Application Performance Signatures for Update Diagnostics
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Solution Overview
Problem
In multi-tier application architectures, it is challenging to efficiently diagnose performance changes and provide fast feedback on updated applications due to frequent software releases and varying workloads between testing and production environments, making thorough performance evaluation difficult.
Innovation Solution
The use of application signatures to analyze performance by comparing transaction latencies and service times across different components and tiers, allowing for quick detection of performance changes caused by updates or workload changes, and providing a model for normal application behavior for efficient capacity planning and debugging.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional performance evaluation methods are used for updated applications, then comprehensive performance analysis can be achieved, but the evaluation process becomes time-consuming and cannot provide fast feedback
Solution Approach 1:
The patent extracts the essential performance characteristics of applications into compact signatures that capture key performance metrics. By taking out only the critical performance attributes rather than analyzing all possible metrics, the system achieves fast performance comparison while maintaining evaluation thoroughness.
Solution Approach 2:
The patent transforms performance evaluation from analyzing raw performance data to comparing derived performance signatures. This parameter transformation enables efficient comparison of application versions by changing the evaluation parameters from detailed metric analysis to signature-based comparison.
2Measurement precision
If detailed performance analysis is performed across all application transactions, then accurate performance evaluation is achieved, but the complexity of analysis increases significantly
Solution Approach 1:
The patent segments the complex performance analysis task into distinct components: performance signature generation, signature comparison, and anomaly detection. By dividing the analysis into manageable segments, the system maintains evaluation accuracy while reducing overall analysis complexity.
Solution Approach 2:
The patent creates simplified copies of application performance characteristics in the form of performance signatures. These signatures are compact representations that preserve essential performance information while being much simpler to analyze than the full set of performance metrics.
3Reliability
If performance evaluation is conducted in production environment with varying workloads, then real-world performance assessment is achieved, but it becomes difficult to distinguish performance changes due to updates from those due to workload variations
Solution Approach 1:
The patent implements feedback mechanisms that continuously monitor performance signatures and compare them against baseline values. By providing feedback on performance deviations, the system can distinguish between expected variations and actual performance issues caused by updates.
Solution Approach 2:
The patent performs preliminary performance signature capture during baseline testing before deployment. This preliminary action establishes reference signatures that can be used to compare against production performance, enabling detection of update-induced changes even in varying workload conditions.
Data Source
AI summary
One embodiment is a method that determines application performance signatures occurring at an application server in a multi-tier architecture. The method then analyzes the application performance signatures to determine whether a change in transaction performance at the application server results from a modification to an application.