Hypervisor Migration Analytics for Guest OS Settings
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Solution Overview
Problem
Current methods for migrating workloads between hypervisors lack a mechanism to map optimization settings, as there is no direct correspondence or standardization between the settings of different hypervisor utility suites, making manual migration error-prone and inefficient.
Innovation Solution
The implementation of an analytics-based system that detects correlations between guest OS optimization tool settings for different hypervisors, allowing for automatic configuration of settings during inter-hypervisor migration, using a local repository of correlation data and a centralized system to intelligently automate the migration process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual migration methods are used for transferring workloads between hypervisors, then flexibility and control are maintained, but migration efficiency decreases and error rates increase due to lack of automated mapping mechanisms
Solution Approach 1:
The patent introduces an intermediary mapping layer that translates between different hypervisor utility suite settings. This intermediary mechanism automatically correlates settings from source hypervisor to destination hypervisor, eliminating manual mapping while maintaining accuracy. The mapping layer acts as a mediator that handles the complexity internally, allowing efficient automated migration without requiring manual intervention in the complex setting correlations.
2Ease of operation
If no standardized mapping mechanism exists between different hypervisor utility suites, then each hypervisor maintains its own optimization settings, but migration becomes error-prone and time-consuming
Solution Approach 1:
The patent creates a universal mapping framework that works across multiple hypervisor platforms (VMware, Microsoft Hyper-V, Xen, KVM). This universal mechanism establishes standardized correlation rules that can translate settings between any supported hypervisor combinations. By implementing multi-functional mapping capabilities, the system ensures both ease of operation through automated translation and reliability through consistent, tested mapping rules across different hypervisor environments.
3Loss of time
If automated analytics-based migration is implemented, then migration speed and accuracy improve, but system complexity and infrastructure requirements increase
Solution Approach 1:
The patent implements preliminary action by pre-establishing correlation models and mapping rules between different hypervisor settings before migration occurs. The analytics system pre-analyzes the source and destination hypervisor configurations and prepares the mapping transformations in advance. This preliminary preparation reduces actual migration time significantly, as the complex analytics and mapping computations are performed beforehand rather than during the critical migration window.
Data Source
AI summary
Presented herein are embodiments for automating analytics-based migration of virtual machine optimization tool settings to different hypervisor environments. Currently, no marketplace workload migration utilities have previously dealt with this scenario. In one or more embodiments, a system gathers data and uses analytics on the data to devise one or more translation/correlation rules or models for virtual machine migration. In one or more embodiments, using historical manually settings, correlations can be determined. Given data about a source guest operating system (OS) tool settings, one or more translation/correlation models may be used to facilitate the translation of guest OS optimization tool settings from the source environment to the destination environment so that migrated virtual machine functions the same as or nearly the same as it did on the source hypervisor.