A multi-tenant IoT telemetry platform hosts its real-time processing pipeline on Google Cloud with a primary deployment in us-east1 and a secondary disaster recovery (DR) site in us-central1. The business mandates a recovery time objective (RTO) of 2 hours and a recovery point objective (RPO) of 15 minutes. During a recent DR validation drill, attempting to fail over processing nodes to the DR region caused severe service degradation because the secondary region lacked sufficient Compute Engine CPU quota to accommodate the incoming traffic volume. Which procedure should the cloud architect implement to ensure reliable disaster recovery validation?
- Automate pre-validation verification checks of regional resource quotas and capacity reservations in the target region prior to initiating failover drills, while conducting regular non-disruptive DR simulations.Answer
- BRely on initiating unannounced live failovers and submitting emergency quota increase requests to Google Cloud Support during the active recovery window whenever capacity limits are reached.
- CTransition the disaster recovery strategy to a cold standby model that backs up data snapshots to Cloud Storage and delays infrastructure provisioning until a disaster occurs.
- DReplace existing VPC Network Peering with dedicated high-bandwidth Partner Interconnect connections between regions to bypass compute provisioning limits.
Answer
Automate pre-validation verification checks of regional resource quotas and capacity reservations in the target region prior to initiating failover drills, while conducting regular non-disruptive DR simulations.
Establishing automated pre-validation procedures that verify regional CPU/instance quotas and active capacity reservations ensures that target DR regions have sufficient capacity before failover traffic is routed, satisfying both RTO and RPO objectives.
Step-by-Step Solution
Key Concept
Disaster Recovery Validation and Quota Management