- A
Deploy the component as a Cloud Function and configure Cloud Functions retry.
Why wrong: Cloud Functions retry is for event-driven functions, not for KFP components running on Vertex AI.
- B
Wrap the component in a `dsl.If` conditional that checks for failure and re-submits the component.
Why wrong: dsl.If is for conditional execution, not retries; manual re-submission is not automatic.
- C
Use Cloud Composer with a task retry policy in Airflow.
Why wrong: Cloud Composer is not used in this scenario; the question is about Vertex AI Pipelines native retry.
- D
Set the `retry` parameter of the component to a positive integer, for example `retry=3`.
The `retry` parameter in the component decorator or constructor enables automatic retries.
Question 935 of 1,000
PMLE Automating and Orchestrating ML Pipelines Practice Question
This PMLE practice question tests your understanding of automating and orchestrating ml pipelines. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 Pipelines to train models on a daily schedule. The pipeline includes a component that runs a BigQuery query to extract features. The team wants to ensure that if the BigQuery component fails due to transient network errors, the pipeline automatically retries it. How can they configure retries in Vertex AI Pipelines?
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
✓
Set the `retry` parameter of the component to a positive integer, for example `retry=3`.
Option D is correct because Vertex AI Pipelines natively supports a `retry` parameter on pipeline components. Setting `retry=3` instructs the pipeline to automatically retry the component up to three times if it fails due to transient errors, such as network timeouts. This is the simplest and most direct way to handle retries within the Vertex AI Pipelines orchestration framework.
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.
- ✗
Deploy the component as a Cloud Function and configure Cloud Functions retry.
Why it's wrong here
Cloud Functions retry is for event-driven functions, not for KFP components running on Vertex AI.
- ✗
Wrap the component in a `dsl.If` conditional that checks for failure and re-submits the component.
Why it's wrong here
dsl.If is for conditional execution, not retries; manual re-submission is not automatic.
- ✗
Use Cloud Composer with a task retry policy in Airflow.
Why it's wrong here
Cloud Composer is not used in this scenario; the question is about Vertex AI Pipelines native retry.
- ✓
Set the `retry` parameter of the component to a positive integer, for example `retry=3`.
Why this is correct
The `retry` parameter in the component decorator or constructor enables automatic retries.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse Vertex AI Pipelines' native `retry` parameter with external retry mechanisms (Cloud Functions, Airflow) or misuse pipeline control flow constructs like `dsl.If` for retry logic, when the correct approach is a simple parameter on the component definition.
Trap categories for this question
Scenario analysis trap
Cloud Composer is not used in this scenario; the question is about Vertex AI Pipelines native retry.
Detailed technical explanation
How to think about this question
Under the hood, Vertex AI Pipelines uses the Kubeflow Pipelines SDK, where the `retry` parameter is implemented as a Kubernetes pod annotation that controls the number of retries for a container execution. The retry count applies to the component's container exit code; if the container exits with a non-zero code, the pipeline re-executes the container up to the specified number of times. In a real-world scenario, transient BigQuery query failures due to network blips or quota exhaustion are common, and setting `retry=3` with an exponential backoff (default behavior) can significantly improve pipeline reliability without manual intervention.
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 healthcare organisation deploys an application with a public-facing web tier and a private database tier. The database subnet has no public IP and only accepts connections from the web tier's security group. Questions like this test whether you can design cloud network isolation using VNets/VPCs, subnets, and security group rules.
What to study next
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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: Set the `retry` parameter of the component to a positive integer, for example `retry=3`. — Option D is correct because Vertex AI Pipelines natively supports a `retry` parameter on pipeline components. Setting `retry=3` instructs the pipeline to automatically retry the component up to three times if it fails due to transient errors, such as network timeouts. This is the simplest and most direct way to handle retries within the Vertex AI Pipelines orchestration framework.
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
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