Extensible Log Analysis Framework with Segmented Parsers
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Large distributed computing systems face challenges in analyzing diverse and complex log files due to the difficulty in creating and maintaining scripts, complexity in reusing script code, and the lack of a central component for configuration and management, especially when dealing with log files of varying formats and types.
Innovation Solution
An extensible event-driven log analysis framework that separates log parsing from log analysis, providing a core infrastructure for executing extensions and analyzers, allowing for the creation of reusable log analysis framework extensions and analyzers that can parse and analyze log files, including the use of state machines and complex algorithms, and enabling dynamic addition of components without recompilation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If scripts are created to analyze log files, then log analysis capability is provided, but the difficulty in creating and maintaining a large number of scripts increases
Solution Approach 1:
The system segments the log analysis functionality into separate parser components, each responsible for a specific log file type. This segmentation allows independent creation and maintenance of parsers without affecting other parts of the system, reducing overall complexity while maintaining versatility.
Solution Approach 2:
The framework provides a universal parser interface that can handle multiple log file types through different parser implementations. The core analysis engine remains universal and can work with any parser that adheres to the interface, enabling one analysis component to serve multiple log formats.
2Adaptability or versatility
If multiple scripts are used to analyze different log files, then diverse log file types can be processed, but the complexity in reusing script code across scripts increases
Solution Approach 1:
The framework establishes a universal parser interface that enables code reuse across different log file types. A single analysis component can be reused with multiple parsers by simply changing the parser implementation, eliminating the need to duplicate analysis logic for each log format.
Solution Approach 2:
The parser interface acts as an intermediary between the diverse log file formats and the unified analysis engine. This mediator layer allows the analysis code to remain generic and reusable while accommodating different log formats through the interface abstraction.
3Productivity
If parsers are created to extract information from log files, then log data can be analyzed, but the lack of a central component for configuration and management of parsers occurs
Solution Approach 1:
The framework merges the configuration and management of multiple parsers into a central configuration component. This central component provides unified control over parser selection, parameters, and coordination, simplifying management while maintaining high productivity in log data extraction.
Data Source
AI summary
A log analysis framework is provided that includes a core that is configured to support the execution of one or more extensions and one or more analyzers. The core provides a common infrastructure, base classes, and utilities for supporting the execution of the extensions and the analyzers. Extensions are software components configured to parse a log file and to trigger events based upon the contents of the log file. Analyzers are executable software components configured to consume events generated by the extensions, to analyze the events, and to generate a report based on the events.