- A
Use dsl.Condition (deprecated) or dsl.If to check metrics and conditionally run deployment.
dsl.If is the correct way to add conditional logic in KFP v2.
- B
Use dsl.ParallelFor to evaluate and deploy in parallel.
Why wrong: ParallelFor is for loops, not conditional branching.
- C
Use an exit handler to deploy regardless of metrics.
Why wrong: Exit handlers run after pipeline termination, not conditionally.
- D
Split the pipeline into two separate pipelines and run the second only if metrics are good.
Why wrong: This is inefficient and not as integrated; conditional logic within a single pipeline is preferred.
Question 207 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 team has a pipeline that trains a model and then evaluates it. They want to conditionally deploy the model to a staging endpoint only if evaluation metrics exceed a threshold. Which KFP feature 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
✓
Use dsl.Condition (deprecated) or dsl.If to check metrics and conditionally run deployment.
Option A is correct because KFP provides `dsl.Condition` (deprecated) and `dsl.If` as first-class pipeline constructs to conditionally execute pipeline components based on runtime metrics or other pipeline outputs. By wrapping the deployment step inside a `dsl.If` block that checks whether evaluation metrics exceed a threshold, the pipeline can deploy the model to a staging endpoint only when the condition is met, avoiding unnecessary deployments for underperforming models.
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 dsl.Condition (deprecated) or dsl.If to check metrics and conditionally run deployment.
Why this is correct
dsl.If is the correct way to add conditional logic in KFP v2.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use dsl.ParallelFor to evaluate and deploy in parallel.
Why it's wrong here
ParallelFor is for loops, not conditional branching.
- ✗
Use an exit handler to deploy regardless of metrics.
Why it's wrong here
Exit handlers run after pipeline termination, not conditionally.
- ✗
Split the pipeline into two separate pipelines and run the second only if metrics are good.
Why it's wrong here
This is inefficient and not as integrated; conditional logic within a single pipeline is preferred.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google often tests the distinction between conditional execution (`dsl.If`) and unconditional execution patterns (exit handlers, parallel loops), tempting candidates to choose a pattern that always runs the deployment step or runs it in parallel without any gate.
Detailed technical explanation
How to think about this question
Under the hood, `dsl.If` compiles into a Kubernetes `Conditional` resource that uses Argo Workflows' `when` field to gate downstream steps based on the output of upstream components. This allows the pipeline to skip the deployment component entirely if the metric threshold is not met, without incurring compute costs or triggering side effects. A real-world scenario is a model retraining pipeline that only promotes a new version to staging if validation accuracy exceeds 95%, preventing regressions from reaching production-like 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 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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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: Use dsl.Condition (deprecated) or dsl.If to check metrics and conditionally run deployment. — Option A is correct because KFP provides `dsl.Condition` (deprecated) and `dsl.If` as first-class pipeline constructs to conditionally execute pipeline components based on runtime metrics or other pipeline outputs. By wrapping the deployment step inside a `dsl.If` block that checks whether evaluation metrics exceed a threshold, the pipeline can deploy the model to a staging endpoint only when the condition is met, avoiding unnecessary deployments for underperforming models.
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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