Question

Difficulty: MediumMulti-AZ, Multi-Region Architectures and Disaster Recovery (DR)

A healthcare technology company hosts its core prescription processing application in the us-east-1 Region. The application uses an Amazon Aurora PostgreSQL database cluster. The company needs to design a disaster recovery (DR) strategy in the us-west-2 Region. The design must achieve a Recovery Point Objective (RPO) of less than 5 minutes and a Recovery Time Objective (RTO) of less than 30 minutes. To comply with budget constraints, the strategy must also minimize ongoing infrastructure costs. Which disaster recovery configuration meets these requirements?

  1. Configure an Amazon Aurora Global Database with the primary cluster in us-east-1 and a secondary cluster in us-west-2. Deploy an Application Load Balancer and an Auto Scaling group in us-west-2 with the desired and minimum capacity set to 0. During a disaster recovery event, promote the secondary database cluster and scale up the Auto Scaling group.Answer
  2. B
    Deploy a Warm Standby architecture in us-west-2 with an active database cluster of the same size as the primary database, and a fully scaled Application Load Balancer and Auto Scaling group running at identical capacity to the primary region.
  3. C
    Deploy an Amazon RDS for PostgreSQL database instance in us-east-1 with a cross-region Read Replica in us-west-2. Configure an Amazon Route 53 latency routing policy to automatically redirect application traffic to the secondary region's Read Replica in the event of a primary database failure.
  4. D
    Configure daily automated database exports to an Amazon S3 bucket, and use S3 Cross-Region Replication to copy the backups to an S3 Glacier Flexible Retrieval vault in us-west-2. In the event of a disaster, retrieve the backup from S3 Glacier and restore it to a new database instance.

Answer

Configure an Amazon Aurora Global Database with the primary cluster in us-east-1 and a secondary cluster in us-west-2. Deploy an Application Load Balancer and an Auto Scaling group in us-west-2 with the desired and minimum capacity set to 0. During a disaster recovery event, promote the secondary database cluster and scale up the Auto Scaling group.
The correct strategy uses Amazon Aurora Global Database to achieve near-zero RPO (sub-second replication) and deploys compute resources scaled to zero in the secondary region to minimize ongoing costs. In the event of a failover, the secondary database is promoted and the compute resources are scaled up, which can easily be completed within the 30-minute RTO. This represents a highly cost-optimized Pilot Light DR pattern.

Step-by-Step Solution

1
Analyze RPO and RTO requirements against database replication technologies.
Amazon Aurora Global Database provides sub-second replication latency, which easily satisfies the 5-minute RPO constraint.
Choosing a continuous replication mechanism is necessary because daily snapshots or exports cannot meet a 5-minute RPO.
2
Evaluate the cost minimization constraint against compute deployment options.
Using a Pilot Light strategy by configuring an Auto Scaling group with a desired/minimum capacity of 0 ensures that compute charges are only incurred during testing or an actual disaster recovery event.
Running a fully scaled Warm Standby configuration continuously is expensive and violates the requirement to minimize ongoing costs.
3
Verify RTO compliance for promoting the secondary database and scaling compute.
Promoting an Aurora secondary cluster takes less than a minute, and scaling up the Auto Scaling group instances takes a few minutes, fitting well within the 30-minute RTO target.
Ensuring both the database promotion and compute provisioning steps can complete within the RTO budget is critical for the success of the DR plan.

Key Concept

Disaster Recovery (DR) strategies on AWS involve balancing Recovery Time Objective (RTO), Recovery Point Objective (RPO), and cost. A Pilot Light strategy keeps data replicated and infrastructure definitions ready, but compute resources are turned off or scaled to zero until a failover occurs, making it highly cost-effective.
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