What should the solutions architect recommend to optimize the application’s performance?
Increase the memory of the Lambda function. Modify the Lambda function to close the database connections when the data is retrieved.
Add an Amazon ElastiCache for Redis cluster to store the frequently accessed data from the RDS database.
Create an RDS proxy by using the Lambda console. Modify the Lambda function to use the proxy endpoint.
Modify the Lambda function to connect to the database outside of the function’s handler. Check for an existing database connection before creating a new connection.
Explanations:
Increasing the memory of the Lambda function may improve its performance but does not directly address the high number of database connections and the need for efficient connection management. Closing connections after retrieval is a good practice, but without proper connection handling, it may still lead to performance issues.
While adding an Amazon ElastiCache for Redis can help reduce the load on the RDS by caching frequently accessed data, it does not solve the immediate issue of high CPU utilization and connection management during the flash sale. This option may improve performance but is not the most effective solution for the current problem.
Creating an RDS proxy allows the Lambda function to manage database connections more efficiently. The proxy can handle connection pooling, reducing the number of connections made to the database, which helps mitigate the high CPU utilization and connection spikes during peak traffic times.
Modifying the Lambda function to check for existing database connections before creating new ones can help, but if the function is invoked frequently, this approach may still lead to a high number of connections and does not address the underlying connection management issue effectively. It may also increase latency due to connection checks.
I judge that the answer is:
Create an RDS proxy by using the Lambda console. Modify the Lambda function to use the proxy endpoint.