Unified Performance Analysis Report for Application Troubleshooting
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Solution Overview
Problem
Performance management tools lack the ability to automatically identify the cause of application performance issues in distributed or Web-based applications, as they overwhelm users with vast amounts of metric data, requiring manual analysis and prior knowledge of application and service relationships.
Innovation Solution
A unified performance analysis report is generated, grouping software services by type, identifying and plotting performance metrics over time, with a service model mapping applications to infrastructure, and a service manager detecting service state changes to provide a graphical representation of metrics and service state indicators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If performance management tools collect comprehensive metric data from multiple sources, then the completeness of performance information is improved, but the complexity of data analysis increases
Solution Approach 1:
The patent segments the overwhelming metric data into organized groups based on service types (web servers, application servers, databases, etc.). Each service type has its metrics categorized and presented in a structured manner, making the data manageable and analyzable while preserving completeness.
Solution Approach 2:
The patent introduces an intermediary layer (the performance management tool with service model) that automatically correlates metrics from multiple sources to application performance issues. This intermediary processes and organizes the raw data, presenting only the most relevant information to users without requiring them to manually analyze all underlying metrics.
2Loss of information
If performance management tools present all collected metric data, then the completeness of information is improved, but the ease of operation deteriorates
Solution Approach 1:
The patent extracts and presents only the most relevant performance indicators and metrics that are directly related to the application performance problem. Instead of showing all collected data, it selectively displays the most useful information, making the tool easier to operate while maintaining information completeness for troubleshooting.
Solution Approach 2:
The patent applies local quality by customizing the presentation of metrics based on service type and relevance. Different service types (web servers, databases, etc.) have their specific metrics highlighted and organized according to their importance, allowing users to quickly focus on relevant information without being overwhelmed by unrelated data.
3Measurement precision
If performance management tools require manual analysis of metric data, then the measurement precision can be maintained, but the productivity decreases
Solution Approach 1:
The patent performs preliminary actions by automatically collecting, organizing, and correlating metric data before presenting it to users. The service model pre-processes the data, establishing relationships between metrics and application performance issues in advance, so users receive ready-analyzed information that maintains precision while eliminating manual analysis time.
Solution Approach 2:
The patent implements feedback mechanisms that automatically correlate metric changes with application performance states. The system continuously monitors metrics, compares them against performance thresholds, and provides feedback about potential issues, enabling users to quickly identify problems without manual analysis while maintaining measurement precision through automated correlation.
Data Source
AI summary
An improved method is provided for identifying a cause of a performance problem experienced by an application in a computing environment. To help a user find and isolate the problem quicker, the method proposes a unified performance analysis report that presents the most likely indicators of the source of the performance problem. The report presents performance metrics for the software services used by the application and charts the metric values over time since it is often the change in a metric that indicates a problem. Each metric chart should also include an indicator for the state of service for the application. This will help the user correlate metrics from multiple sources to the time period in which the application experienced a problem.