- A
dsl.If
Why wrong: dsl.If is for conditional execution, not parallelism.
- B
dsl.Parallel
Why wrong: There is no dsl.Parallel construct in KFP SDK v2.
- C
A for loop in the pipeline function that creates multiple tasks
You can use a Python for loop to generate multiple task invocations, effectively creating parallel tasks.
- D
dsl.Pipeline
Why wrong: dsl.Pipeline is a decorator for the pipeline function, not for parallel execution.
- E
dsl.Collected
dsl.Collected is used to collect results from a parallel loop created by dsl.ParallelFor or similar.
Question 860 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.
An ML engineer is creating a Vertex AI Pipeline that includes a loop to train multiple models in parallel on different hyperparameter sets. Which TWO KFP SDK v2 constructs can be used to implement this parallel execution?
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
✓
A for loop in the pipeline function that creates multiple tasks
Option C is correct because in KFP SDK v2, you can use a Python for loop inside the pipeline function to dynamically create multiple task instances, each with different hyperparameter sets. These tasks are then executed in parallel by the Vertex AI Pipelines orchestrator, as long as there are no data dependencies between them. This pattern leverages the SDK's ability to compile Python control flow into a directed acyclic graph (DAG) of pipeline steps.
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.If
Why it's wrong here
dsl.If is for conditional execution, not parallelism.
- ✗
dsl.Parallel
Why it's wrong here
There is no dsl.Parallel construct in KFP SDK v2.
- ✓
A for loop in the pipeline function that creates multiple tasks
Why this is correct
You can use a Python for loop to generate multiple task invocations, effectively creating parallel tasks.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
dsl.Pipeline
Why it's wrong here
dsl.Pipeline is a decorator for the pipeline function, not for parallel execution.
- ✓
dsl.Collected
Why this is correct
dsl.Collected is used to collect results from a parallel loop created by dsl.ParallelFor or similar.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the misconception that a dedicated 'Parallel' construct exists in KFP SDK v2, when in fact parallel execution is achieved through Python loops or the dsl.ParallelFor component, and candidates may confuse dsl.ParallelFor with the nonexistent dsl.Parallel.
Detailed technical explanation
How to think about this question
Under the hood, KFP SDK v2 compiles the pipeline function into an IR (Intermediate Representation) YAML that defines the DAG. When a Python for loop creates multiple tasks, each task becomes a separate node in the DAG, and the orchestrator schedules them concurrently if they have no upstream dependencies. A real-world scenario is hyperparameter tuning, where you train models with different learning rates and batch sizes simultaneously to speed up experimentation.
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.
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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: A for loop in the pipeline function that creates multiple tasks — Option C is correct because in KFP SDK v2, you can use a Python for loop inside the pipeline function to dynamically create multiple task instances, each with different hyperparameter sets. These tasks are then executed in parallel by the Vertex AI Pipelines orchestrator, as long as there are no data dependencies between them. This pattern leverages the SDK's ability to compile Python control flow into a directed acyclic graph (DAG) of pipeline steps.
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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