Log Analysis System for Computer Stability Remediation
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Solution Overview
Problem
Traditional security systems rely on structured event schemas to analyze log files, limiting their ability to assess computer stability issues in new or updated products, as they require pre-existing schema analysis, which is inflexible and inefficient.
Innovation Solution
A computer-implemented method that directly analyzes text within log lines using natural language processing and machine learning classifiers to identify stability problems without relying on pre-established event schemas, enabling the analysis of novel log lines and remediation of stability issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional event schema approaches are used to analyze log files, then structured data extraction is improved, but adaptability to new or updated products deteriorates
Solution Approach 1:
The patent replaces the mechanical schema-matching system with a machine learning-based natural language processing system. Instead of requiring pre-defined event schemas and manual parsing rules, the system uses trained ML models to automatically understand and extract information from log lines in any format, thereby maintaining measurement precision while achieving adaptability to new products.
Solution Approach 2:
The patent changes the fundamental parameter of log analysis from schema-based structured extraction to ML-based semantic understanding. By transforming the analysis approach from rigid pattern matching to flexible language modeling, the system maintains extraction precision while gaining the ability to adapt to new product log formats without reconfiguration.
2Measurement precision
If pre-established event schemas are required for log analysis, then analysis accuracy is improved, but productivity deteriorates due to constant schema updates
Solution Approach 1:
The patent implements a self-service system where the machine learning models automatically adapt to new log formats through continuous training on newly collected log data. The system eliminates the need for manual schema creation and updates by autonomously learning from examples, thereby maintaining high analysis accuracy while dramatically improving productivity by removing the manual maintenance burden.
Solution Approach 2:
The patent performs preliminary training of machine learning models on diverse log formats during the development phase, enabling the system to handle new product logs without requiring subsequent schema updates. This preliminary preparation allows the system to maintain accuracy across different products while avoiding the continuous productivity loss associated with manual schema maintenance.
3Loss of information
If schema-based log parsing is used, then information extraction from known formats is improved, but device complexity increases due to schema maintenance
Solution Approach 1:
The patent extracts the complexity of schema maintenance by removing the entire schema-based parsing infrastructure and replacing it with a unified machine learning approach. The ML models directly process raw log text without requiring intermediate schema definitions, thereby maintaining complete information extraction capability while eliminating the complex schema maintenance apparatus.
4Measurement precision
If manual schema creation is required for each product, then analysis precision is improved, but ease of operation deteriorates
Solution Approach 1:
The patent implements self-service by enabling the machine learning system to automatically adapt to new product log formats through continuous learning from collected log data. The system eliminates the need for manual schema creation and configuration by autonomously understanding new log structures, thereby maintaining high analysis precision while dramatically improving ease of operation by removing all manual setup requirements.
Data Source
AI summary
The disclosed computer-implemented method for remediating computer stability issues may include (i) determining that a device has experienced a computer stability problem, (ii) obtaining, from the device, one or more computer-generated log lines that potentially include information pertaining to a cause of the computer stability problem, (iii) directly analyzing text included within the computer-generated log lines, (iv) identifying information relating to the computer stability problem based on the direct analysis of the text, and (v) remediating the device to resolve the computer stability problem. Various other methods, systems, and computer-readable media are also disclosed.