What should a solutions architect do to meet these requirements?
Reduce the Lambda concurrency rate.
Enable RDS Proxy on the RDS DB instance.
Resize the RDS DB instance class to accept more connections.
Migrate the database to Amazon DynamoDB with on-demand scaling.
Explanations:
Reducing the Lambda concurrency rate may limit the number of simultaneous requests to the database, but it does not address the underlying issue of connection timeouts, especially during peak traffic. This could lead to degraded performance and does not scale effectively with unpredictable traffic.
Enabling RDS Proxy provides a connection pool for the database, which can manage database connections more efficiently and reduce the likelihood of connection timeouts during peak usage. It helps in managing database connections, especially in a serverless architecture, where Lambda functions may create many connections that can overwhelm the database.
Resizing the RDS DB instance class can increase the capacity for connections, but this approach typically requires downtime for the instance to resize. Additionally, if the application is already experiencing connection timeouts due to a high volume of short-lived connections from Lambda, merely resizing the instance may not effectively solve the problem of connection management and could lead to increased costs without guaranteed improvements.
Migrating to Amazon DynamoDB involves a significant change to the application architecture and code, as it requires rewriting data access patterns. While DynamoDB can handle scaling automatically, this option does not align with the requirement of minimizing code changes and might also necessitate additional overhead in terms of data modeling and management.