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Difficulty: EasyCost-Optimized Database Design and Capacity Planning

A company is planning to migrate a relational database to AWS. The database experiences highly variable traffic, with high read/write activity during business hours and nearly zero activity at night. The application requires high availability with automatic failover. The company wants to minimize costs by paying only for the database capacity actually used. Which database configuration is the most cost-effective?

  1. Amazon Aurora Serverless v2 configured with Multi-AZAnswer
  2. B
    Amazon RDS for PostgreSQL Multi-AZ deployment using a fixed instance size and covered by a Compute Savings Plan
  3. C
    Amazon RDS for PostgreSQL Single-AZ deployment with a Read Replica configured as the automatic disaster recovery failover target
  4. D
    Amazon DynamoDB configured with fixed provisioned capacity mode to store the relational schema

Answer

Amazon Aurora Serverless v2 configured with Multi-AZ
Amazon Aurora Serverless v2 is the most cost-effective choice because it automatically scales database capacity up and down based on actual application demand. During periods of low activity or at night, it scales down to minimal capacity, ensuring the company only pays for the database capacity consumed. It also supports Multi-AZ deployments, which fulfills the high availability and automatic failover requirements.

Step-by-Step Solution

1
Analyze the workload requirements and identify that traffic is highly variable with near-zero activity at night, requiring a dynamic scaling solution to optimize costs.
Aurora Serverless v2 is selected as the primary database candidate due to its ability to scale capacity automatically based on real-time demand.
To align database capacity with actual usage and minimize idle capacity costs.
2
Evaluate the high availability and automatic failover requirements.
Deploying Aurora Serverless v2 in a Multi-AZ configuration ensures automatic failover capability while keeping compute costs aligned with actual usage.
To meet the high availability requirement without compromising the cost-optimization goal.
3
Review and eliminate alternative options based on AWS cost optimization and architectural constraints.
Fixed-size RDS with Compute Savings Plans is eliminated due to scope limitations, Single-AZ with Read Replicas is eliminated due to failover limitations, and DynamoDB with provisioned capacity is eliminated due to schema and scaling mismatches.
To ensure the selected solution is both architecturally sound and the most cost-effective.

Key Concept

Auto-scaling database capacity dynamically for variable workloads while meeting high availability standards
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Topics

Cost-Optimized Database Design and Capacity Planning