Volume Group Migration With Simulated Performance Limits
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Solution Overview
Problem
Conventional migration of volume groups across data storage systems is inefficient due to the lack of knowledge about how to size new data storage systems to host volume groups and the duration they should host them, leading to potential performance degradation and unmet performance requirements.
Innovation Solution
Simulate the placement of volume groups on potential target storage systems to determine performance limits and predict the duration they can host the volume groups without degradation, using performance metrics and AI-driven clustering algorithms to optimize placement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If volume groups are migrated across data storage systems to balance load or consolidate workloads, then operational efficiency is improved, but performance degradation occurs due to lack of knowledge about target system capacity and hosting duration
Solution Approach 1:
The system performs simulation of volume group placement on potential target storage systems before actual migration occurs. This preliminary action determines performance limits and predicts hosting duration, allowing administrators to make informed decisions about migration timing and target selection, thereby preventing performance degradation while maintaining operational efficiency
Solution Approach 2:
The system provides feedback to administrators through notifications that include predicted hosting duration and performance limit information. This feedback loop enables administrators to adjust migration strategies based on simulated performance data, ensuring that volume groups are migrated to appropriate targets at optimal times without compromising performance requirements
2Loss of time
If volume groups are migrated without simulation and performance prediction, then migration speed is improved, but placement efficiency deteriorates due to inefficient target selection
Solution Approach 1:
The system performs simulation and performance prediction as preliminary actions before actual migration. By determining performance limits and predicting hosting duration in advance, the system enables rapid, informed migration decisions that improve both migration speed and placement efficiency simultaneously
Solution Approach 2:
The system creates a simulated copy of the volume group placement scenario to evaluate performance characteristics without actual migration. This virtual simulation allows administrators to assess multiple potential targets quickly, improving placement efficiency while maintaining fast migration execution
Data Source
AI summary
A computer-implemented method (CIM), according to one embodiment, includes simulating placement of a volume group on a first potential target storage system, and determining a first performance limit for the first potential target storage system based on the simulating. The method further includes predicting a duration the first potential target storage system can host the volume group without performance degradation, based on the first performance limit, and outputting a notification to a customer device, where the notification includes an indication of the predicted duration. A computer program product (CPP), according to another embodiment, includes a set of one or more computer-readable storage media, and program instructions, collectively stored in the set of one or more storage media, for causing a processor set to perform the foregoing method.