Which solution will meet these requirements?

Explanations:

Migrating to Amazon Aurora MySQL and using Aurora Replicas can significantly reduce replication lag due to its optimized architecture for replication and better performance under load. Aurora also supports auto-scaling, which helps manage peak loads without changing application code. Native functions can be leveraged for stored procedures, maintaining performance while reducing lag.

Deploying ElastiCache for Redis can improve read performance by caching frequently accessed data, but it does not directly address the replication lag issue. Additionally, modifying the application code to check the cache before querying the database increases operational overhead. Replacing stored procedures with Lambda functions also adds complexity and doesn’t align with the goal of minimizing changes to the application.

Migrating to a MySQL database on EC2 instances may allow for choosing larger, more powerful instances to reduce lag, but this approach involves significant operational overhead in terms of management and scaling. Additionally, it doesn’t provide the same level of optimized replication as Aurora, potentially leading to continued lag issues. Maintaining stored procedures on EC2 does not address the need for minimizing changes.

Migrating to Amazon DynamoDB would require a complete redesign of the data model and application logic, as DynamoDB is a NoSQL database and does not support stored procedures. Although it can handle high throughput with on-demand capacity scaling, it does not address the specific issue of replication lag experienced in the current architecture and introduces significant changes to the application.