Virtual Machine Migration Resource Limit Management
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Solution Overview
Problem
Current methods for virtual machine migration lack the ability to effectively manage and adjust the total amount of compute resources consumed by virtual machines during migration, often resulting in exceeding predefined resource limits, leading to inefficient and costly licensing agreements.
Innovation Solution
A system that assesses compute resource utilization, sets limits, and allocates resources on a target host to ensure that virtual machines migrate within defined limits, using natural language processing to extract licensing agreement details and manage resource allocation dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If virtual machines are migrated from source host to target host without resource limit management, then migration process is simple and fast, but compute resource consumption exceeds predefined limits leading to increased licensing costs
Solution Approach 1:
The system performs preliminary assessment of compute resource utilization on the source host before migration, and pre-configures resource allocation limits on the target host. This advance preparation ensures that migration can proceed efficiently while resource consumption remains controlled from the outset, preventing excessive licensing costs without sacrificing migration speed.
Solution Approach 2:
The system continuously monitors compute resource consumption during the migration process and dynamically adjusts resource allocation on the target host based on predefined limits. This feedback mechanism ensures that resource usage stays within acceptable boundaries while maintaining optimal migration performance, resolving the contradiction between migration speed and resource control.
2Quantity of substance
If compute resource allocation is dynamically adjusted during migration, then resource limits are maintained, but system complexity increases
Solution Approach 1:
The system implements automated self-service mechanisms where the migration management system automatically assesses source host resource utilization, calculates appropriate allocation limits, and configures target host resources without manual intervention. This automation maintains precise resource control while minimizing the operational complexity burden on administrators.
Solution Approach 2:
The system pre-configures resource allocation templates and limits based on historical data and licensing agreements before migration begins. This preliminary setup reduces the complexity of real-time dynamic adjustment during migration, as the system only needs to follow pre-established rules rather than making complex decisions on the fly.
3Quantity of substance
If resource allocation limits are enforced during migration, then licensing costs are optimized, but migration flexibility is reduced
Solution Approach 1:
The system implements dynamic resource allocation that adapts to migration needs within predefined budgetary constraints. Rather than rigid fixed limits, the system allows flexible adjustment of resource allocation during migration as long as the total consumption remains within the licensed capacity. This dynamic approach optimizes licensing costs while preserving necessary migration flexibility.
Solution Approach 2:
The system changes resource allocation parameters dynamically during migration based on actual workload requirements and available capacity, while maintaining the overall consumption within licensed limits. This allows the migration process to adapt to changing conditions without violating licensing agreements, balancing cost optimization with operational flexibility.
Data Source
AI summary
An embodiment generates a compute resource allocation limit parameter for controlling a total amount of compute resources consumed by a set of virtual machines over a combination of a source host environment and a target host environment. The embodiment adjusts an allocation of compute resources for the set of virtual machines according to the compute resource allocation limit parameter. The embodiment migrates the set of virtual machines from the source host environment to the target host environment.