Which solution will meet these requirements with the LEAST operational overhead?

Explanations:

Increasing the maximum timeout of the Lambda function may help if the function is timing out due to long processing times, but it does not address the root cause of failures. Checking AWS CloudTrail for error details is useful but can be labor-intensive and may not provide immediate insights into specific message processing issues.

Increasing the visibility timeout allows a message to remain invisible for a longer period if the Lambda function fails to process it. However, this does not resolve the issue of understanding why the function fails, and checking logs in CloudWatch may still require manual effort to identify problems.

Creating a dead-letter queue (DLQ) allows the Lambda function to automatically send failed messages to a separate SQS queue for further analysis, thereby reducing operational overhead. This solution provides a clear mechanism for handling failures and allows the developer to examine the messages that failed to process without additional manual steps.

While using a DynamoDB table to log failed messages could help in tracking issues, it introduces more operational overhead. The developer would need to manage the DynamoDB table and ensure proper error handling and logging, which can complicate the architecture unnecessarily compared to using a DLQ.