processing burden.
Data Source
AI summary
A method may include monitoring a log file at an endpoint of a managed network, and an error log entry that indicates a technical error experienced at the endpoint may be identified. The method may include ignoring the log entries that are generated during a first time period following identification of the error log entry. A first set of log entries may be collected during a first time interval beginning at the end of the first time period and going back a second time period. A second set of log entries may be collected during a second time interval beginning at the end of the first time period and moving forward for a third time period. The first and second sets of log entries may be aggregated, and a mitigation action determined based on analysis of the aggregated log entries may be implemented as a solution to the technical error.