Which solution will meet these requirements?
Refactor the Lambda function into two functions. Configure one function to transform the data and one function to load the data into the DynamoDB table. Create an Amazon Simple Queue Service (Amazon SQS) queue in between the functions to hold the items as messages and to invoke the second function.
Turn on auto scaling for the DynamoDB table. Use Amazon CloudWatch to monitor the table’s read and write capacity metrics and to track consumed capacity.
Create an alias for the Lambda function. Configure provisioned concurrency for the application to use.
Refactor the Lambda function into two functions. Configure one function to store the data in the DynamoDB table. Configure the second function to process the data and update the items after the data is stored in DynamoDB. Create a DynamoDB stream to invoke the second function after the data is stored.
Explanations:
This solution decouples the data transformation and loading processes. By using an Amazon SQS queue to hold items as messages, it smooths out the workload, reducing throttling by invoking the second function only when DynamoDB can handle the load.
Auto scaling will increase capacity in DynamoDB but may not address the immediate throttling issue, as it depends on the speed and reliability of the auto scaling adjustments, which may not handle sudden traffic spikes effectively.
Provisioned concurrency for Lambda ensures function availability but does not help with the throttling in DynamoDB. The throttling issue exists at the DynamoDB layer, not in Lambda concurrency.
This setup will introduce unnecessary complexity by creating a second function triggered by DynamoDB streams. This solution does not address the throttling issue, as the flow of data to DynamoDB remains subject to the same traffic spikes.
In my opinion, the answer is:
Refactor the Lambda function into two functions. Configure one function to transform the data and one function to load the data into the DynamoDB table. Create an Amazon Simple Queue Service (Amazon SQS) queue in between the functions to hold the items as messages and to invoke the second function.