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?
- Configure provisioned concurrency for each Lambda function by setting the ProvisionedConcurrentExecutions parameter to 10.
- Enable cluster cache management for Aurora PostgreSQL. Change the connection string of each Lambda function to point to cluster cache management.
- 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.
- Configure reserved concurrency for each Lambda function by setting the ReservedConcurrentExecutions parameter to 10.
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