Automated Incident Information Search Using Context Extraction
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Solution Overview
Problem
In server systems, identifying the cause of incidents and recovering services efficiently is hindered by the need for manual collection, indexing, and analysis of machine data, which is time-consuming and labor-intensive, especially in complex systems with large amounts of data and limited context information.
Innovation Solution
A computer-implemented method that extracts context information from incident tickets, determines relevant machine data sources, and uses keyword searches to automatically find information related to the incident, reducing the need for manual intervention and improving efficiency in complex systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If manual collection, indexing, and analysis of machine data is performed, then comprehensive incident information can be obtained, but the process becomes time-consuming and labor-intensive
Solution Approach 1:
The system performs preliminary indexing of machine data with metadata tags before incidents occur. When an incident happens, the already-indexed data can be quickly retrieved using keyword matching, eliminating the need for manual collection and analysis during the incident response.
Solution Approach 2:
The patent replaces manual mechanical processes (human collectors physically gathering and analyzing logs) with an automated computer-based system that uses keyword matching and metadata filtering to automatically retrieve and present relevant incident information.
2Measurement precision
If manual collection, indexing, and analysis of machine data is performed, then accurate incident cause identification is possible, but the process becomes labor-intensive
Solution Approach 1:
The system performs self-service by automatically retrieving, filtering, and presenting relevant incident information without requiring manual intervention. The automated keyword matching and metadata filtering processes replace human analysts while maintaining accurate incident cause identification.
3Loss of information
If comprehensive machine data is searched manually, then relevant incident information can be found, but the process is inefficient in complex systems with large amounts of data
Solution Approach 1:
The patent segments the large volume of machine data into organized collections with metadata tags (source, type, time range, component). This segmentation allows the system to efficiently search only relevant portions of data using keyword matching, rather than manually reviewing all data in complex systems.
Solution Approach 2:
The system replaces inefficient manual searching through large data volumes with automated computer-based keyword matching and metadata filtering, dramatically improving incident response efficiency in complex systems with extensive machine data.
Data Source
AI summary
Computer-implemented method for searching for information related to an incident generated in a server system, a system and a computer program product. The method includes extracting context information from a current ticket describing the incident, the context information including a first expression describing a symptom of the incident and indicating at least one component of the server system associated with the symptom; determining a data source which generates data in which the information related to the incident is to be searched for at least according to the at least one component; and using the first expression describing the symptom and a second different expression describing the symptom as keywords to search for the information related to the incident in the data.