Correlating Hypervisor and OS Data for VM Performance Diagnosis
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Solution Overview
Problem
Existing performance-monitoring tools for virtual machines struggle to correlate hypervisor data with operating system data, making it difficult to diagnose performance issues effectively, as hypervisors cannot obtain virtual-process performance parameters directly.
Innovation Solution
A performance-monitoring system that collects and correlates hypervisor data with operating system data for virtual machines using an event-based system like SPLUNK ENTERPRISE, enabling the storage and processing of massive quantities of minimally processed performance data for later analysis, allowing for flexible querying and visualization of both hypervisor and operating system metrics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If performance-monitoring tools only gather virtual-machine performance parameters from the hypervisor, then the system is simple to operate, but the measurement precision is insufficient to determine the root cause of performance problems
Solution Approach 1:
The patent introduces an intermediary component that collects performance parameters from both the hypervisor and the operating system within the virtual machine. This intermediary aggregates data from multiple sources (hypervisor-level VM parameters and OS-level virtual process parameters) and presents them in a correlated manner, enabling comprehensive performance analysis without requiring direct complex integration between monitoring tools and multiple data sources
Solution Approach 2:
The patent combines performance parameters from two distinct layers: the hypervisor layer (virtual-machine level) and the operating system layer (virtual process level). By merging these data sources into a unified performance monitoring system, the patent achieves comprehensive measurement precision while maintaining system manageability through integrated data presentation
2Measurement precision
If the system collects both virtual-machine performance parameters and virtual-process performance parameters, then the measurement precision improves, but the device complexity increases due to multiple data sources
Solution Approach 1:
The patent employs an intermediary data collection system that handles the complexity of gathering parameters from multiple sources (hypervisor and operating system). This intermediary layer abstracts the complexity away from the user, presenting correlated performance data in a unified manner while internally managing the intricate data collection and correlation processes
Solution Approach 2:
The performance monitoring system is designed with multi-functionality to handle diverse data sources. It can simultaneously collect, correlate, and present performance parameters from both the hypervisor and the operating system, making it a universal solution that addresses multiple monitoring needs through a single integrated system
3Ease of operation
If administrators use separate diagnostic tools for hypervisor and operating system data, then each tool can be optimized for its specific data source, but the ease of operation decreases due to difficulty in correlating data
Solution Approach 1:
The patent merges performance parameters from separate data sources (hypervisor and operating system) into a unified presentation. This allows administrators to view and analyze correlated performance information from both layers simultaneously, preventing information loss that would occur when using separate tools and maintaining ease of operation through integrated data display
Data Source
AI summary
During operation, the system obtains hypervisor data for a set of virtual machines, wherein the hypervisor data was received from one or more hypervisors while the set of virtual machines was running on the hypervisors. The system also obtains operating system data for the set of virtual machines, wherein the operating system data was received from a set of operating systems while the set of operating systems was running on the set of virtual machines. Next, the system correlates hypervisor data for a virtual machine with corresponding operating system data for the virtual machine. Finally, the system presents the correlated hypervisor data and operating system data for the virtual machine to a user.