A company is building a serverless data ingestion pipeline. IoT devices send data to an Amazon API Gateway endpoint, which triggers an AWS Lambda function. The Lambda function processes the data and writes it to an Amazon Aurora Serverless v2 database. During load testing, the database connections are exhausted, causing the Lambda functions to fail. How can the Architect resolve this issue with the LEAST architectural changes?

Answer options:

Implement Amazon RDS Proxy between the Lambda functions and the Aurora database.

Increase the maximum capacity of the Aurora Serverless v2 cluster to 128 ACUs.

Replace API Gateway and Lambda with Amazon Kinesis Data Firehose to write directly to Aurora.

Configure the Lambda function to use provisioned concurrency.

How to approach this question

Identify the AWS service designed specifically to manage database connections for serverless applications.

Full Answer

A.Implement Amazon RDS Proxy between the Lambda functions and the Aurora database.✓ Correct

Implement Amazon RDS Proxy between the Lambda functions and the Aurora database.

AWS Lambda functions can scale to thousands of concurrent executions in seconds. Relational databases (like Aurora) have a hard limit on the number of concurrent connections they can handle. This mismatch causes connection exhaustion. Amazon RDS Proxy is a fully managed, highly available database proxy that pools and shares database connections, allowing serverless applications to scale massively without overwhelming the database.

Common mistakes

Thinking scaling up the database compute (ACUs) is the best way to handle connection exhaustion.

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