Adaptive VM Boot Sequence Generation for Disaster Recovery

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Solution Overview

Problem

Configuring the boot order of virtual machines (VMs) in disaster recovery scenarios is complex and error-prone, leading to potential failures due to manual configuration and race conditions, which can hinder the initial setup of disaster recovery tools and increase the risk of failure during recovery operations.

Innovation Solution

A smart and adaptive system that uses machine learning processes to automatically generate and optimize the VM boot sequence based on data analytics from production sites and DR test runs, allowing for dynamic modification and user feedback to refine the boot sequence logic, thereby reducing human error and improving DR performance.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If manual configuration of VM boot order is used, then flexibility in customization is improved, but configuration complexity and error rate increase

Engineering Contradiction:

Improvecustomization flexibilityVSAvoidconfiguration complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system automatically generates the VM boot sequence by analyzing dependencies among virtual machines without requiring manual administrator intervention. The algorithm autonomously determines the correct boot order based on detected dependency relationships, eliminating manual configuration while maintaining adaptability to different VM environments.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the manual mechanical process of configuring boot order with an automated computational algorithm. The system uses dependency analysis algorithms to automatically determine boot sequences, substituting human administrative actions with automated software-based dependency detection and sequence generation.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Adaptability or versatility

If manual configuration of VM boot order is used, then customization capability is improved, but time consumption and setup duration increase

Engineering Contradiction:

Improvecustomization capabilityVSAvoidsetup time

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The system performs preliminary automated analysis of VM dependencies during the disaster recovery setup phase, generating the boot sequence in advance before actual recovery operations begin. This preliminary automatic configuration eliminates the time-consuming manual setup process while ensuring the boot order is optimized for the specific VM environment.

Inventive Principle:

Principle #10Preliminary action

3Adaptability or versatility

If trial and error configuration method is used, then boot order can be adjusted, but error rate and failure risk increase

Engineering Contradiction:

Improveboot order adjustabilityVSAvoidrecovery reliability

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The system incorporates feedback mechanisms that monitor disaster recovery operations and use the collected information to optimize and refine the boot sequence. The algorithm learns from actual recovery outcomes and adjusts the dependency analysis and boot order generation accordingly, improving reliability through continuous feedback-driven optimization rather than trial-and-error approaches.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system performs preliminary automated analysis of VM dependencies to determine the correct boot sequence before recovery operations begin, eliminating the need for trial-and-error configuration during actual disaster recovery. The boot order is pre-calculated based on detected dependency relationships, ensuring reliability from the first attempt.

Inventive Principle:

Principle #10Preliminary action

4Productivity

If automated boot sequence generation is implemented, then configuration time is reduced, but system complexity increases

Engineering Contradiction:

Improveconfiguration speedVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent replaces complex manual configuration processes with an automated algorithmic system that detects VM dependencies and generates boot sequences. While the underlying system is complex, the user-facing interface remains simple, and the automation eliminates the need for administrators to understand complex dependency relationships, effectively managing system complexity through automation.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS11550595B2Adaptive system for smart boot sequence formation of VMs for disaster recovery

Publication Date: 2023.01.10 EMC IP HLDG CO LLC

AI summary

One example method includes receiving input concerning a boot order sequence, where the input includes VM metadata, entering a training phase which includes generating a boot sequence rule based on the input, using the boot sequence rule to generate a proposed boot sequence, performing the proposed boot sequence, and gathering information concerning performance of the proposed boot sequence. The gathered information can be used as a basis to generate a modified boot sequence.