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.
Explanations:
Configuring provisioned concurrency ensures that a set number of Lambda instances are always warm and ready to handle requests. However, it does not inherently reduce the number of database connections being made; each provisioned instance may still create separate connections, thus not addressing the underlying issue of excessive database connections.
Enabling cluster cache management for Aurora PostgreSQL allows for improved query performance by caching results, but it does not specifically manage or pool database connections. Therefore, while it can enhance performance, it does not reduce the number of connections made by the Lambda functions.
Using Amazon RDS Proxy provides a connection pooling mechanism that allows Lambda functions to reuse database connections rather than establishing a new one for each invocation. This reduces the number of connections to the database while maintaining scalability for the Lambda functions.
Configuring reserved concurrency limits the number of concurrent executions for a specific Lambda function. While this may prevent excessive scaling and can indirectly reduce the number of connections, it does not manage connections effectively. It can also lead to underutilization of Lambda functions and may limit scalability, as fewer concurrent executions could slow down processing.