Ranking Target Server Partitions for Virtual Migration
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Solution Overview
Problem
Current virtual server migration technologies lack automated mechanisms for ranking target server partitions based on performance characteristics, leading to suboptimal migration decisions and manual intervention.
Innovation Solution
A computer-implemented method and system that analyzes the performance state of virtualized process collections and ranks target server partitions using a generic algorithm to ensure optimal migration based on scalability and performance metrics, enabling automated and dynamic migration within a data center.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated migration mechanism is implemented, then productivity is improved, but device complexity increases
Solution Approach 1:
The system performs self-service by automatically monitoring its own performance state and initiating migration decisions without external intervention. The performance state analysis unit continuously evaluates system metrics and the automated decision-making process enables the system to migrate workloads autonomously based on predefined policies, eliminating the need for manual operational intervention while maintaining manageable complexity through rule-based automation.
Solution Approach 2:
The system implements preliminary action by pre-establishing performance thresholds and migration policies before migration events occur. The performance state analysis unit continuously monitors system metrics against predefined thresholds, and the automated decision-making framework is prepared in advance to trigger migrations when conditions are met, enabling rapid automated response without ad-hoc decision-making complexity.
2Manufacturing precision
If performance state analysis is performed, then manufacturing precision is improved, but use of energy increases
Solution Approach 1:
The system applies parameter changes by dynamically adjusting the granularity and frequency of performance state analysis based on system conditions. The performance state analysis unit monitors key performance parameters and adapts its analysis depth according to workload characteristics and policy definitions, enabling precise migration decisions while modulating computational energy consumption to match actual system needs rather than performing constant high-granularity analysis.
Data Source
AI summary
A computer implemented method, data processing system, and computer program product for automated ranking of target server partitions based on current workload partition performance state. When a violation of a stack tier policy for the virtualized process collection in a source logical partition is detected, the stack tier comprising the virtualized process collection is examined to determine a scalability of the stack tier. A set of logical partitions are examined to identify target logical partitions for the migration event, wherein the target logical partitions are compatible for migrating the virtualized process collection based on the scalability of the stack tier. A performance state of the virtualized process collection is analyzed, and the target logical partitions for selection in the migration event are ranked based on the performance states of the virtualized process collection and the stack tier policy.