Which solution will meet these requirements?
Configure the AWS DMS replication instance with a Multi-AZ deployment to provision instances across multiple Availability Zones.
Create an AWS DMS Serverless replication task to analyze and replicate the data while provisioning the required capacity.
Use Amazon EC2 Auto Scaling to scale the size of the AWS DMS replication instance up or down based on the amount of data toreplicate.
Provision AWS DMS replication capacity by using Amazon Elastic Container Service (Amazon ECS) with an AWS Fargate launch type to analyze and replicate the data while provisioning the required capacity.
Explanations:
Configuring a Multi-AZ deployment for AWS DMS replication instance improves availability and fault tolerance but does not address the requirement of dynamically allocating capacity based on data replication needs. It still requires a fixed amount of resources regardless of data volume.
AWS DMS Serverless allows for automatic provisioning of the necessary resources to handle varying workloads. It scales the capacity based on the actual requirements of the data replication task, thus efficiently managing costs while meeting the company’s need to replicate data changes.
While Amazon EC2 Auto Scaling can dynamically adjust the number of EC2 instances based on demand, AWS DMS replication instances cannot be directly managed in this way. AWS DMS does not support dynamic scaling of replication instances through EC2 Auto Scaling, making this option unsuitable.
Using Amazon ECS with Fargate may allow for a containerized approach to run AWS DMS tasks, but it does not provide a native solution for DMS itself. AWS DMS is designed to run on AWS-managed instances, and using ECS/Fargate introduces unnecessary complexity and does not directly address the requirement for automatic capacity provisioning.
I guess:
Create an AWS DMS Serverless replication task to analyze and replicate the data while provisioning the required capacity.