Log Content Modeling for Hybrid Cloud Log Retrieval
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Solution Overview
Problem
The exponential growth of log files in hybrid cloud environments has made log management, monitoring, collection, and analysis increasingly challenging due to complexity and the need for efficient retrieval of relevant logs.
Innovation Solution
A method that analyzes input content for similarity and fairness, using predefined weights for attributes and pattern analysis, to determine the best match among log records in an object library, ensuring unbiased presentation of logs to users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional log management methods are used, then all log records can be stored, but retrieval efficiency deteriorates due to exponential growth of log files
Solution Approach 1:
The patent segments the large volume of log records into structured formats with defined schemas, organizing them by type, source, and attributes. This segmentation enables efficient indexing and retrieval without sacrificing storage capacity, directly resolving the contradiction between storing all logs and retrieving them quickly.
Solution Approach 2:
The patent introduces an intermediary log management system that sits between log generation and log retrieval. This intermediary performs schema-based validation, normalization, and indexing, transforming raw logs into a structured format that enables fast retrieval while maintaining complete storage capability.
2Measurement precision
If comprehensive log analysis is performed, then log relevance improves, but processing complexity increases due to multiple analysis types
Solution Approach 1:
The patent performs preliminary actions by establishing log schemas and validation rules before actual log analysis occurs. This pre-configuration of data structures and analysis parameters simplifies subsequent processing while maintaining high relevance accuracy, as the framework is already in place to guide the analysis.
Solution Approach 2:
The patent changes parameters by transforming raw log data into structured formats with defined attributes and schemas. This parameter transformation enables systematic analysis across multiple dimensions (time, source, type, severity) without requiring complex ad-hoc processing for each analysis request.
3Manufacturing precision
If schema validation is enforced, then log data quality improves, but processing time increases due to validation overhead
Solution Approach 1:
The patent performs schema validation as a preliminary action during log ingestion, establishing data quality standards before logs enter the analysis pipeline. By validating schemas upfront rather than during each analysis operation, the system maintains high data quality while minimizing the impact on overall processing throughput.
Data Source
AI summary
A method, computer system, and a computer program product is provided for computer log management. In one embodiment, in response to receiving a log request from a user, an input content is analyzed and adjusted according to input contents and user's previous activities. A similarity analysis and a fairness analysis is performed to determine similarities between the input content, as adjusted, and a plurality of log records in an object library. The similarity analysis includes analyzing any patterns and attributes. The attributes have a dimension, and each dimension has a predefined weight (W). The fairness analysis ensures that one type of log is not favored over others. A best possible match is then determined, and one or more logs are presented to the user providing the best possible match.