Cloud Instance Failover via Availability Zone Segmentation

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Solution Overview

Problem

The unpredictability of spot instance availability in cloud computing environments due to fluctuations in demand and supply, leading to potential instability and sudden terminations, which can deter users despite the cost benefits.

Innovation Solution

Optimizing cloud computing operations by defining a primary availability zone (AZ) and a set of fallback AZs, where the primary AZ is actively used under normal conditions, and performance metrics are continuously monitored to switch to a fallback AZ when certain conditions are met, ensuring continuous availability and fault tolerance.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If applications are deployed in multiple AZs to mitigate spot instance unpredictability, then availability and fault tolerance are improved, but egress data traffic costs and network complexity increase

Engineering Contradiction:
ImproveavailabilityVSAvoidegress data traffic cost
Core Design Contradiction:
ReliabilityVSLoss of energy

Solution Approach 1:

The system segments the multi-AZ deployment into a primary AZ for active application execution and fallback AZs for standby. This segmentation allows the application to run in a single primary AZ under normal conditions, avoiding cross-AZ data traffic costs, while maintaining backup capacity in fallback AZs for failover scenarios.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The system dynamically switches between primary and fallback AZs based on spot instance availability and performance metrics. When spot instances become unavailable or performance degrades, the system automatically fails over to a fallback AZ, providing dynamic adaptability to changing conditions while minimizing cross-AZ traffic.

Inventive Principle:
Principle #15Dynamics

2Productivity

If spot instances are used to reduce costs, then operational efficiency is improved, but availability stability deteriorates due to sudden terminations

Engineering Contradiction:
Improveoperational efficiencyVSAvoidavailability stability
Core Design Contradiction:
ProductivityVSReliability

Solution Approach 1:

The system prepares fallback AZs in advance with pre-configured capacity and standby spot instances. When the primary AZ experiences spot instance terminations or performance degradation, the fallback AZs are already ready to immediately take over, cushioning the impact of spot instance instability and maintaining continuous operation.

Inventive Principle:
Principle #11Beforehand cushioning (Prior cushioning)

Solution Approach 2:

The system continuously monitors performance metrics of spot instances in the primary AZ and automatically triggers failover to fallback AZs when thresholds are breached. This feedback mechanism enables the system to respond to spot instance instability in real-time, maintaining availability stability while preserving the cost benefits of spot instances.

Inventive Principle:
Principle #23Feedback

3Loss of energy

If a single-AZ configuration is used to avoid egress data traffic, then network costs are reduced, but availability and fault tolerance worsen

Engineering Contradiction:
Improvenetwork costVSAvoidfault tolerance
Core Design Contradiction:
Loss of energyVSReliability

Solution Approach 1:

The system segments the fault tolerance capability into a primary AZ for active operations and fallback AZs for backup capacity. This allows the system to maintain single-AZ operation for cost efficiency while having segmented backup capacity ready in alternative AZs for failover scenarios.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The system introduces a control plane as an intermediary that manages the primary and fallback AZs. This control plane monitors the primary AZ's health and orchestrates failover to fallback AZs when needed, enabling the system to maintain low network costs while preserving fault tolerance through automated failover capabilities.

Inventive Principle:
Principle #24Intermediary (Mediator)

Data Source

PatentUS12299500B1Optimizing cloud instances with smart availability zone failover
Publication Date: 2025.05.13 CAST AI GROUP INC
  • US12299500B1 patent drawing
  • US12299500B1 patent drawing
  • US12299500B1 patent drawing

AI summary

A method or a system for enhancing cloud computing operations across various availability zones (AZs) of a cloud service provider (CSP). A set of performance metrics for multiple AZs are determined through data collection and analysis using a machine learning model. An initial AZ is selected for deploying an application based on the current performance metrics. The application is then deployed on this AZ. Continuous monitoring of these metrics is conducted to assess the performance of the deployed AZ. If the performance decreases to a predefined threshold, a second AZ is selected based on the latest performance metrics. The application is subsequently switched from the first AZ to the second AZ.