vProxy Health Ranking for Backup Reliability
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Solution Overview
Problem
Current virtualization environments lack a systematic approach to selecting healthy proxy VMs and virtualization hosts for backup and restore operations, often relying on random selection, which can impact performance and resource management.
Innovation Solution
A method that involves obtaining health data items for vProxies and virtualization hosts, performing clustering analysis to label them as high or low health, and conducting confidence analysis to rank them, providing a ranked list for entities requesting backup and restore operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If random selection is used to choose proxy VMs for backup operations, then device complexity is reduced, but reliability of backup operations deteriorates
Solution Approach 1:
The system performs preliminary health assessments and clustering analysis of proxy VMs before backup operations are initiated. Health scores are pre-calculated and stored, allowing the selection mechanism to simply retrieve and use pre-evaluated proxy candidates rather than performing complex real-time analysis during backup operations.
Solution Approach 2:
The patent replaces random selection (mechanical/simple system) with a health-based scoring and ranking system. The selection is driven by quantitative health metrics and confidence values rather than random chance, substituting a deterministic algorithmic approach for a stochastic one.
2Reliability
If health analysis and ranking systems are implemented for proxy selection, then reliability of backup operations is improved, but device complexity increases
Solution Approach 1:
The selection process is segmented into distinct components: health data collection, clustering analysis, confidence calculation, and ranking. Each component handles a specific aspect of the selection process, making the overall complex system manageable through modular organization of functions.
Solution Approach 2:
The patent introduces intermediary elements such as health scores and confidence values that mediate between raw health data and final proxy selection. These intermediaries simplify the decision-making process by providing aggregated, interpretable metrics that guide the selection without requiring direct analysis of all underlying health parameters.
3Ease of operation
If proxy VM health is not considered during selection, then ease of operation is maintained, but productivity of backup operations deteriorates
Solution Approach 1:
The system performs self-service by automatically assessing proxy health, calculating confidence values, and generating ranked lists of suitable proxies. This eliminates the need for manual proxy evaluation and selection by administrators, maintaining ease of operation while significantly improving backup productivity through automated intelligent selection.
Data Source
AI summary
Techniques described herein relate to methods for managing backup and restore operations. The method may include obtaining a health data items associated with vProxies; performing a first clustering analysis using the health data items to apply a first vProxy health label to a first portion of the vProxies and a second vProxy health label to a second portion of the vProxies; performing a first confidence analysis to determine a separate vProxy health confidence value for the first vProxy health label assigned to each of the first portion of vProxies; ranking the first portion of vProxies based on the first confidence analysis to obtain a ranked vProxy health list; receiving a request to perform a backup and restore management operation; and providing, in response to the request, a portion of the ranked vProxy health list to an entity requesting the backup and restore management operation.