Question 1

How many questions are on the Apache Airflow DAG Authoring exam?

Accepted Answer

Our record lists 75 questions for the Apache Airflow DAG Authoring. The vendor does not publish a question count, so treat that as a working figure rather than an official specification.

Question 2

How long do you have to complete the Apache Airflow DAG Authoring exam?

Accepted Answer

Our record lists 60 minutes, roughly 48 seconds per question. The vendor does not publish a duration for this exam, so use it as a planning figure.

Question 3

What score do you need to pass the Apache Airflow DAG Authoring exam?

Accepted Answer

Our record lists 70% as the pass mark for the Apache Airflow DAG Authoring. Most certification bodies do not publish a numeric cut score, so treat this as our benchmark rather than an official threshold.

Question 4

What are the domains on the Apache Airflow DAG Authoring exam?

Accepted Answer

There are 5 domains: Operators and Hooks, Advanced DAG Authoring, Deployment and Security, DAG Development Fundamentals, Testing and Quality Assurance. The official weights are Operators and Hooks 25%, Advanced DAG Authoring 25%, Deployment and Security 10%, DAG Development Fundamentals 25%, Testing and Quality Assurance 15%.

Question 5

How should I use the domain weights when revising?

Accepted Answer

Weight by percentage, not by domain. 25% is the one where lost points cost you the most, and Certilum scores you per domain so you can see exactly where that is.

Question 6

Does Certilum have practice questions for the Apache Airflow DAG Authoring exam?

Accepted Answer

Yes: 75 questions in our bank for this certification, each tagged to the exam domain it belongs to, with the official domain weights applied.

Specification	Value
Questions	75
Time limit	60 minutes (48s per question)
Passing score	70%
Domains	5
Level	Associate
Question bank here	75 questions
Source	Certilum's own record — the vendor does not publish this figure

Domain	Weight	Topics	Practice Qs
Operators and Hooks	25%	Using built-in operators (PythonOperator, BashOperator, PostgresOperator) Creating and customizing task-level parameters and templates Implementing sensors and timeouts +2 more	19
Advanced DAG Authoring	25%	Designing dynamic DAGs and parameterized templates Implementing branching, triggers, and conditional logic Understanding TaskFlow API and the @dag and @task decorators +2 more	19
Deployment and Security	10%	Managing environment variables and secrets Configuring role-based access controls (RBAC) for DAGs Packaging DAGs for Astronomer deployments +2 more	7
DAG Development Fundamentals	25%	Defining DAGs using Python and context managers Configuring default_args and DAG parameters Understanding the role of the Airflow Scheduler and Executor +2 more	19
Testing and Quality Assurance	15%	Writing unit tests for DAGs and operators Using the Airflow LocalExecutor and test configurations Implementing DAG validation and linting (pytest-airflow) +2 more	11

Apache Airflow DAG Authoring Exam Format

Exam facts at a glance

Official domain weights

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