Virtual Machine Backup Granularity via Dynamic Querying

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Solution Overview

Problem

Current virtual machine backup systems, such as VMware Consolidated Backup (VCB), face challenges in performing granular file-level backups for non-Microsoft Windows virtual machines, requiring image-level backups which are laborious and result in data loss, and lack automatic identification of virtual machines for backup, making it difficult to manage transient virtual environments.

Innovation Solution

A method for dynamically querying virtual machine managers and hosts to automatically identify and copy virtual machine data at a file, volume, or disk level, enabling granular restoration and simplifying the backup process across various operating systems, including non-Microsoft Windows platforms.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If image-level backup is used for non-Microsoft Windows virtual machines, then backup compatibility is improved, but restoration granularity deteriorates and data loss occurs

Engineering Contradiction:

Improvebackup compatibilityVSAvoidrestoration granularity

Core Design Contradiction:

Adaptability or versatilityVSManufacturing precision

Solution Approach 1:

The patent segments the virtual machine backup process into multiple levels: image-level backup for compatibility and file-level backup for granularity. The system divides virtual disk data into manageable components that can be backed up at different granularities, allowing restoration of individual files or entire virtual machines as needed.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent implements dynamic backup strategy that adapts to different virtual machine types and user needs. The system can dynamically switch between image-level and file-level backup approaches, and can dynamically identify and query virtual machines during the backup process to optimize the backup method for each specific case.

Inventive Principle:

Principle #15Dynamics

2Ease of operation

If manual identification of virtual machines is used, then backup control is improved, but operational complexity deteriorates in transient environments

Engineering Contradiction:

Improvebackup controlVSAvoidoperational complexity

Core Design Contradiction:

Ease of operationVSDevice complexity

Solution Approach 1:

The patent implements self-service mechanisms where the backup system automatically identifies and queries virtual machines without requiring manual intervention. The system autonomously discovers transient virtual machines in the environment, determines their backup requirements, and executes appropriate backup operations without user involvement.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent incorporates feedback loops where the backup system continuously queries virtual machine managers and hosts to identify available virtual machines, receives information about their state and requirements, and adjusts backup operations accordingly. This feedback mechanism enables automatic adaptation to changing virtual environments.

Inventive Principle:

Principle #23Feedback

3Manufacturing precision

If file-level backup is performed for Microsoft Windows virtual machines, then restoration granularity is improved, but backup speed deteriorates compared to image-level backup

Engineering Contradiction:

Improverestoration granularityVSAvoidbackup speed

Core Design Contradiction:

Manufacturing precisionVSProductivity

Solution Approach 1:

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The patent applies partial backup action by allowing users to select specific files, directories, or volumes for backup rather than requiring complete virtual machine backups. This partial action approach backs up only the necessary portions of virtual machine data, improving speed while maintaining granularity where needed.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS11436210B2Classification of virtualization data

Publication Date: 2022.09.06 COMMVAULT SYSTEMS INC

AI summary

A method and system described herein for classifying data of virtual machines in a heterogeneous computing comprising virtual machines and non-virtual machines. The system may access a secondary copy of data stored by a virtual machine, create metadata associated with that data, store the metadata in an index that comprises metadata associated with data stored on non-virtual machines, using a journal file, determine modified data objects within the data stored by the virtual machine, access or create metadata associated with modified data objects, and update the index accordingly.