Thread Performance Analysis in Continuous Integration Pipelines
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Solution Overview
Problem
Current distributed storage systems face challenges in efficiently monitoring and analyzing performance data across thread instances, particularly in identifying resource consumption differences after software updates, which can lead to performance degradation.
Innovation Solution
A method and apparatus that execute a first and second set of files, collect performance data, identify subsets corresponding to thread instances, calculate a score indicating resource consumption differences, and generate debugging messages based on these differences, ensuring that threads with the same entry function or opcode are compared for resource utilization analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual instrumentation upgrades are performed to monitor performance data, then measurement precision is improved, but device complexity and time consumption increase
Solution Approach 1:
The system automatically collects performance data from thread instances without requiring manual instrumentation. The performance monitoring subsystem autonomously gathers data, identifies thread instances, and compares resource consumption, eliminating the need for manual setup and reducing instrumentation complexity while maintaining measurement precision.
Solution Approach 2:
The patent replaces manual instrumentation processes with an automated software-based performance monitoring subsystem. This subsystem uses programmatic methods to collect, process, and analyze performance data, substituting manual mechanical operations with automated computational processes that reduce complexity and time consumption.
2Measurement precision
If comprehensive performance data is collected from all thread instances, then measurement precision is improved, but loss of time increases due to processing large data volumes
Solution Approach 1:
The system extracts and identifies specific thread instances based on matching entry functions and opcodes from the updated file set. By selectively focusing on relevant thread instances rather than processing all possible data, the system maintains measurement precision for comparable threads while reducing the overall data volume that requires processing, thus minimizing time loss.
Solution Approach 2:
The performance data is segmented and organized by thread instance characteristics such as entry function and opcode. This segmentation allows the system to efficiently group and compare only relevant thread instances, reducing the computational burden of processing comprehensive data while maintaining accurate measurements for comparable threads.
3Productivity
If automated performance analysis is implemented, then productivity is improved, but device complexity increases due to additional monitoring subsystems
Solution Approach 1:
The performance monitoring subsystem is designed to perform multiple functions: collecting performance data, identifying thread instances by entry function and opcode, comparing resource consumption, and generating analysis results. This multi-functional approach consolidates what could be separate complex systems into a single unified subsystem, improving productivity while managing complexity through functional integration.
Data Source
AI summary
A method is provided comprising: executing a first set of files, and collecting a first set of performance data; updating the first set of files to produce a second set of files; executing the second set of files and collecting a second set of performance data; identifying a first subset of the first set of performance data; identifying a second subset of the first set of performance data; calculating a score based on the first subset and the second subset, the score indicating a difference in resource consumption between one or more first thread instances that are instantiated using the first set of files and one or more second thread instances that are instantiated using the second set of files; and generating and outputting a debugging message based on the score, wherein the first thread instances and the second thread instances have the same entry function and the same opcode.