AWS Certified Solutions Architect Associate SAA-C03 Practice Question
A media company is deploying a web application that shows high demand variability, with expected surges in traffic during new content releases. The web application utilizes a compute layer hosted on Amazon EC2 to serve dynamic content which must scale accordingly. Which approach should the company's solutions architect take to ensure the compute layer can cost-effectively manage varying workloads with minimal manual intervention?
Set up an Amazon RDS Multi-AZ deployment for the backend database to accommodate extra load
Implement scheduled scaling actions for the EC2 instances based on the content release schedule
Configure Amazon EC2 Auto Scaling with a target tracking scaling policy for the EC2 instances serving dynamic content
Manually resize the Amazon EC2 instances periodically to anticipate the high-demand periods
Employing Amazon EC2 Auto Scaling with a target tracking scaling policy enables dynamic scaling of EC2 instances in response to demand, ensuring cost-effectiveness by automatically adjusting the fleet size based on a specific, measurable performance metric. Manually resizing instances does not provide automation or rapid responsiveness. Implementing a scheduled scaling action would not be responsive to unpredictable traffic. Using an Amazon RDS Multi-AZ deployment targets database availability and failover, not the scalability of the compute layer needed for dynamic content delivery.
Ask Bash
Bash is our AI bot, trained to help you pass your exam. AI Generated Content may display inaccurate information, always double-check anything important.
What is Amazon EC2 Auto Scaling and how does it work?
Open an interactive chat with Bash
What are target tracking scaling policies in EC2 Auto Scaling?
Open an interactive chat with Bash
Why is manual resizing of EC2 instances not recommended for variable demand?