- Amazon S3 buckets for storing content
- Amazon EC2 for the front-end web servers
- AWS Lambda for executing image processing
- Amazon DynamoDB for storing session-related data
The team expects a significant increase in traffic to the site. The application should handle the additional load without interruption. The team ran initial tests by adding new servers to the EC2 front-end to handle the larger load, but the instances took up to 20 minutes to become fully configured. The team wants to reduce this configuration time. What changes will the Engineering team need to implement to make the solution the MOST resilient and highly available while meeting the expected increase in demand?
A. Use AWS OpsWorks to automatically configure each new EC2 instance as it is launched. Configure the EC2 instances by using an Auto Scaling group behind an Application Load Balancer across multiple Availability Zones. Implement Amazon DynamoDB Auto Scaling. Use Amazon Route 53 to point the application DNS record to the Application Load Balancer.
B. Deploy a fleet of EC2 instances, doubling the current capacity, and place them behind an Application Load Balancer. Increase the Amazon DynamoDB read and write capacity units. Add an alias record that contains the Application Load Balancer endpoint to the existing Amazon Route 53 DNS record that points to the application.
C. Configure Amazon CloudFront and have its origin point to Amazon S3 to host the web application. Implement Amazon DynamoDB Auto Scaling. Use Amazon Route 53 to point the application DNS record to the CloudFront DNS name.
D. Use AWS Elastic Beanstalk with a custom AMI including all web components. Deploy the platform by using an Auto Scaling group behind an Application Load Balancer across multiple Availability Zones. Implement Amazon DynamoDB Auto Scaling. Use Amazon Route 53 to point the application DNS record to the Elastic Beanstalk load balancer.