DEA-C01 Data Ingestion and Transformation Practice Question
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?
⚠ Common exam trap
Test-takers frequently 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.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The DynamoDB table's write capacity is insufficient for the workload.
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.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
The DynamoDB table's write capacity is insufficient for the workload.
Why this is correct
DynamoDB returns ThrottlingException when write requests exceed the table's provisioned write capacity units. Intermittent failures during Glue writes indicate the table's write capacity is insufficient for the pipeline's throughput, not a code or schema fault.
- ✗
The network connection between Glue and DynamoDB is unstable.
Why it's wrong here
DynamoDB is reached over AWS's internal network via HTTPS; transient connectivity loss yields connection or timeout errors, not a service-generated ThrottlingException. Network instability is tempting because intermittent failures suggest transport faults, but it would be correct only if the errors were socket-level rather than API throttling.
- ✗
The Glue job's timeout setting is too low.
Why it's wrong here
A low timeout terminates the job with a timeout or state-change error, and it would fail consistently rather than intermittently. Timeout tuning is tempting for long-running Glue jobs, but it would be correct only when logs show the job exceeding its configured duration, not throttling responses.
- ✗
The Glue job does not have sufficient IAM permissions to write to DynamoDB.
Why it's wrong here
Insufficient IAM permissions produce AccessDeniedException, not ThrottlingException, so the symptom contradicts the cause. This option tempts because permission errors are the commonest Glue-to-DynamoDB write failure; it would be correct if the job returned explicit authorisation denials instead.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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