~/gcp-pde · Maintain and automate data workloads ▊
GCP · objective · 20% of the exam
Maintain and automate data workloads — Professional Data Engineer
The official GCP documentation our Maintain and automate data workloads practice questions are cited to. Review the primary sources, then practise.
Official references for this objective
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Google Cloud — Cloud Data Fusion | Google Cloud
Design cost: based on the number of hours an instance is running and not the number of pipelines being developed and run.
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Google Cloud — Managed Service for Apache Airflow | Apache Airflow 3
Key enhancements include DAG versioning for auditability and confident rollbacks, alongside scheduler-managed backfills for simpler historical data reprocessing.
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Google Cloud — Cloud Scheduler documentation | Google Cloud Documentation
Learn how to use Cloud Scheduler and Cloud Run functions to automatically start and stop Cloud SQL instances on a regular schedule using resource labels.