Diagnostic Identifier Generation for Cloud Error Tracing
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Solution Overview
Problem
Debugging errors in computer programs, especially when multiple applications across different computing environments interact, is challenging due to compatibility issues and the complexity of preserving and analyzing stack trace data, especially in cloud computing environments where hardware is decoupled from developers.
Innovation Solution
Generating diagnostic identifiers based on stack trace data using hash operations to combine attribute information, allowing for comparison and determination of related events and processing flows in cloud computer systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If stack trace data is preserved for each application to trace errors, then error tracing capability is improved, but device complexity and analysis difficulty increase
Solution Approach 1:
The patent introduces diagnostic identifiers as intermediary elements that mediate between stack trace data and error analysis. These identifiers aggregate key diagnostic information from multiple applications into standardized markers, allowing analysts to trace errors across application boundaries without examining complete stack traces from each application, thus reducing analysis complexity while maintaining error tracing capability
Solution Approach 2:
The patent creates simplified copies of diagnostic information in the form of diagnostic identifiers that represent complex stack trace data. Instead of analyzing original stack traces directly, the system generates and analyzes these identifier copies, which contain essential diagnostic properties in a condensed, standardized format that reduces analysis burden
2Measurement precision
If diagnostic information from multiple applications is analyzed to identify errors, then error identification accuracy is improved, but loss of time increases
Solution Approach 1:
The patent extracts essential diagnostic properties from complex stack trace data and encapsulates them in diagnostic identifiers. By taking out only the critical information needed for error identification (such as key stack frames, error types, and contextual markers) and removing redundant details, the system maintains error identification accuracy while significantly reducing the time required to analyze diagnostic information from multiple applications
3Measurement precision
If detailed stack trace data is examined from each application, then diagnostic precision is improved, but ease of operation deteriorates
Solution Approach 1:
The patent merges diagnostic information from multiple applications into unified diagnostic identifiers that present a consolidated view of the error landscape. By combining scattered stack trace data into integrated identifier structures that show relationships between applications and errors, the system maintains diagnostic precision while improving ease of analysis through a unified interface
Data Source
AI summary
Techniques are described for determining diagnostic information (e.g., a diagnostic identifier) for one or more events related to operations performed in a cloud computer system. A diagnostic identifier may be generated based on diagnostic data corresponding to one or more attributes about an event. A computing operation may be performed to generate a code (e.g., a hash code) for each attribute in the diagnostic data. The generated code(s) may be combined to form a diagnostic identifier to identify the diagnostic data. A comparison may be performed by comparing each code in one diagnostic identifier to a code in another diagnostic identifier corresponding to an attribute for which the codes were generated. A measure of a match between the two identifiers may be determined using a result of the comparison. The measure of the match may enable tracing and analysis of one or more events occurring in the cloud computer system.