Which solution meets these requirements?
Migrate the database to Amazon Aurora MySQL. Replace the MySQL read replicas with Aurora Replicas and enable Aurora Auto Scaling
Deploy an Amazon ElastiCache for Redis cluster in front of the database. Modify the website to check the cache before querying the database read endpoints.
Migrate the database from Amazon RDS to MySQL running on Amazon EC2 compute instances. Choose very large compute optimized instances for all replica nodes.
Migrate the database to Amazon DynamoDB. Initially provision a large number of read capacity units (RCUs) to support the required throughput with on- demand capacity scaling enabled.
Explanations:
Amazon Aurora MySQL is designed for high performance and high availability with minimal replication lag. Aurora Replicas are more efficient than MySQL read replicas and support Aurora Auto Scaling, which adjusts the number of replicas based on traffic, reducing lag and maintaining performance.
Although caching with ElastiCache could reduce load on the database by storing frequently accessed data, this option requires modifying the application code to check the cache first. Additionally, it does not address replication lag directly, as it only reduces database query frequency.
Running MySQL on Amazon EC2 with large instances for replicas might improve performance, but it would require significant operational overhead, and replication lag issues could still persist. It also increases maintenance complexity, with no guarantee of reducing replication lag effectively.
Migrating to Amazon DynamoDB would require a substantial change to the database structure and application code, which does not meet the requirement for minimal changes. Additionally, DynamoDB is a NoSQL solution, which may not fit the current relational database schema and consistency needs.
I scheme that the answer is:
Migrate the database to Amazon Aurora MySQL. Replace the MySQL read replicas with Aurora Replicas and enable Aurora Auto Scaling