Microstep Workload Migration for User Comfort
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Solution Overview
Problem
Current workload migration strategies in IT systems fail to consider user comfort and criticality, leading to resistance and underutilization of resources in hyperscaler environments, resulting in increased hosting and support costs over time.
Innovation Solution
Implementing a microstep score system to progressively migrate workloads based on user amenability, which generates recommendations aligned with workload characteristics and updates safety scores to incrementally increase resource consumption and user comfort with technology changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If workload migration suggestions are implemented without considering user comfort, then resource utilization improves, but user resistance increases and adoption is impaired
Solution Approach 1:
The patent segments the workload migration process into multiple progressive steps rather than a single abrupt change. The system divides migration into incremental phases, allowing users to adapt gradually. Each step presents smaller, more manageable migration suggestions that build user confidence and comfort over time, ultimately achieving better resource utilization without overwhelming users.
Solution Approach 2:
The patent implements a dynamic recommendation system that adapts to user responses and feedback. The migration suggestions are not static but evolve based on user acceptance patterns, comfort levels, and previous interactions. The system dynamically adjusts the pace and scope of migration recommendations to match user adaptability, resolving the contradiction between pushing for resource optimization and respecting user comfort.
2Ease of operation
If IT personnel avoid introducing change where unnecessary, then user resistance is minimized, but resources in hyperscaler environments remain underutilized
Solution Approach 1:
The patent implements a feedback-driven system that continuously monitors user responses to migration suggestions and system resource utilization metrics. This feedback loop allows IT personnel to make informed decisions about when and how to introduce changes. The system provides data-driven insights into actual resource underutilization, enabling targeted migration initiatives that address real problems while minimizing unnecessary changes that would trigger user resistance.
Solution Approach 2:
The patent performs preliminary analysis and assessment before recommending workload migration. The system evaluates resource utilization patterns, identifies genuine underutilization cases, and assesses user comfort levels before proposing changes. This preliminary action ensures that migration suggestions are based on actual needs rather than assumptions, reducing unnecessary changes while still addressing real resource optimization opportunities.
3Productivity
If workload migration is implemented without considering criticality and relationship to human decision, then technical optimization is achieved, but implementation may be impaired or prevented
Solution Approach 1:
The patent applies different migration strategies and recommendation approaches based on the specific characteristics of each workload, including its criticality level and relationship to human decision-making processes. High-criticality workloads receive more cautious, well-justified migration suggestions with extensive impact analysis, while lower-criticality workloads can undergo more aggressive optimization. This localized approach ensures technical optimization is achieved while maintaining implementation success by adapting to each workload's unique context.
Data Source
AI summary
One example method includes discovering computing workloads that are available to migrate from a current platform to a target platform, and the workloads are controlled by a user, determining that the computing workloads are migratable from the current platform to the target platform, ordering the computing workloads according to a respective measurable aspect, such as SLA (Service Level Agreement) for example, of each of the computing workloads, and generating a recommendation to the user that one of the computing workloads be migrated to the target platform, and the recommendation is generated based on a microstep score that has been assigned to the user.