- A
Use a BranchPythonOperator to check the status of the Dataflow job before proceeding.
Why wrong: BranchPythonOperator is for conditional branching; not needed for a simple sequential dependency.
- B
Nest the tasks in a SubDAG with a schedule_interval that starts after the expected Dataflow completion time.
Why wrong: SubDAGs group tasks but do not enforce dependencies between tasks in the parent DAG.
- C
Set a TriggerRule on the Vertex AI pipeline task to 'all_done' and reference the previous task.
Why wrong: TriggerRule defines when a task should run based on upstream task statuses, but dependencies are still defined with bitshift operators.
- D
Use the bitshift operators (>>) to set the execution order: Dataflow_task >> VertexAI_pipeline.
The >> operator sets a direct dependency: VertexAI_pipeline runs only after Dataflow_task succeeds.
PMLE Automating and Orchestrating ML Pipelines Practice Question
This PMLE practice question tests your understanding of automating and orchestrating ml pipelines. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company uses Cloud Composer to orchestrate a nightly ML workflow that includes running a Vertex AI pipeline, querying BigQuery, and running a Dataflow job. The Airflow DAG must run only if the previous day's Dataflow job succeeded. Which Airflow concept should they use to implement this dependency?
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
Use the bitshift operators (>>) to set the execution order: Dataflow_task >> VertexAI_pipeline.
Option D is correct because Airflow's bitshift operators (>>) define task dependencies in a DAG. By setting `Dataflow_task >> VertexAI_pipeline`, the Vertex AI pipeline task will only execute after the Dataflow task has completed successfully. This directly enforces the required dependency without additional logic or branching.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use a BranchPythonOperator to check the status of the Dataflow job before proceeding.
Why it's wrong here
BranchPythonOperator is for conditional branching; not needed for a simple sequential dependency.
- ✗
Nest the tasks in a SubDAG with a schedule_interval that starts after the expected Dataflow completion time.
Why it's wrong here
SubDAGs group tasks but do not enforce dependencies between tasks in the parent DAG.
- ✗
Set a TriggerRule on the Vertex AI pipeline task to 'all_done' and reference the previous task.
Why it's wrong here
TriggerRule defines when a task should run based on upstream task statuses, but dependencies are still defined with bitshift operators.
- ✓
Use the bitshift operators (>>) to set the execution order: Dataflow_task >> VertexAI_pipeline.
Why this is correct
The >> operator sets a direct dependency: VertexAI_pipeline runs only after Dataflow_task succeeds.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests whether candidates understand that Airflow's default task dependency behavior (via bitshift operators) inherently enforces success-based execution, making explicit branching or trigger rule modifications unnecessary for simple sequential dependencies.
Detailed technical explanation
How to think about this question
In Airflow, bitshift operators (>> and <<) set upstream/downstream relationships between tasks, which are evaluated by the scheduler to determine execution order. The default TriggerRule is 'all_success', meaning downstream tasks only run if all upstream tasks succeeded. This behavior is fundamental to Airflow's dependency resolution and is the simplest, most reliable way to enforce sequential success-based dependencies in a DAG.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this PMLE question test?
Automating and Orchestrating ML Pipelines — This question tests Automating and Orchestrating ML Pipelines — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use the bitshift operators (>>) to set the execution order: Dataflow_task >> VertexAI_pipeline. — Option D is correct because Airflow's bitshift operators (>>) define task dependencies in a DAG. By setting `Dataflow_task >> VertexAI_pipeline`, the Vertex AI pipeline task will only execute after the Dataflow task has completed successfully. This directly enforces the required dependency without additional logic or branching.
What should I do if I get this PMLE question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
This PMLE practice question is part of Courseiva's free Google Cloud 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 PMLE exam.
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