- A
dsl.Collected
Why wrong: dsl.Collected is for collecting outputs from parallel loops, not importing artifacts.
- B
dsl.importer
dsl.importer is used to import existing artifacts into a pipeline.
- C
dsl.Importer
Why wrong: The correct API is lowercase `importer`; `dsl.Importer` does not exist.
- D
dsl.Artifact
Why wrong: dsl.Artifact is a class for defining artifact types, not a component for importing.
Question 397 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 data scientist is defining a Vertex AI pipeline and needs to include a step that imports a pre-existing model from Cloud Storage into the pipeline as an artifact. Which Kubeflow Pipelines SDK v2 component 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
✓
dsl.importer
The `dsl.importer` component in Kubeflow Pipelines SDK v2 is specifically designed to import existing artifacts (such as models, datasets, or metrics) from external storage (e.g., Cloud Storage) into a pipeline as a pipeline artifact. It allows you to reference a pre-existing model without retraining or re-uploading, making it the correct choice for this use case.
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.
- ✗
dsl.Collected
Why it's wrong here
dsl.Collected is for collecting outputs from parallel loops, not importing artifacts.
- ✓
dsl.importer
Why this is correct
dsl.importer is used to import existing artifacts into a pipeline.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
dsl.Importer
Why it's wrong here
The correct API is lowercase `importer`; `dsl.Importer` does not exist.
- ✗
dsl.Artifact
Why it's wrong here
dsl.Artifact is a class for defining artifact types, not a component for importing.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse the Python class naming convention (capitalized `Importer`) with the actual SDK v2 function name (lowercase `importer`), or mistakenly think `dsl.Artifact` can import artifacts when it only defines the artifact schema.
Trap categories for this question
Command / output trap
dsl.Collected is for collecting outputs from parallel loops, not importing artifacts.
Detailed technical explanation
How to think about this question
Under the hood, `dsl.importer` creates an `ImporterSpec` that wraps a URI (e.g., `gs://bucket/model.pkl`) and an artifact type (e.g., `Model`), and it generates a pipeline task that produces an output artifact without executing any container. This is useful in scenarios where a model is trained externally or stored in a central registry, and you need to pass it as an input to downstream pipeline steps like evaluation or deployment.
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.
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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: dsl.importer — The `dsl.importer` component in Kubeflow Pipelines SDK v2 is specifically designed to import existing artifacts (such as models, datasets, or metrics) from external storage (e.g., Cloud Storage) into a pipeline as a pipeline artifact. It allows you to reference a pre-existing model without retraining or re-uploading, making it the correct choice for this use case.
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
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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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