Automated Error Log Analysis Engine for Root Cause Identification
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Solution Overview
Problem
Current methods for analyzing error logs are time-consuming and costly, often requiring repeated analysis to identify and correct recurring errors, as the cause and solution of errors are not effectively linked or remembered.
Innovation Solution
An automated system that parses error log data into a standardized format, links it to previous errors, and uses a self-learning mechanism to improve matching accuracy, allowing users to customize matching criteria for more precise identification of root causes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated tests are used to generate error logs, then testing efficiency is improved, but error analysis time and cost increase
Solution Approach 1:
The system performs preliminary actions by automatically parsing error logs, comparing them against a database of known errors, and generating preliminary analysis results before human reviewers need to examine the logs. This preprocessing step reduces the time human analysts spend on each error log by handling routine comparison tasks in advance.
Solution Approach 2:
The patent introduces an intermediary automated analysis system that acts as a mediator between error log generation and human analysis. This intermediary system parses logs, compares them to known errors, and provides preliminary findings to human analysts, thereby reducing their workload and analysis time while maintaining thoroughness.
2Measurement precision
If manual error log analysis is performed, then error causes can be identified, but the same errors re-occur multiple times requiring repeated analysis
Solution Approach 1:
The system implements feedback by automatically comparing new error logs against a growing database of previously analyzed errors. When matches are found, the system retrieves and presents the original analysis and solution, preventing repeated analysis of the same error types and enabling continuous improvement through accumulated knowledge.
Solution Approach 2:
The patent uses copying by creating and maintaining a database of copied error patterns and their analyses. When a new error log is received, the system copies relevant information from matching historical errors to provide immediate analysis, eliminating the need to re-analyze identical errors from scratch.
3Adaptability or versatility
If error logs are analyzed without standardization, then various error formats can be handled, but searching and comparison become difficult
Solution Approach 1:
The system applies segmentation by breaking down error logs into standardized components or fields during parsing. This segmentation allows the system to handle various error formats by normalizing them into consistent structural elements, making subsequent searching and comparison operations efficient and reliable.
Solution Approach 2:
The patent implements parameter changes by transforming error logs from their original varied formats into a standardized format with consistent parameters and fields. This parameter standardization enables efficient searching and comparison while maintaining the ability to handle diverse error sources through the parsing stage.
Data Source
AI summary
Test results can be analyzed and linked using an automated system. In a first embodiment, an error log can be received including log data associated with an error. The log data can be parsed to transform it into a standardized format to allow for easier searching and comparison. Once standardized, an automatic comparison can be made between the parsed log data and previous errors obtained from error logs. If a match is found between the parsed log data and a previous error, then the parsed log data can be linked to the previous error so as to generate a relationship between the two.