System Dump Fingerprinting for Diagnostic Analysis
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Solution Overview
Problem
Analyzing system dump data for computer system failures is resource-intensive and time-consuming due to the large amount of data involved, requiring expert querying and strategic analysis.
Innovation Solution
A computer-implemented method and system that determines a fingerprint of the system dump to identify matching criteria, allowing user devices to access and analyze diagnostic data, record queries, and cache results for quicker access, facilitating collaborative analysis and reuse across teams.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If expert querying and strategic analysis are performed on system dump data, then diagnostic accuracy is improved, but resource consumption and analysis time increase
Solution Approach 1:
The system performs preliminary actions by automatically generating a fingerprint of the system dump that identifies the system model and dump type before analysis begins. This pre-processing enables quick identification and categorization of dumps, allowing experts to focus only on relevant data without time-consuming manual sorting and filtering.
Solution Approach 2:
The fingerprint serves as an intermediary mechanism between the raw system dump data and the expert analysis process. It acts as a mediator that summarizes complex dump characteristics into a concise identifier, enabling efficient matching against criteria and reducing the information overload that would otherwise require extensive expert querying.
2Reliability
If system dump data is collected and stored for analysis, then diagnostic capability is improved, but data volume and storage requirements increase
Solution Approach 1:
The system extracts only the essential identifying characteristics from the large system dump data to create a compact fingerprint. This extraction process retains the critical diagnostic capability while dramatically reducing the data volume that needs to be stored and managed, as only the fingerprint and metadata need to be retained rather than the entire dump.
Solution Approach 2:
Instead of storing and managing the complete system dump data, the system creates a simplified copy in the form of a fingerprint that captures the essential identification information. This copy enables diagnostic capability through efficient matching and retrieval while minimizing storage requirements compared to retaining the full original data.
3Measurement precision
If manual querying of system dump data is performed, then analysis depth is improved, but labor requirements and complexity increase
Solution Approach 1:
The system performs self-service by automatically generating fingerprints and enabling users to search for dumps based on criteria without requiring complex manual querying procedures. The fingerprint mechanism autonomously handles data identification and matching, reducing the operational complexity while allowing users to focus on high-value analysis tasks.
Solution Approach 2:
The system changes the parameter space from complex manual query parameters to simplified fingerprint-based identification. By transforming the search space into a fingerprint matching problem, the system reduces operational complexity while maintaining the ability to perform deep analysis through the fingerprint's comprehensive system characteristics.
4Adaptability or versatility
If system dumps are searched and analyzed without fingerprinting, then flexibility in querying is maintained, but search efficiency and data identification speed decrease
Solution Approach 1:
The system segments the system dump identification process into two parts: the fingerprint generation that captures essential characteristics, and the search criteria that allow flexible querying. This segmentation enables fast fingerprint-based matching while preserving querying flexibility through the ability to search by various dump characteristics encoded in the fingerprint.
Solution Approach 2:
The fingerprint serves a universal purpose that supports multiple functions: it identifies system models, categorizes dump types, enables fast searching, and maintains flexibility for various query criteria. This multi-functionality achieves both search efficiency and querying flexibility without requiring separate mechanisms for each function.
Data Source
AI summary
Technical solutions are described for analyzing a system dump. An example computer implemented method includes determining a fingerprint of the system dump, which identifies a model of the system and a type of the system dump. The method further includes receiving, from a first user device, a request to identify system dumps matching a set of system dump criteria and identifying the first user device based on the fingerprint of the system dump matching the set of system dump criteria specified, and sending access information of the system dump. The method also includes recording a query and its result as executed by the first user device against the system dump and sending, for receipt by a second user device, access information of the result of the query in the database, in response to the second user device requesting identification of system dumps matching said set of system dump criteria.