A Space Exploration Company Owns a Series of Telescopes That

Multiple Choice

A space exploration company owns a series of telescopes that capture a large number of images and data of the night sky. The images and data are processed on an application hosted on AWS Fargate in a target group assigned to an Application Load Balancer (ALB) . The application is made available through the address https://space.example.com. Scientists require another custom-built application hosted on several Amazon EC2 instances within an Auto Scaling group. This application will be made available from the address https://space.example.com/meteor. The company needs a solution that can automatically scale from a small number of requests overnight to a large number of requests for a future meteor shower. What is the MOST operationally efficient solution that meets these requirements?

A) Update the existing target group with the new EC2 instances. Update the application's ALB by adding a listener rule that redirects /meteor to the newly added EC2 instances.
B) Create a new target group. Configure the Auto Scaling group of the EC2 instances to use the target group. Update the ALB by adding a listener rule that redirects /meteor to the new target group.
C) Create a Network Load Balancer (NLB) . Configure the NLB to listen on two ports. Configure a target group for one port to deliver all IP traffic to the Auto Scaling group to process the custom images. Configure a target group for the second port to deliver all IP traffic to Fargate. Use path-based routing in the ALB to route traffic for the URL prefix /meteor to the first target group. Route all other paths to the second target group.
D) Place the ALB behind an Amazon CloudFront distribution. Create a Lambda@Edge function that parses the request URI and adds the path-pattern header with the IP addresses of the EC2 instances to any request for /meteor. Add a listener rule to the ALB that looks for the HTTP header and uses the IP addresses of the EC2 instances to forward the traffic.