Real-Time Topology Modeling for Virtualized Transaction Monitoring
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems struggle to effectively model and visualize the complex interdependencies between virtualization, operating systems, and transaction processing in large-scale web applications, making it difficult to anticipate the impact of deployment changes and optimize performance.
Innovation Solution
A monitoring technology that deploys agents to detect and integrate virtualization, operating system, and transaction processing aspects, creating a real-time topological model of the computing infrastructure, enabling visualization and analysis of these interdependencies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple separate tools are used to monitor virtualization, operating systems, and application processes, then comprehensive monitoring coverage is achieved, but system complexity and difficulty of integration increase
Solution Approach 1:
The patent combines multiple separate monitoring tools into a single integrated topology discovery system that can monitor virtualization infrastructure, operating systems, and application processes simultaneously. The system unifies data collection from hypervisors, virtual machines, physical hosts, and application layers into one coherent topology model, eliminating the need for multiple separate tools and their associated integration complexities.
Solution Approach 2:
The monitoring system is designed with multi-functionality to handle diverse monitoring tasks across different layers of the computing stack. It can discover virtualization topology, track operating system instances, monitor application processes, and analyze interdependencies all through a single universal platform that adapts to various monitoring requirements without needing separate specialized tools.
2Loss of information
If detailed topology information is collected from all layers, then complete interdependency visualization is achieved, but data processing complexity and time requirements increase
Solution Approach 1:
The system performs preliminary topology discovery and mapping actions continuously in the background, maintaining an up-to-date topology model before changes occur. By proactively collecting and organizing topology information from all layers in advance, the system prepares the data structure so that when changes or analysis requests occur, the information is already processed and ready for immediate use, reducing real-time processing requirements.
Solution Approach 2:
The topology discovery process is segmented into distinct layers (virtualization layer, operating system layer, application layer) that can be processed independently and then integrated. This segmentation allows the system to collect detailed information from each layer separately using specialized collectors, process them through dedicated analysis routines, and combine the results into a unified topology model, improving overall processing efficiency.
3Measurement precision
If real-time topology updates are implemented, then current system state accuracy is improved, but computational resource consumption increases
Solution Approach 1:
The system implements periodic topology discovery and update cycles rather than continuous real-time monitoring. Topology collectors periodically query virtualization managers, hypervisors, and application layers to detect changes, and the topology model is updated only when changes are detected. This periodic approach maintains accurate topology information while significantly reducing computational resource consumption compared to continuous monitoring.
Solution Approach 2:
The system employs feedback mechanisms where topology collectors monitor for specific change events (such as VM creation, migration, or termination) and trigger updates only when changes are detected. This event-driven feedback approach ensures the topology model remains accurate by updating precisely when needed, rather than continuously consuming computational resources, while still providing near-real-time accuracy.
Data Source
AI summary
A system and method for real-time discovery and monitoring of multidimensional topology models describing structural aspects of applications and of computing infrastructure used to execute those applications is disclosed. Different types of agents are deployed to the monitored application execution infrastructure dedicated to capture specific topological aspects of the monitored system. Virtualization agents detect and monitor the virtualization structure of virtualized hardware used in the execution infrastructure, operating system agents deployed to individual operating systems monitor resource utilization, performance and communication of processes executed by the operating system and transaction agents deployed to processes participating in the execution of transactions, providing end-to-end transaction trace and monitoring data describing individual transaction executions. The monitoring and tracing data of the deployed agents contains correlation data that allows to create a topology model of the monitored system that integrates transaction execution, process execution and communication and virtualization related aspects.