What should a solutions architect do to meet these requirements?
Set up an Amazon Aurora MySQL database as a replication target for the on-premises database. Create an Aurora Replica for the Aurora MySQL database, and move the aggregation jobs to run against the Aurora Replica. Set up collection endpoints as AWS Lambda functions behind a Network Load Balancer (NLB), and use Amazon RDS Proxy to write to the Aurora MySQL database. When the databases are synced, disable the replication job and restart the Aurora Replica as the primary instance. Point the collector DNS record to the NLB.
Set up an Amazon Aurora MySQL database. Use AWS Database Migration Service (AWS DMS) to perform continuous data replication from the on-premises database to Aurora. Move the aggregation jobs to run against the Aurora MySQL database. Set up collection endpoints behind an Application Load Balancer (ALB) as Amazon EC2 instances in an Auto Scaling group. When the databases are synced, point the collector DNS record to the ALDisable the AWS DMS sync task after the cutover from on premises to AWS.
Set up an Amazon Aurora MySQL database. Use AWS Database Migration Service (AWS DMS) to perform continuous data replication from the on-premises database to Aurora. Create an Aurora Replica for the Aurora MySQL database, and move the aggregation jobs to run against the Aurora Replica. Set up collection endpoints as AWS Lambda functions behind an Application Load Balancer (ALB), and use Amazon RDS Proxy to write to the Aurora MySQL database. When the databases are synced, point the collector DNS record to the ALB. Disable the AWS DMS sync task after the cutover from on premises to AWS.
Set up an Amazon Aurora MySQL database. Create an Aurora Replica for the Aurora MySQL database, and move the aggregation jobs to run against the Aurora Replica. Set up collection endpoints as an Amazon Kinesis data stream. Use Amazon Kinesis Data Firehose to replicate the data to the Aurora MySQL database. When the databases are synced, disable the replication job and restart the Aurora Replica as the primary instance. Point the collector DNS record to the Kinesis data stream.
Explanations:
This option suggests setting up a replication target with Aurora, but it does not adequately address the need for continuous data replication and fails to properly ensure a smooth cutover to AWS, as it proposes restarting the Aurora Replica as the primary instance, which is not a recommended practice for migration.
While this option sets up continuous data replication using AWS DMS, it suggests using EC2 instances in an Auto Scaling group for the collection endpoints, which may introduce complexity and potential downtime. It also lacks the use of an RDS Proxy for better connection management.
This option provides a comprehensive solution by using AWS DMS for continuous data replication, creating an Aurora Replica for aggregation jobs, and using Lambda functions behind an ALB for the collection endpoints. It allows for seamless migration and ensures minimal disruption to the existing environment, with a clear plan for cutover and disabling the DMS sync task post-migration.
This option proposes using Kinesis data streams for collecting data, which is not necessary for this scenario. It complicates the architecture unnecessarily and does not align with the requirement for a smooth transition from on-premises to AWS, as it does not utilize AWS DMS for continuous replication effectively.
I calculate that the answer is:
Set up an Amazon Aurora MySQL database. Use AWS Database Migration Service (AWS DMS) to perform continuous data replication from the on-premises database to Aurora. Create an Aurora Replica for the Aurora MySQL database, and move the aggregation jobs to run against the Aurora Replica. Set up collection endpoints as AWS Lambda functions behind an Application Load Balancer (ALB), and use Amazon RDS Proxy to write to the Aurora MySQL database. When the databases are synced, point the collector DNS record to the ALB. Disable the AWS DMS sync task after the cutover from on premises to AWS.