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Data Pipeline OrchestrationeasyMultiple ChoiceObjective-mapped

GCP-ADP Data Pipeline Orchestration Practice Question

Which Cloud Composer metric should you monitor to identify if your Airflow scheduler is struggling to parse your DAGs in a timely manner?

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

dag_processing_total_parse_time

The 'dag_processing_total_parse_time' metric specifically tracks the time taken to process and parse DAG files.

Answer analysis

Option-by-option breakdown

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

  • airflow_task_execution_time

    Why it's wrong here

    This tracks how long actual tasks take, not the scheduling process.

  • dag_run_success_count

    Why it's wrong here

    This tracks business outcomes, not system performance.

  • dag_processing_total_parse_time

    Why this is correct

    This metric tracks DAG parsing performance.

  • scheduler_heartbeat

    Why it's wrong here

    This indicates if the scheduler is alive, not if it is efficient.

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JA

Written and reviewed by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

Last reviewed August 2026 · checked against the official Google Cloud exam blueprint

This GCP-ADP 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 GCP-ADP exam.