AWS Certified Developer – Associate (DVA-C02) — Question 203

A developer is building a serverless application that connects to an Amazon Aurora PostgreSQL database. The serverless application consists of hundreds of AWS Lambda functions. During every Lambda function scale out, a new database connection is made that increases database resource consumption.

The developer needs to decrease the number of connections made to the database. The solution must not impact the scalability of the Lambda functions.

Which solution will meet these requirements?

Answer options

• A. Configure provisioned concurrency for each Lambda function by setting the ProvisionedConcurrentExecutions parameter to 10.
• B. Enable cluster cache management for Aurora PostgreSQL. Change the connection string of each Lambda function to point to cluster cache management.
• C. Use Amazon RDS Proxy to create a connection pool to manage the database connections. Change the connection string of each Lambda function to reference the proxy.
• D. Configure reserved concurrency for each Lambda function by setting the ReservedConcurrentExecutions parameter to 10.

Correct answer: C

Explanation

The correct solution is C because Amazon RDS Proxy efficiently manages database connections, reducing the number of simultaneous connections without affecting the Lambda functions' ability to scale. Option A and D relate to concurrency settings that do not address connection pooling, while option B involves cluster cache management, which does not directly reduce the number of database connections made.