AWS Certified Solutions Architect – Professional — Question 854
A company operating a website on AWS requires high levels of scalability, availability, and performance. The company is running a Ruby on Rails application on
Amazon EC2. It has a data tier on MySQL 5.6 on Amazon EC2 using 16 TB of Amazon EBS storage Amazon CloudFront is used to cache application content.
The Operations team is reporting continuous and unexpected growth of EBS volumes assigned to the MySQL database. The Solutions Architect has been asked to design a highly scalable, highly available, and high-performing solution.
Which solution is the MOST cost-effective at scale?
Answer options
- A. Implement Multi-AZ and Auto Scaling for all EC2 instances in the current configuration. Ensure that all EC2 instances are purchased as reserved instances. Implement new elastic Amazon EBS volumes for the data tier.
- B. Design and implement the Docker-based containerized solution for the application using Amazon ECS. Migrate to an Amazon Aurora MySQL Multi-AZ cluster. Implement storage checks for Aurora MySQL storage utilization and an AWS Lambda function to grow the Aurora MySQL storage, as necessary. Ensure that Multi-AZ architectures are implemented.
- C. Ensure that EC2 instances are right-sized and behind an Elastic Load Balancing load balancer. Implement Auto Scaling with EC2 instances. Ensure that the reserved instances are purchased for fixed capacity and that Auto Scaling instances run on demand. Migrate to an Amazon Aurora MySQL Multi-AZ cluster. Ensure that Multi-AZ architectures are implemented.
- D. Ensure that EC2 instances are right-sized and behind an Elastic Load Balancer. Implement Auto Scaling with EC2 instances. Ensure that Reserved instances are purchased for fixed capacity and that Auto Scaling instances run on demand. Migrate to an Amazon Aurora MySQL Multi-AZ cluster. Implement storage checks for Aurora MySQL storage utilization and an AWS Lambda function to grow Aurora MySQL storage, as necessary. Ensure Multi-AZ architectures are implemented.
Correct answer: C
Explanation
Amazon Aurora automatically and dynamically scales database storage up to 128 TB, meaning that custom AWS Lambda functions to grow storage (as suggested in options B and D) are redundant and unnecessary. Option C represents the most cost-effective compute strategy by combining Reserved Instances for predictable baseline workloads with On-Demand instances for auto-scaled traffic spikes, while leveraging Aurora's native storage scaling to resolve the EBS growth issue.