SAA-C03 Question 475
Single answerA company runs a high-traffic e-commerce platform that uses a relational database for its transactional data. The database experiences unpredictable workloads with traffic spikes during major sales events. The company has a limited budget and wants to ensure the database solution is cost-optimized while still providing high availability and scalability. Which solution is the most cost-effective choice?
- A
Use Amazon RDS with a Multi-AZ deployment and provisioned instances with sufficient capacity to handle peak traffic.
- B
Use Amazon RDS with a Multi-AZ deployment and configure an Auto Scaling group for the database instances.
- C
Use Amazon Aurora Serverless v2, which automatically adjusts capacity to match workload demands.
- D
Use Amazon DynamoDB with on-demand capacity mode and migrate the relational database schema to a NoSQL model.
Show answer and explanation
Correct answer: C
Explanation
Amazon Aurora Serverless v2 is the most cost-optimized solution for this scenario because it provides the ability to scale database capacity automatically based on workload demands and charges only for the consumed capacity. This avoids the need to provision resources for peak traffic, reducing overall costs while maintaining scalability and high availability.
- A. Incorrect.
This option provides high availability, but provisioning instances for peak traffic can lead to underutilization during normal workloads, resulting in higher costs. It is not the most cost-optimized choice.
- B. Incorrect.
Amazon RDS does not support Auto Scaling for the database instances themselves. This is an invalid option.
- C. Correct.
Amazon Aurora Serverless v2 is a highly cost-effective solution for unpredictable workloads as it automatically adjusts capacity to match demand, avoiding over-provisioning.
- D. Incorrect.
While Amazon DynamoDB is cost-effective with on-demand capacity mode, migrating a relational database to a NoSQL model requires significant changes to the application and may not be suitable for transactional workloads.