Event Analysis System for Distributed Error Diagnosis
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Solution Overview
Problem
In distributed environments, diagnosing errors in systems requires collaboration among multiple teams with different expertise, and existing methods are inefficient in correlating log files from multiple sources to identify root causes of errors.
Innovation Solution
An event analysis system that develops a knowledge base of dependency relationships and valid event patterns to identify the root cause of errors by comparing log files with these patterns, tracing dependencies through a hierarchical structure, and presenting non-matching events for error analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If log files from multiple sources are combined and analyzed manually by multiple teams, then comprehensive error diagnosis is achieved, but the process becomes time-consuming and inefficient
Solution Approach 1:
The patent segments the error diagnosis process into distinct automated components: log file collection from multiple sources, dependency relationship extraction, event pattern matching, and root cause identification. Each component handles a specific aspect of the analysis independently, enabling parallel processing and eliminating the need for manual multi-team collaboration while maintaining comprehensive diagnosis accuracy.
Solution Approach 2:
The patent introduces an intermediary automated analysis system that acts as a mediator between multiple log sources and the final error diagnosis. This intermediary automatically correlates events across different log files, identifies dependency relationships, and pinpoints root causes without requiring human teams to manually integrate information from multiple sources.
2Measurement precision
If manual multi-team collaboration is used for error diagnosis, then comprehensive analysis of complex distributed systems is achieved, but the complexity of the diagnostic process increases
Solution Approach 1:
The patent creates a universal automated diagnostic system that performs multiple functions: collecting logs from diverse sources, parsing different log formats, extracting dependency relationships, matching event patterns, and identifying root causes. This single multi-functional system replaces the need for multiple specialized teams, reducing process complexity while maintaining comprehensive analysis capability.
Solution Approach 2:
The patent implements feedback mechanisms where the automated system continuously learns from analyzed log patterns and refines its dependency relationship models. The system uses feedback from event pattern matching results to improve future root cause identification accuracy, creating a self-improving diagnostic process that reduces complexity over time.
3Productivity
If automated event pattern matching is implemented, then error analysis efficiency is improved, but the initial setup and knowledge base development become more complex
Solution Approach 1:
The patent applies preliminary action by pre-defining valid event patterns and dependency relationships in the knowledge base before actual error diagnosis occurs. These patterns are established in advance based on system architecture and operational knowledge, enabling rapid automated matching during error analysis without requiring complex real-time reasoning, thus improving efficiency while managing setup complexity.
Data Source
AI summary
Operations include identifying an error generated by a primary operation. The event analysis system may determine that the primary operation depends on one or more lower-level operations. The event analysis system compares a log file, for the lower-level operation, to a valid event pattern for the lower-level operation. If the event analysis system identifies one or more events in the log file for the lower-level operation which do not match the valid event pattern for the lower-level operation, then the event analysis system presents or selects the set of events, in the log file for the lower-level operation, for error analysis corresponding to the error generated by the primary operation.