Cloud Failover Resource Allocation Using Skeletal Backup Instances

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Solution Overview

Problem

Deploying primary and backup instances of mission critical applications in geographically dispersed cloud environments leads to unnecessary doubling of computing resources, increasing costs, power consumption, and cooling requirements due to idle resources.

Innovation Solution

Implementing a primary application cloud instance that allocates necessary resources based on historical usage and provides heartbeat and session state information to a dormant backup instance, which in turn allocates a minimum quantity of resources for a skeletal version, conserving resources and enabling quick scaling during failures.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If primary and backup instances are deployed in geographically dispersed cloud environments, then reliability is improved, but computing resources are doubled unnecessarily

Engineering Contradiction:

Improvefault toleranceVSAvoidcomputing resources

Core Design Contradiction:

ReliabilityVSQuantity of substance

Solution Approach 1:

The backup instance dynamically adjusts its resource allocation based on operational state. During normal operation, it maintains minimal resources while in standby mode, and automatically scales up to full capacity when failover is triggered, eliminating the need for permanent full resource allocation

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system changes the operational parameters of the backup instance from active full-performance mode to dormant minimal-mode. By altering the state parameters (CPU allocation, memory allocation, network bandwidth) based on whether the instance is primary or backup, resources are optimized while maintaining reliability

Inventive Principle:

Principle #35Parameter changes

2Speed

If backup instances are kept ready with full resources, then failover speed is improved, but power consumption increases

Engineering Contradiction:

Improvefailover speedVSAvoidpower consumption

Core Design Contradiction:

SpeedVSUse of energy by moving object

Solution Approach 1:

The backup instance performs preliminary actions by pre-configuring its infrastructure and maintaining connection readiness, but deferes full resource activation until actually needed. This allows rapid activation without continuous full power consumption, as the essential configuration work is done in advance

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements periodic health checks and status synchronization between primary and backup instances, rather than continuous full operation. The backup instance periodically verifies its readiness state and synchronizes minimal necessary data, maintaining failover capability while dramatically reducing continuous power consumption

Inventive Principle:

Principle #19Periodic action

3Reliability

If idle computing resources are maintained for backup, then service continuity is improved, but cooling requirements increase

Engineering Contradiction:

Improveservice continuityVSAvoidcooling requirements

Core Design Contradiction:

ReliabilityVSTemperature

Solution Approach 1:

The cooling system dynamically adjusts based on the actual computational load of the backup instance. Since the backup operates in minimal-mode during standby, heat generation is significantly reduced, allowing for adaptive cooling that matches actual thermal output rather than provisioning for maximum potential load continuously

Inventive Principle:

Principle #15Dynamics

4Reliability

If full resources are allocated to backup instance, then application availability during failures is improved, but cost increases

Engineering Contradiction:

Improveapplication availabilityVSAvoidcost

Core Design Contradiction:

ReliabilityVSLoss of energy

Solution Approach 1:

The system changes resource allocation parameters based on the operational role. The backup instance operates with modified parameters (reduced CPU cores, reduced memory, limited network bandwidth) during standby, and transitions to full parameters only when activated, directly reducing operational costs while maintaining availability

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS20250363031A1Systems and methods for optimizing resources for applications deployed in primary and backup geographically dispersed cloud environments

Publication Date: 2025.11.27 VERIZON PATENT & LICENSING INC

AI summary

A primary application cloud instance may receive historical usage of an application, may allocate, based on the historical usage, a quantity of cloud resources for enabling the application to be accessed, and may enable the application to be accessed. The primary application cloud instance may provide, to a backup application cloud instance that allocates a minimum quantity of cloud resources for providing a skeletal version of the application, heartbeat and session state information associated with the primary application cloud instance, and the quantity of cloud resources for enabling the application to be accessed. The primary application cloud instance may provide, to the backup application cloud instance, an indication of a failure of the primary application cloud instance, via the heartbeat and session state information, to cause the backup application cloud instance to allocate the quantity of cloud resources and to enable access to the application.