Non-invasive Time-based Profiling Tool for Networked Systems
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Solution Overview
Problem
Conventional debugging tools fail to provide comprehensive insights into the interaction between subsystems and the impact of application program execution on other machines, making it difficult to determine the root cause of problems in large networked systems.
Innovation Solution
A non-invasive time-based profiling tool that instruments subsystems to collect event reports, traces events, and correlates causation relationships across multiple machines, presenting a unified graphical user interface for developers to analyze system performance and debug issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple debugging tools are used to collect information from different subsystems and machines, then the quantity and diversity of collected information increases, but the complexity of manually analyzing and integrating this information increases
Solution Approach 1:
The patent combines information from multiple debugging tools and subsystems into a single unified profile view. The system integrates event reports from various subsystems (OS, network, disk, memory) and correlates them across multiple machines, presenting all this information in one cohesive interface rather than requiring developers to manually integrate separate tool outputs.
Solution Approach 2:
The profiling tool acts as an intermediary between multiple debugging tools and the developer. It collects data from various subsystems and machines, processes and correlates the information, then presents it in a unified manner, thereby reducing the manual analysis burden on developers.
2Reliability
If conventional debugging tools collect information from multiple machines and subsystems, then the comprehensiveness of system profiling improves, but the difficulty of determining root causes increases due to limited integration information
Solution Approach 1:
The system segments information by subsystem and machine, organizing event reports from different sources (OS events, network events, disk events, memory events) into structured categories. This segmentation allows comprehensive collection while maintaining organization, making root cause analysis more manageable through structured viewing and filtering capabilities.
Solution Approach 2:
The system provides feedback by correlating events across subsystems and machines to identify causation relationships. It highlights potential root causes by showing how events in one subsystem relate to events in other subsystems or on other machines, thereby assisting developers in determining root causes more effectively.
3Adaptability or versatility
If developers manually sieve through information from multiple debugging tools, then the flexibility in analyzing specific issues improves, but the time required for analysis increases
Solution Approach 1:
The system performs preliminary organization and correlation of information automatically. It pre-processes event reports from multiple subsystems and machines, establishing causal relationships and structuring the data before the developer needs to analyze it. This preliminary action reduces the time required for manual analysis while maintaining flexibility.
Solution Approach 2:
The unified profiling tool serves multiple functions: it collects information from various subsystems, correlates events across machines, identifies causation relationships, and presents integrated profiles. This multi-functionality eliminates the need for developers to manually integrate information from multiple separate tools, reducing analysis time while maintaining versatility.
Data Source
AI summary
A software execution profiling method comprising: collecting, from a plurality of subsystems of a client machine, information including an event report corresponding to each of a plurality of events occurring in the plurality of subsystems, each event report specifying an event identifier and a cause identifier; responsive to determining that the cause identifier includes an empty field, determining time values in the information associated with the first event and a second which caused the first event; determining to indicate a causation relationship between the first event and the second event in view of the time value of the second event being within the defined period of the time value of the first event; and presenting via a graphical user interface (GUI) the events and an indicator of the causation relationship.