Question 104 of 506
Automating and orchestrating ML pipelinesmediumMultiple ChoiceObjective-mapped

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.

An ML team is using Vertex AI Pipelines to automate model training and deployment. They want to reuse components across multiple pipelines. What is the best practice for managing component code?

Clue words in this question

Noticing these words before you look at the options changes how you read each choice.

  • Clue: "best"

    Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.

Question 1mediummultiple choice
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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

Store components as container images in Artifact Registry and reference them from pipelines

Option E is correct because Vertex AI Pipelines natively supports reusable components by packaging them as container images stored in Artifact Registry. This allows teams to version, share, and reference components across multiple pipelines without duplicating code, ensuring consistency and reducing maintenance overhead. Container images encapsulate the component's runtime environment and logic, making them portable and independently deployable.

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.

  • Define components inline in the pipeline definition

    Why it's wrong here

    Not reusable across pipelines.

  • Embed component code in Cloud Composer DAGs

    Why it's wrong here

    Cloud Composer is for orchestration, not component definition.

  • Copy the component definitions into each pipeline's YAML file

    Why it's wrong here

    Duplicates code, hard to maintain.

  • Use Cloud Functions to define components

    Why it's wrong here

    Cloud Functions are not designed for pipeline components.

  • Store components as container images in Artifact Registry and reference them from pipelines

    Why this is correct

    Centralized, versioned, reusable.

    Clue confirmation

    The clue word "best" in the question point toward this answer.

    Related concept

    Read the scenario before looking for a memorised answer.

Common exam traps

Common exam trap: answer the scenario, not the keyword

Google Cloud often tests the misconception that inline definitions or YAML duplication are acceptable for reuse, but the trap here is that candidates overlook the requirement for versioned, decoupled, and independently deployable components, which only container images in a registry can provide.

Detailed technical explanation

How to think about this question

Under the hood, Vertex AI Pipelines uses the Kubeflow Pipelines SDK, where components are defined as containerized operations. Storing components as container images in Artifact Registry leverages OCI (Open Container Initiative) standards, enabling precise version pinning via tags or digests (e.g., us-central1-docker.pkg.dev/my-project/my-repo/my-component:v1). This approach also supports caching of component outputs based on the container image digest, improving pipeline execution efficiency. In a real-world scenario, a team might maintain a shared repository of curated components (e.g., data validation, feature engineering, model evaluation) that multiple pipelines reference, ensuring that updates to a component are propagated only when the image tag is updated.

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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.

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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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: Store components as container images in Artifact Registry and reference them from pipelines — Option E is correct because Vertex AI Pipelines natively supports reusable components by packaging them as container images stored in Artifact Registry. This allows teams to version, share, and reference components across multiple pipelines without duplicating code, ensuring consistency and reducing maintenance overhead. Container images encapsulate the component's runtime environment and logic, making them portable and independently deployable.

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.

Are there clue words in this question I should notice?

Yes — watch for: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Last reviewed: Jun 30, 2026

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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.