- A
Google Cloud Pipeline Components (GCPC) for custom containers
Why wrong: GCPC provides pre-built components for GCP services, not a generic container runner.
- B
Python function component using @dsl.component
Why wrong: Python function components run Python code, not arbitrary container images.
- C
Importer component to load the container as an artifact
Why wrong: Importer imports existing artifacts, not components.
- D
Container component using @dsl.container_component
Container components allow you to specify a Docker image that runs as a component.
Question 729 of 1,000
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 machine learning engineer needs to create a pipeline that runs a custom container component on Vertex AI. The container expects a Cloud Storage path as input and outputs a model artifact. Which component type should they define using the Kubeflow Pipelines SDK v2?
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
✓
Container component using @dsl.container_component
Option D is correct because the Kubeflow Pipelines SDK v2 provides the @dsl.container_component decorator specifically for defining components that wrap custom container images. This allows the engineer to specify the container image, input/output paths (like a Cloud Storage path), and artifact metadata, enabling Vertex AI to execute the container as a pipeline step and capture the model artifact.
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.
- ✗
Google Cloud Pipeline Components (GCPC) for custom containers
Why it's wrong here
GCPC provides pre-built components for GCP services, not a generic container runner.
- ✗
Python function component using @dsl.component
Why it's wrong here
Python function components run Python code, not arbitrary container images.
- ✗
Importer component to load the container as an artifact
Why it's wrong here
Importer imports existing artifacts, not components.
- ✓
Container component using @dsl.container_component
Why this is correct
Container components allow you to specify a Docker image that runs as a component.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse the Importer component (which only imports existing artifacts) with a component that runs a container to produce an artifact, or they mistakenly think Google Cloud Pipeline Components can wrap any custom container when they only provide pre-built Google service integrations.
Detailed technical explanation
How to think about this question
Under the hood, @dsl.container_component generates a component specification that includes the container image URI, command, arguments, and artifact declarations. The SDK compiles this into a pipeline JSON that Vertex AI interprets, mounting Cloud Storage paths as volumes and capturing output artifacts via metadata store URIs. A real-world scenario is deploying a custom training container that reads data from GCS and writes a model.pkl to a specified output path, which the pipeline then registers as a model artifact for serving.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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Automating and Orchestrating ML Pipelines — study guide chapter
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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: Container component using @dsl.container_component — Option D is correct because the Kubeflow Pipelines SDK v2 provides the @dsl.container_component decorator specifically for defining components that wrap custom container images. This allows the engineer to specify the container image, input/output paths (like a Cloud Storage path), and artifact metadata, enabling Vertex AI to execute the container as a pipeline step and capture the model artifact.
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.
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 →
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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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