A financial analytics company is designing a cost-optimized disaster recovery (DR) architecture on Google Cloud for a non-critical internal processing web application. The organization has established the following operational requirements and constraints: Cost Efficiency: Minimize compute spend by running only a single active VM instance and avoiding continuously running standby compute instances. Automated Instance Recovery: If the active VM or application service fails, the platform must automatically provision a replacement VM without requiring manual administrative intervention. Data Recovery & RPO: Data changes are captured through scheduled Persistent Disk snapshots, defining the organization's Recovery Point Objective (RPO). Endpoint Consistency: The frontend IP address exposed to clients must remain constant during and after instance recreation. Which disaster recovery architectural pattern should you implement?

Deploy a Managed Instance Group (MIG) with a target size of 1 behind an Application Load Balancer, using an instance template whose startup script restores and mounts the latest disk snapshot.: What the Cold Standby Pattern Is The cold failover pattern using a Managed Instance Group (MIG) with a target size of one is a cost-effective disaster recovery architecture in Google Cloud. It combines automated instance autohealing, predefined instance templates, and Persistent Disk snapshots to recover a failed workload without paying for idle standby compute instances. How It Meets the Requirements Cost Efficiency: Setting the MIG target size to 1 ensures that only a single VM runs at any given time, eliminating the overhead of idle secondary instances. Automated Instance Recovery: Integrated HTTP health checks detect application or instance crashes. When a failure occurs, the MIG automatically recreates the VM instance in the zone using the specified instance template. Data Recovery & RPO: The VM's startup script fetches the latest Persistent Disk snapshot and attaches/mounts the restored disk upon startup, achieving the target RPO defined by snapshot frequency. Endpoint Consistency: Placing an external or internal Application Load Balancer in front of the MIG ensures that incoming client requests consistently target the same stable virtual IP address regardless of backend VM replacements. Key Advantages and Capabilities Automated Autohealing: Provides self-healing compute capabilities that eliminate manual intervention for single-VM failures. Predictable Configuration: Uses custom images and instance templates to ensure configuration consistency across VM recreations. Decoupled Frontend: Isolates client-facing networking from backend instance lifecycles using Google Cloud load balancers. Cross-Zone Portability: Persistent Disk snapshots are stored regionally/multi-regionally, allowing manual disk reconstruction in another zone if a full zonal disruption occurs. Why This Is Optimal This architecture perfectly balances recovery automation with aggressive cost reduction, delivering a functional cold DR strategy without the resource waste of active duplicate servers.

Cold Dr Pattern Managed Instance Group | Professional Cloud Architect

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Explanations

What the Cold Standby Pattern Is

The cold failover pattern using a Managed Instance Group (MIG) with a target size of one is a cost-effective disaster recovery architecture in Google Cloud. It combines automated instance autohealing, predefined instance templates, and Persistent Disk snapshots to recover a failed workload without paying for idle standby compute instances.

How It Meets the Requirements

Cost Efficiency: Setting the MIG target size to 1 ensures that only a single VM runs at any given time, eliminating the overhead of idle secondary instances.
Automated Instance Recovery: Integrated HTTP health checks detect application or instance crashes. When a failure occurs, the MIG automatically recreates the VM instance in the zone using the specified instance template.
Data Recovery & RPO: The VM's startup script fetches the latest Persistent Disk snapshot and attaches/mounts the restored disk upon startup, achieving the target RPO defined by snapshot frequency.
Endpoint Consistency: Placing an external or internal Application Load Balancer in front of the MIG ensures that incoming client requests consistently target the same stable virtual IP address regardless of backend VM replacements.

Key Advantages and Capabilities

Automated Autohealing: Provides self-healing compute capabilities that eliminate manual intervention for single-VM failures.
Predictable Configuration: Uses custom images and instance templates to ensure configuration consistency across VM recreations.
Decoupled Frontend: Isolates client-facing networking from backend instance lifecycles using Google Cloud load balancers.
Cross-Zone Portability: Persistent Disk snapshots are stored regionally/multi-regionally, allowing manual disk reconstruction in another zone if a full zonal disruption occurs.

Why This Is Optimal

This architecture perfectly balances recovery automation with aggressive cost reduction, delivering a functional cold DR strategy without the resource waste of active duplicate servers.

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Professional Cloud Architect

Cold Dr Pattern Managed Instance Group