- A
Use a startup script in the training VM to install libraries from Artifact Registry.
Why wrong: Startup scripts can be overridden or modified.
- B
Use Vertex AI Pipelines with a component that pulls libraries from Artifact Registry at runtime.
Why wrong: Pulling at runtime could still allow unapproved libraries if the pipeline is modified.
- C
Create a custom Vertex AI training container that installs libraries from Artifact Registry at build time and restrict training job submission to that container using IAM.
This encapsulates libraries in the container and controls usage.
- D
Configure Vertex AI Training with a custom job configuration that specifies the library sources.
Why wrong: Job configuration can be bypassed.
- E
Use Cloud Build to build the training image with approved libraries and push to Container Registry, then restrict training jobs to that image.
Why wrong: Container Registry is deprecated; Artifact Registry is preferred. Also, proper IAM on image is needed.
Quick Answer
The correct approach is to create a custom Vertex AI training container that installs libraries from Artifact Registry at build time and restrict training job submission to that container using IAM. This enforces approved libraries by shifting compliance to the image layer, where dependencies are frozen during the Docker build process, preventing any runtime injection of unapproved packages through startup scripts or pip install commands. On the Google Professional Machine Learning Engineer exam, this tests your understanding of immutable infrastructure for ML training and how IAM can gate container usage—a common trap is thinking that runtime scanning or post-hoc auditing is sufficient, but the exam emphasizes prevention over detection. Remember the memory tip: “Build-time lock, IAM the key” to recall that compliance is sealed at image creation, not at execution.
PMLE Practice Question: Collaborating within and across teams to manage data and models
This PMLE practice question tests your understanding of collaborating within and across teams to manage data and models. 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 company uses Vertex AI Experiments to track ML training runs. They want to enforce that all training runs use only approved libraries from a central Artifact Registry to ensure compliance. Which approach should they take?
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
Create a custom Vertex AI training container that installs libraries from Artifact Registry at build time and restrict training job submission to that container using IAM.
Option C is correct because it enforces compliance at the image level: by building a custom container that installs only approved libraries from Artifact Registry at build time, and then restricting training job submission to that specific container using IAM, you ensure that no unauthorized libraries can be introduced at runtime. This approach eliminates the risk of developers injecting unapproved dependencies via startup scripts or runtime pulls, and it aligns with the principle of immutable infrastructure for ML training.
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.
- ✗
Use a startup script in the training VM to install libraries from Artifact Registry.
Why it's wrong here
Startup scripts can be overridden or modified.
- ✗
Use Vertex AI Pipelines with a component that pulls libraries from Artifact Registry at runtime.
Why it's wrong here
Pulling at runtime could still allow unapproved libraries if the pipeline is modified.
- ✓
Create a custom Vertex AI training container that installs libraries from Artifact Registry at build time and restrict training job submission to that container using IAM.
Why this is correct
This encapsulates libraries in the container and controls usage.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Configure Vertex AI Training with a custom job configuration that specifies the library sources.
Why it's wrong here
Job configuration can be bypassed.
- ✗
Use Cloud Build to build the training image with approved libraries and push to Container Registry, then restrict training jobs to that image.
Why it's wrong here
Container Registry is deprecated; Artifact Registry is preferred. Also, proper IAM on image is needed.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse runtime library installation (options A, B, D) with build-time image hardening (option C), overlooking that only a pre-built, IAM-restricted container can truly prevent unauthorized dependencies from being loaded during training.
Detailed technical explanation
How to think about this question
Under the hood, Vertex AI Training uses the `workerPoolSpecs.containerSpec.imageUri` field to specify the container image for each worker. By setting IAM roles such as `aiplatform.customJobs.create` with a condition that restricts `resource.imageUri` to a specific Artifact Registry path (e.g., `location-docker.pkg.dev/project/repo/image:tag`), you enforce that only the approved container can be used. This approach also leverages Docker’s layer caching and Artifact Registry’s vulnerability scanning to maintain a secure, auditable lineage of training environments.
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 company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.
What to study next
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FAQ
Questions learners often ask
What does this PMLE question test?
Collaborating within and across teams to manage data and models — This question tests Collaborating within and across teams to manage data and models — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Create a custom Vertex AI training container that installs libraries from Artifact Registry at build time and restrict training job submission to that container using IAM. — Option C is correct because it enforces compliance at the image level: by building a custom container that installs only approved libraries from Artifact Registry at build time, and then restricting training job submission to that specific container using IAM, you ensure that no unauthorized libraries can be introduced at runtime. This approach eliminates the risk of developers injecting unapproved dependencies via startup scripts or runtime pulls, and it aligns with the principle of immutable infrastructure for ML training.
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.
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Last reviewed: Jun 24, 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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