Courseiva
Question 382 of 990
Collaborating to manage data and modelsmediumMultiple ChoiceObjective-mapped

PMLE Collaborating to manage data and models Practice Question

An organization uses Cloud Composer to orchestrate ML workflows. A DAG that triggers Vertex AI training jobs fails because the training job exceeds the 7-day maximum runtime. What is the best way to handle long-running training jobs in Cloud Composer?

⚠ Common exam trap

Candidates often assume increasing the Airflow execution timeout is a valid solution, but the PMLE exam tests understanding that Cloud Composer's architecture imposes practical limits on synchronous task execution, and the correct approach is to use asynchronous orchestration with services like Vertex AI Pipelines.

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 Vertex AI Pipeline to manage the training job asynchronously

Vertex AI Pipelines natively supports asynchronous execution, allowing Cloud Composer to trigger a pipeline and monitor its status without blocking the Airflow worker for the entire duration of the training job. This decouples the DAG execution timeout from the training runtime, enabling workflows that exceed the 7-day Airflow task timeout limit.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Increase the DAG execution timeout to 14 days in the Airflow configuration

    Why it's wrong here

    Cloud Composer has a 7-day limit for DAG runs, and increasing timeout may not be allowed.

  • Use Vertex AI Pipeline to manage the training job asynchronously

    Why this is correct

    Vertex AI Pipeline can handle long-running jobs independently of the DAG runtime.

  • Refactor the training job to run on Dataflow, which supports longer runtimes

    Why it's wrong here

    Dataflow is for data processing, not model training.

  • Set max_active_runs=1 in the DAG to prevent overlapping runs

    Why it's wrong here

    This does not address the runtime limit.

About these practice questions

Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →

How Courseiva writes practice questions · Editorial policy

Last reviewed: Jun 11, 2026

Question Discussion

Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.

Loading comments…

Sign in to join the discussion.

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.