Correlating Machine Health with Application Performance Metrics
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Solution Overview
Problem
Current monitoring methods for web-based applications lack the ability to effectively correlate application performance data with machine health data, making it difficult for administrators to understand the impact of machine health on application performance.
Innovation Solution
A system and method that collects and correlates application performance data and machine health data over a specific period, allowing users to view the correlation and identify the effects of machine health on application performance, involving an agent that monitors application performance and collects machine health data, which is then reported to users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If application performance monitoring is implemented using standard OS interfaces for CPU and memory usage, then basic performance metrics can be obtained, but the data remains out of context and does not reveal the actual effect on software performance
Solution Approach 1:
The patent combines application performance data with machine health data into a unified monitoring system. The agent collects both types of data and presents them in a correlated view, merging previously separate information streams to provide comprehensive performance context.
Solution Approach 2:
The patent introduces an intermediary layer (the monitoring agent and correlation system) that sits between the OS interfaces and the administrator. This intermediary correlates machine health data with application performance data, transforming raw metrics into meaningful performance context.
2Productivity
If distributed web services are expanded across multiple machines to improve service delivery, then web services can reach consumers faster, but the topology becomes more difficult to track and monitor
Solution Approach 1:
The patent creates a universal monitoring agent that can operate across multiple different machines and distributed system components. This single agent design provides multi-functional capabilities to collect and correlate data across the entire distributed topology, simplifying monitoring of complex expansions.
Solution Approach 2:
The patent implements a feedback mechanism where performance data and machine health data are continuously collected, correlated, and presented to administrators. This feedback loop enables real-time monitoring and tracking of distributed service performance across the expanding topology.
Data Source
AI summary
Application performance data and machine health are collected by a system. The system correlates the two data types to provide context as to how machine health affects the performance of an application. Performance data for an application, for example an application executing as part of a distributed business transaction, and health data for a machine which hosts the application are collected. The performance data and machine health data may be correlated for a particular period of time. The correlation may then be reported to a user. By viewing the correlation, a user may see when machine health was good and bad, and may identify the effects of the machine health on the performance of an application.