Transaction Metrics Collection via Tree Data Structures
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Solution Overview
Problem
Existing software monitoring techniques incur substantial overhead costs and inefficiencies due to the inefficient communication of transaction trace data between agents and managers in computing environments.
Innovation Solution
A tree data structure is used to represent sequences of invoked components, allowing agents to efficiently report metrics by indexing static and dynamic data, and synchronizing tree data structures across agents and managers to reduce redundant data transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional transaction trace data communication methods are used between agents and managers, then complete monitoring data can be obtained, but substantial overhead costs and inefficiencies occur due to redundant data transmission
Solution Approach 1:
The patent extracts and transmits only the essential metric data from the transaction trace information, separating the critical performance metrics from the complete transaction trace data. This allows managers to obtain the necessary monitoring information without receiving redundant detailed trace data, thereby reducing communication overhead and improving monitoring efficiency while maintaining complete visibility into application performance.
2Loss of information
If detailed transaction trace data is transmitted from agents to managers, then comprehensive monitoring information is available, but data transmission redundancy increases substantially
Solution Approach 1:
The system extracts only the essential metric data representing transaction performance from the complete transaction trace information. By identifying and transmitting only the critical performance metrics rather than all detailed trace data, the patent eliminates data transmission redundancy while preserving the completeness of monitoring information needed for effective application management.
3Reliability
If agents report all component invocation details to managers, then complete transaction context is captured, but communication overhead and processing burden increase
Solution Approach 1:
The patent extracts and reports only the essential metric data that captures the critical transaction context and performance information. By filtering out unnecessary detailed component invocation information and transmitting only the extracted performance metrics, the system maintains accurate transaction context for monitoring and management while significantly reducing communication overhead and simplifying the communication architecture between agents and managers.
Data Source
AI summary
Transaction-segregated metrics are obtained for component invocations of different transactions of an application. Corresponding tree data structures are maintained by an agent and a manager which describe sequences of invoked components of the different transactions. The start and end of each component are each represented by a node in each branch of the tree data structure. Each transaction is identified by matching a branch to a transaction trace. Gatherers are linked to one or more nodes to collect the transaction-segregated metrics. For example, metrics can be gathered separately for component invocations in different transactions. Metrics can also be gathered together for instances of different components in one or more transactions. A user interface includes a directed graph having vertices connected by edges. Edge portions are visually distinguished from one another based on the metrics of the gatherers. Each edge portion can be associated with one or more of the gatherers.