PMLE Scaling Prototypes into ML Models Practice Question
A company wants to train a custom machine learning model on Vertex AI using a pre-built container for scikit-learn. They want to use spot VMs to reduce costs. However, the training job fails intermittently due to preemption. Which TWO actions should they take to ensure the training job completes successfully?
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 max_retry_count in the worker pool spec to a value greater than 0
To handle spot VM preemptions, the training job must be restartable. Using checkpoints allows the job to resume from the last saved state. Vertex AI automatically retries on preemption if the job is restartable (managed by the service). Setting max_retry_count in the worker pool spec allows Vertex AI to automatically restart the job after preemption. Also, reducing machine type or increasing parallel trials are not direct solutions.
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 larger machine type to reduce training time
Why it's wrong here
Larger machines are more expensive and preemptions are not mitigated.
- ✗
Increase the number of parallel trials in hyperparameter tuning
Why it's wrong here
This does not help with spot VM preemption; it's for hyperparameter tuning.
- ✗
Set the worker_pool_specs to use spot VMs by setting spot=True
Why it's wrong here
This enables spot VMs but does not ensure completion; it's a prerequisite, but not sufficient.
- ✓
Set the max_retry_count in the worker pool spec to a value greater than 0
Why this is correct
Vertex AI will retry the job if preempted up to max_retry_count times.
- ✓
Implement checkpointing in the training code to save model state periodically to Cloud Storage
Why this is correct
Checkpointing allows resumption after preemption.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.