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Difficulty: MediumDisaster Recovery and Business Continuity Execution

A global logistics company runs its real-time package routing platform in Google Cloud. The core backend relies on a Compute Engine Managed Instance Group (MIG) and a Cloud SQL for PostgreSQL database located in primary region `us-central1`. To achieve a Recovery Point Objective (RPO) under 1 minute and a Recovery Time Objective (RTO) under 15 minutes, the team designed a Warm Standby disaster recovery (DR) pattern in secondary region `us-east4` using cross-region Cloud SQL read replicas. During an unannounced DR failover simulation, database promotion succeeded within 2 minutes, but spinning up additional backend instances in `us-east4` failed due to regional Compute Engine resource quota limits, causing an RTO breach. Which architectural adjustment should the Cloud Architect implement to ensure reliable DR execution while maintaining the Warm Standby strategy?

  1. Proactively request and maintain sufficient Compute Engine regional quotas in `us-east4` while running a minimal baseline instance footprint in the secondary Managed Instance Group that automatically scales out upon failover.Answer
  2. B
    Deploy an automated Cloud Function triggered by failover alerts to submit emergency Compute Engine quota increase requests to Google Cloud Support during a disaster event.
  3. C
    Transition to a Cold Backup strategy by taking automated hourly database snapshots to Cloud Storage and building all compute and database resources on demand following a primary region outage.
  4. D
    Migrate the relational database layer to a multi-region Cloud Spanner instance and configure cross-region VPC Network Peering to eliminate compute quota dependencies.

Answer

Proactively request and maintain sufficient Compute Engine regional quotas in `us-east4` while running a minimal baseline instance footprint in the secondary Managed Instance Group that automatically scales out upon failover.
The correct strategy for Warm Standby disaster recovery requires proactive capacity planning. Pre-requesting regional Compute Engine quotas ensures GCP will permit the required number of instances to launch. Maintaining a minimal baseline instance footprint in the secondary region ensures application config validation and fast auto-scaling within the 15-minute RTO target.

Step-by-Step Solution

1
Analyze DR requirements and execution bottleneck
The scenario specifies a Warm Standby pattern requiring RPO < 1 min and RTO < 15 min. The failure point was insufficient compute resource quota in the secondary region during failover scaling.
Warm Standby requires secondary compute infrastructure to be ready to scale out rapidly without hitting API or capacity constraints.
2
Evaluate regional quota management for DR execution
GCP resource quotas are region-specific and must be explicitly requested ahead of time. Quota approvals cannot be performed instantaneously during emergency failover.
Ensuring quota availability prior to a disaster guarantees that autoscaling policies can provision required compute nodes.
3
Align compute footprint with Warm Standby pattern
Pre-provisioning a minimal baseline MIG in the DR region ensures deployment templates and network connectivity are verified continuously, allowing seamless scale-out when failover occurs.
A minimal active footprint in the secondary region satisfies RTO bounds while optimizing baseline operational costs.

Key Concept

Disaster Recovery Execution & Quota Management
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Topics

Disaster Recovery and Business Continuity Execution

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