PDE Ingesting and Processing the Data Practice Question
A data engineer is building a Dataflow pipeline that reads from BigQuery, transforms data using Apache Beam, and writes results to Cloud Storage in Avro format. They need to ensure the pipeline can be easily redeployed with different parameters without modifying code. Which deployment method should they use?
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
✓
Dataflow Flex Templates
Dataflow Flex Templates allow you to package a pipeline as a Docker image and pass runtime parameters, enabling parameterized deployments without code changes.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Dataflow Flex Templates
Why this is correct
Flex Templates use Docker images and support arbitrary pipeline options, including custom parameters.
- ✗
Direct deployment using the gcloud command with parameters
Why it's wrong here
This requires command-line parameters but does not provide a reusable template.
- ✗
Dataflow Classic Templates
Why it's wrong here
Classic Templates also support parameters but are limited to predefined templates and have less flexibility.
- ✗
Deploy as a Cloud Function triggered by Cloud Scheduler
Why it's wrong here
Cloud Functions are not suitable for long-running batch pipelines.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This PDE 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 PDE exam.