Automated Log Parser Generation for Scalable Analytics

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Solution Overview

Problem

Conventional log analytics tools face challenges in efficiently collecting and analyzing log records from large-scale computing systems due to their inefficiencies in scaling, manual parser construction, and resource redundancy, requiring significant time and resources from skilled personnel.

Innovation Solution

A method and system that automatically constructs log parsers by identifying variable and non-variable parts within log data, generating regular expressions, and employing a cloud-based or SaaS-based architecture for scalable log analytics, allowing users to configure log collection without detailed knowledge of host locations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If conventional log analytics tools are used to collect and analyze log records from large-scale computing systems, then basic log analysis capability is provided, but the system cannot efficiently scale when posed with massive systems involving large numbers of computing systems and applications

Engineering Contradiction:
Improvelog analysis efficiencyVSAvoidsystem scalability
Core Design Contradiction:
ProductivityVSAdaptability or versatility

Solution Approach 1:

The patent implements a centralized log analytics platform that serves multiple computing systems and applications through a single unified system. The platform uses standardized parsers and analysis components that can handle diverse log formats from different sources, eliminating the need for separate per-host configurations and enabling the system to scale to handle massive numbers of systems efficiently

Inventive Principle:
Principle #6Universality (Multi-functionality)

2Reliability

If conventional per-host log analytics approach is used, then individual host log analysis is achieved, but extensive redundant processing and resource usage occurs due to inability to share resources and analysis components

Engineering Contradiction:
Improvelog analysis accuracyVSAvoidredundant resource usage
Core Design Contradiction:
ReliabilityVSLoss of energy

Solution Approach 1:

The patent merges individual host log analysis capabilities into a centralized platform where multiple hosts share common resources including parsers, analysis algorithms, and processing infrastructure. This consolidation eliminates redundant processing that occurs when each host maintains separate analysis capabilities, reducing overall resource consumption while maintaining analysis accuracy through shared expertise

Inventive Principle:
Principle #5Merging (Combining)

3Manufacturing precision

If log parsers are manually constructed by skilled personnel, then accurate log parsing is achieved, but significant time and resources are required to build and maintain parsers

Engineering Contradiction:
Improveparser construction accuracyVSAvoidparser development time
Core Design Contradiction:
Manufacturing precisionVSLoss of time

Solution Approach 1:

The patent implements automatic parser generation capabilities that allow the system to create and maintain its own parsing components without requiring continuous manual intervention from skilled personnel. The system can automatically adapt to new log formats, generate appropriate parsers, and maintain them as systems evolve, significantly reducing the time and expert resources needed compared to manual construction approaches

Inventive Principle:
Principle #25Self-service

Data Source

PatentEP3278243B1Method and system for implementing a log parser in a log analytics system
Publication Date: 2024.07.31 ORACLE INT CORP
  • EP3278243B1 patent drawingFigure 1A
  • EP3278243B1 patent drawingFigure 1B
  • EP3278243B1 patent drawingFigure 2

AI summary

Disclosed is a system, method, and computer program product for implementing a log analytics method and system that can configure, collect, and analyze log records in an efficient manner. An improved approach has been described to automatically generate a log parser by analysis of the line content of a log. In addition, an efficient approach has been described to extract key-value content from the log content.