Which solution meets these requirements?
Create an Amazon CloudWatch alarm action that triggers a Lambda function to add an Amazon RDS for MySQL read replica when resource utilization hits a threshold.
Migrate the database to Amazon Aurora, and add a read replica. Add a database connection pool outside of the Lambda handler function.
Migrate the database to Amazon Aurora, and add a read replica. Use Amazon Route 53 weighted records.
Migrate the database to Amazon Aurora, and add an Aurora Replica. Configure Amazon RDS Proxy to manage database connection pools.
Explanations:
Creating a CloudWatch alarm to add read replicas dynamically can help during peak times, but it doesn’t address the connection pool issue effectively. Lambda functions can still exhaust the database connections, leading to slow response times.
While migrating to Amazon Aurora and adding a read replica can improve performance, it does not specifically address connection pooling. Without proper management of database connections, the application may still face performance issues during peak loads.
Similar to option B, migrating to Aurora and adding a read replica helps with performance, but using Route 53 weighted records does not solve the connection pooling problem. It also does not provide effective management for high connection loads during peak usage.
Migrating to Amazon Aurora and adding an Aurora Replica, along with configuring Amazon RDS Proxy for connection pooling, effectively addresses the scalability and availability concerns. RDS Proxy helps manage and pool database connections, reducing the load on the database during peak periods.
I reckon the answer is:
Migrate the database to Amazon Aurora, and add an Aurora Replica. Configure Amazon RDS Proxy to manage database connection pools.