DEA-C01 Data Operations and Support Practice Question
A data engineering team notices that an AWS Glue ETL job fails intermittently with a 'ThrottlingException' error. The job reads from an Amazon S3 bucket and writes to an Amazon Redshift table. What is the MOST likely cause of this error?
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 Redshift cluster's write throughput is exceeding its provisioned capacity.
The 'ThrottlingException' error occurs when the rate of API requests exceeds the allowed limit. In this scenario, the Glue job writes to Amazon Redshift. Redshift has a provisioned write throughput capacity; if the Glue job attempts to write data faster than Redshift can handle, Redshift throttles the requests, resulting in a ThrottlingException. This is the most likely cause. Option A is incorrect because S3 throttling would manifest as a different error (e.g., 'SlowDown' or 'RequestTimeout'). Option C is incorrect because Glue job concurrency limits would cause a 'ConcurrentRunsExceededException' or similar, not ThrottlingException. Option D is incorrect because insufficient memory would typically lead to an 'OutOfMemoryError' or job failure, not a ThrottlingException.
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 S3 bucket's request rate is exceeding the bucket's performance limits.
Why it's wrong here
S3 scales to high request rates; throttling would be due to other factors.
- ✓
The Redshift cluster's write throughput is exceeding its provisioned capacity.
Why this is correct
Redshift throttles writes when the cluster's I/O capacity is exceeded.
- ✗
The Glue job is exceeding the maximum number of concurrent runs allowed.
Why it's wrong here
Concurrent run limits cause job queuing, not ThrottlingException during data operations.
- ✗
The Glue job's allocated memory is insufficient for the data volume.
Why it's wrong here
Insufficient memory leads to OOM errors, not ThrottlingException.
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 |
Go deeper
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DEA-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DEA-C01 exam.