A data pipeline uses AWS Glue to process data from an S3 data lake. The pipeline fails intermittently with a 'ThrottlingException' when writing to a DynamoDB table. What is the MOST likely cause?
ThrottlingException indicates the write capacity is exceeded; increasing capacity or using auto-scaling resolves it.
Why this answer
A ThrottlingException from DynamoDB indicates that the request rate to the table has exceeded the provisioned write capacity. AWS Glue jobs can generate high-throughput writes, and if the DynamoDB table's write capacity units (WCUs) are not sufficient to handle the burst, DynamoDB will throttle the requests. This is the most direct cause of the intermittent failure described.
Exam trap
The trap here is that candidates may confuse ThrottlingException with permission errors (Option D) or network issues (Option B), but AWS specifically tests the understanding that DynamoDB throttling is a capacity management mechanism, not a connectivity or authorization problem.
How to eliminate wrong answers
Option B is wrong because network instability between Glue and DynamoDB would typically result in connection timeouts or retryable network errors, not a specific ThrottlingException which is an application-level error from DynamoDB's API. Option C is wrong because a Glue job's timeout setting controls how long the job can run before being terminated, not how it handles individual API throttling errors; a timeout would cause a different error (e.g., 'Timeout exceeded'). Option D is wrong because insufficient IAM permissions would result in an AccessDeniedException, not a ThrottlingException; the error message directly indicates capacity limits, not authorization failures.