A company runs a website that uses a content management system (CMS) on Amazon EC2. The CMS runs on a single EC2 instance and uses an Amazon Aurora MySQL Multi-AZ DB instance for the data tier. Website images are stored on an Amazon Elastic Block Store (Amazon EBS) volume that is mounted inside the EC2 instance. Which combination of actions should a solutions architect take to improve the performance and resilience of the website? (Choose two.)
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Correct answer: Move the website images onto an Amazon Elastic File System (Amazon EFS) file system that is mounted on every EC2 instance., Create an Amazon Machine Image (AMI) from the existing EC2 instance. Use the AMI to provision new instances behind an Application Load Balancer as part of an Auto Scaling group. Configure the Auto Scaling group to maintain a minimum of two instances. Configure an Amazon CloudFront distribution for the website..
Why this is the answer
The existing architecture has a single point of failure with the EC2 instance and limited scalability. Creating an AMI and using it with an Auto Scaling group behind an Application Load Balancer (ALB) improves both performance (load distribution) and resilience (automatic instance replacement and scaling). Maintaining a minimum of two instances ensures high availability. Integrating Amazon CloudFront caches content closer to users, significantly improving website performance and reducing load on the EC2 instances. Moving website images to Amazon EFS provides a shared, scalable, and highly available file system that can be mounted by multiple EC2 instances. This eliminates the EBS volume as a single point of failure for image storage and allows multiple EC2 instances to access the same image data, which is crucial for a multi-instance setup. Mounting an S3 bucket on every EC2 instance is not a standard or efficient way to serve website images directly; S3 is typically accessed via API or CloudFront. Sharing images via NFS from a primary EC2 instance reintroduces a single point of failure and does not scale well.
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