DEA-C01 Data Operations and Support Practice Question
A data engineer is using Amazon Managed Workflows for Apache Airflow (MWAA) to orchestrate a data pipeline. The pipeline includes a task that runs an AWS Glue job. The engineer notices that the Glue job occasionally fails due to transient issues, and the Airflow task fails immediately without retrying. The engineer wants to configure the Airflow task to retry the Glue job up to 2 times with a 5-minute delay between retries. Which configuration in the Airflow DAG should the engineer use?
⚠ Common exam trap
Watch out — candidates often confuse retry configuration at the orchestration layer (Airflow) with retry settings on the Glue job itself, leading to attempts to set non-existent Glue parameters.
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
✓
Set retries=2 and retry_delay=timedelta(minutes=5) in the default_args dictionary.
In Amazon MWAA, retry behavior for tasks is controlled by Airflow's built-in retry parameters. Setting retries and retry_delay in default_args applies to all tasks, including those running Glue jobs. This ensures that transient failures are retried with the specified delay, improving pipeline resilience.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Set retries=2 and retry_delay=timedelta(minutes=5) in the default_args dictionary.
Why this is correct
In Apache Airflow, the retries and retry_delay parameters in default_args control the number of retries and the delay between them for all tasks in the DAG. Setting retries to 2 and retry_delay to 5 minutes will automatically retry the failed Glue job task up to two times with the specified delay. This is the standard way to configure retry behavior in Airflow.
- ✗
Set max_retries=2 and retry_interval=300 in the Glue job's default arguments.
Why it's wrong here
AWS Glue jobs do not have max_retries or retry_interval parameters in their default arguments. Retry logic for Airflow tasks must be configured within Airflow, not in the Glue job. Setting these would have no effect, and the task would still fail without retries, causing pipeline failures.
- ✗
Use the retry_exponential_backoff=True parameter in the DAG definition.
Why it's wrong here
The retry_exponential_backoff parameter enables exponential backoff for retries, but it does not set the number of retries or a fixed delay. The requirement is for a fixed 5-minute delay and exactly 2 retries. Exponential backoff would increase the delay between retries, which is not what is needed here.
- ✗
Configure the Airflow task to use the GlueJobOperator with retry_limit=2 and retry_delay=300.
Why it's wrong here
The GlueJobOperator does not have retry_limit or retry_delay parameters. Retry configuration in Airflow is done via the task's retries and retry_delay attributes, typically set in default_args or per task. Using non-existent parameters would not enable retries and could cause DAG parsing errors.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Amazon Web Services exam blueprint
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.