A Company Is Refactoring an Existing Web Service That Provides

A company is refactoring an existing web service that provides read and write access to structured data. The service must respond to short but significant spikes in the system load. The service must be fault tolerant across multiple AWS Regions. Which actions should be taken to meet these requirements?

A) Store the data in Amazon DocumentDB. Create a single global Amazon CloudFront distribution with a custom origin built on edge-optimized Amazon API Gateway and AWS Lambda. Assign the company's domain as an alternate domain for the distribution, and configure Amazon Route 53 with an alias to the CloudFront distribution.
B) Store the data in replicated Amazon S3 buckets in two Regions. Create an Amazon CloudFront distribution in each Region, with custom origins built on Amazon API Gateway and AWS Lambda launched in each Region. Assign the company's domain as an alternate domain for both distributions, and configure Amazon Route 53 with a failover routing policy between them.
C) Store the data in an Amazon DynamoDB global table in two Regions using on-demand capacity mode. In both Regions, run the web service as Amazon ECS Fargate tasks in an Auto Scaling ECS service behind an Application Load Balancer (ALB) . In Amazon Route 53, configure an alias record in the company's domain and a Route 53 latency-based routing policy with health checks to distribute traffic between the two ALBs.
D) Store the data in Amazon Aurora global databases. Add Auto Scaling replicas to both Regions. Run the web service on Amazon EC2 instances in an Auto Scaling group behind an Application Load Balancer in each Region. Configure the instances to download the web service code in the user data. In Amazon Route 53, configure an alias record for the company's domain and a multi-value routing policy