Conditional Dynamic Software Instrumentation for Runtime Diagnostics
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Solution Overview
Problem
Existing software monitoring techniques face challenges in efficiently collecting performance data without over-instrumenting, which can impair application performance and lead to the omission of important data, making analysis and diagnosis difficult.
Innovation Solution
A method for conditional instrumentation that selectively instruments callable methods based on specific execution contexts, such as method calls and transaction data, allowing for targeted data collection only when certain conditions are met, thereby reducing overhead and improving diagnostic capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If comprehensive instrumentation of software components is applied, then complete performance data collection is achieved, but application performance is impaired and overhead costs increase
Solution Approach 1:
The patent applies local quality by instrumenting only specific methods and components that are relevant to the diagnostic question at hand, rather than uniformly instrumenting all software components. The system dynamically determines which methods to instrument based on the specific performance issue being investigated, applying instrumentation locally where needed while leaving other components uninstrumented to minimize overhead.
Solution Approach 2:
The patent implements partial action by collecting only the necessary performance data required for diagnosis rather than comprehensively instrumenting all components. The system performs selective instrumentation based on the specific diagnostic needs, avoiding excessive data collection that would impair application performance while still obtaining sufficient information for effective analysis.
2Productivity
If selective instrumentation of specific methods is applied, then overhead is reduced, but important performance data may be omitted
Solution Approach 1:
The patent applies dynamics by making the instrumentation configuration adaptive and changeable during runtime. The system can dynamically add or remove instrumentation based on the specific diagnostic needs that emerge during performance analysis. This dynamic approach allows the system to start with minimal instrumentation to maintain performance, then selectively add instrumentation for specific methods when diagnostic requirements demand it.
Solution Approach 2:
The patent implements feedback mechanisms where performance data from instrumented methods is continuously monitored and analyzed. Based on this feedback, the system can identify when additional instrumentation is needed for related called methods, and automatically adjust the instrumentation configuration accordingly. This feedback loop ensures that important performance data is not omitted while keeping overhead minimal.
3Measurement precision
If dynamic instrumentation is applied to diagnose performance issues, then diagnostic precision is improved, but system complexity increases
Solution Approach 1:
The patent applies segmentation by breaking down the instrumentation system into modular components that can be independently configured and managed. Each instrumented method can be controlled separately, and the system can selectively apply instrumentation to different parts of the software based on diagnostic needs. This segmentation reduces overall system complexity by allowing focused instrumentation rather than requiring a monolithic instrumentation approach.
Data Source
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AI summary
Techniques for analyzing software in which un-instrumented components can be discovered and conditionally instrumented during a runtime of the software. Initially, software such as an application can be configured with a baseline set of instrumented components such as methods. As the application runs, performance data gathered from the instrumentation may indicate that the performance of some methods is below expectations. To analyze this, any methods which are callable from a method at issue are discovered, such as by inspecting the byte code of loaded classes in a JAVA Virtual Machine (JVM). To limit and focus the diagnosis, the instrumentation which is added to the discovered components can be conditional, so that the instrumentation is executed only in a specified context. The context can involve, e.g., a specified sequence of components in which a discovered component is called, and/or transaction data in which a discovered component is called.