Virtual Node Migration Using Accommodation Data
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Solution Overview
Problem
In computing environments with virtualization, efficiently managing the migration of data processing clusters across hosts is challenging, especially when resources such as storage are dynamic, as existing methods struggle to optimize resource allocation and quality of service.
Innovation Solution
A method is implemented where a management system monitors data processing clusters for migration criteria, such as latency and data throughput, and identifies suitable hosts based on accommodation data, allowing for the migration of virtual nodes from one host to another to maintain optimal resource utilization and quality of service.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If virtual nodes are deployed on host computing systems to increase resource efficiency, then resource utilization improves, but difficulties arise in assigning virtual nodes to hosts when storage resources are dynamic
Solution Approach 1:
The system continuously monitors accommodation data including storage resource availability, data accessibility metrics, and cluster performance to dynamically determine optimal host assignments. This feedback mechanism allows the system to adapt to changing storage resources and automatically reassign virtual nodes when migration criteria are satisfied, resolving the operational difficulty while maintaining high resource utilization
Solution Approach 2:
The patent implements dynamic migration criteria that evaluate multiple factors including data accessibility, storage resource availability, and cluster performance metrics. The system continuously updates accommodation data and reevaluates host assignments based on changing conditions, enabling flexible adaptation to dynamic storage resources while maintaining efficient resource utilization
2Productivity
If data processing clusters are migrated to optimize resource allocation, then resource allocation efficiency improves, but system complexity increases
Solution Approach 1:
The system performs self-service migration management by automatically monitoring accommodation data, evaluating migration criteria, selecting optimal target hosts, and executing cluster migrations without manual intervention. The management system handles the complexity of migration orchestration, host selection, and data accessibility evaluation internally, reducing the operational burden while maintaining efficient resource allocation
Solution Approach 2:
The system performs preliminary evaluation of migration criteria and accommodation data before executing migrations. By pre-assessing data accessibility metrics, storage resource availability, and potential target hosts, the system prepares migration plans in advance, reducing the complexity of actual migration execution and ensuring optimal resource allocation
3Reliability
If migration criteria are based on data accessibility metrics, then quality of service improves, but measurement and detection difficulty increases
Solution Approach 1:
The system introduces accommodation data as an intermediary metric that aggregates complex data accessibility measurements into manageable evaluation parameters. The management system collects raw data accessibility metrics from multiple sources, processes them through standardized evaluation criteria, and uses the resulting accommodation data to determine migration decisions, simplifying the measurement process while maintaining quality of service
Data Source
AI summary
Described herein are systems, methods, and software to migrate virtual nodes of a data processing cluster. In one implementation, a management system monitors an executing data processing cluster on one or more first hosts to determine when the data processing cluster satisfies migration criteria. Once satisfied, the management system selects one or more second hosts to support the data processing cluster based on accommodation data associated with the hosts. After selection, the management system may initiate operations to migrate the data processing cluster from the one or more first hosts to the one or more second hosts.