Application Chain Monitoring With Resource Saturation Correlation
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Solution Overview
Problem
Current IT infrastructure monitoring solutions fail to link resource saturation with application performance issues, leading to delayed problem identification and failure to meet service level agreements (SLAs) for IT departments.
Innovation Solution
A system with consumption probes that monitor and report resource usage levels across an application chain, establishing thresholds and intervals for acceptable performance, and implementing an alert mechanism to detect and prevent performance degradations by correlating measurements between servers and applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional IT infrastructure monitoring solutions are used, then resource saturation can be diagnosed, but the link between resource saturation and application performance cannot be established
Solution Approach 1:
The monitoring system is segmented into multiple specialized components: consumption probes for resource metrics, application performance monitors for service level metrics, and a correlation engine. This segmentation allows each component to focus on specific data collection while the correlation engine establishes the links between them, resolving the information loss problem.
Solution Approach 2:
A correlation engine acts as an intermediary component that receives data from both infrastructure monitoring tools and application performance monitors. This intermediary correlates the data to establish the link between resource saturation and application performance, preventing information loss and enabling precise measurement.
2Reliability
If monitoring is not implemented on the infrastructure, then intervention can be avoided, but problem origin cannot be identified when quality of service thresholds are violated
Solution Approach 1:
The monitoring system is designed with multi-functional components that serve multiple purposes. The same consumption probes and correlation engine used for detailed problem analysis can also provide high-level service level agreement compliance reporting, reducing the need for separate monitoring systems and managing complexity.
Solution Approach 2:
The system automatically correlates infrastructure metrics with application performance data and generates alerts when service level agreements are at risk of being violated. This self-service capability eliminates the need for manual monitoring and intervention, maintaining reliability while managing complexity through automation.
3Measurement precision
If detailed monitoring of all applications and resources is implemented, then precise problem identification is achieved, but system complexity and data processing load increase
Solution Approach 1:
The monitoring approach applies local quality by focusing detailed measurement precision only where needed - at the specific application-resource correlations that are actually problematic. The system identifies and monitors critical correlations rather than uniformly monitoring all possible combinations, reducing complexity while maintaining precision for relevant metrics.
Solution Approach 2:
The system dynamically adjusts monitoring parameters based on detected patterns and service level agreement requirements. When correlations show stable performance, monitoring intensity is reduced; when degradation is detected, the system increases measurement precision for affected areas, optimizing the balance between precision and complexity.
Data Source
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AI summary
The present invention relates to a system comprising at least one computer machine and software or code executable by the machine to implement a mechanism for monitoring the performance of applications in an application chain, the system comprising a computer hardware and software arrangement forming a measurement reference (1) allowing, on the one hand, the measurement by consumption probes installed on resources to measure resource usage levels of applications during periods of performance degradation of one or more application(s) in the application chain, and on the other hand, the storage, by application and by period of the application chain, in a memory (11) of these usage levels in the measurement reference (1);characterized in that the hardware and software arrangement of the system also allows: - establishing a usage reference (2) for the data of the measurement reference by defining and storing in at least one memory (21, 22, 23, 24), per resource and per application, acceptable performance thresholds (Smin, Sint, Smax) of the level of use of the measurement reference (1); - establishing a module for categorizing performance problems (3) according to the measurement reference (1) and usage reference (2); - and implementing an alert mechanism (4) when the monitoring mechanism detects a performance problem in one or more applications in the application chain or when the problem is resolved.