PMLE Monitoring ML Solutions Practice Question
An ML engineer manages a Vertex AI Endpoint serving a fraud detection model. Compliance requires that every prediction be logged with its input features for audit, but the team also wants to minimize storage costs. They decide to enable request-response logging on the endpoint. Which configuration should they use to meet both requirements?
⚠ Common exam trap
The trap here is focusing on sampling rates for cost savings when the compliance requirement explicitly demands that every prediction be logged, making any sampling below full capture incorrect.
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
✓
Enable request-response logging with a sampling rate of 1.0 and set the logging destination to a Cloud Storage bucket with a lifecycle policy to delete objects after 30 days.
Compliance requires that every prediction be logged with its input features, so the sampling rate must be 1.0. To minimize storage costs, logs should be stored in a cost-effective location such as Cloud Storage, with a lifecycle policy to delete after the required retention period. Sampling below 1.0 or using higher-cost logging services would either miss predictions or increase expenses, failing one of the stated requirements.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Enable request-response logging with a sampling rate of 0.1 and send logs to Cloud Logging.
Why it's wrong here
A sampling rate of 0.1 logs only about 10% of predictions, which fails the requirement that every prediction be logged for audit. Cloud Logging may also incur higher costs for long-term retention and is not ideal for large-scale audit storage. The scenario demands complete logging, so any sampling below 1.0 is unacceptable. This option does not meet the compliance requirement.
- ✗
Enable request-response logging with a sampling rate of 1.0 and send logs to Cloud Logging with a default retention of 30 days.
Why it's wrong here
Logging at 1.0 satisfies completeness, but Cloud Logging default retention is 30 days and is not designed for cost-effective long-term storage of high-volume prediction logs. The team wants to minimize storage costs; Cloud Logging can become expensive at scale. Cloud Storage with a lifecycle policy is more cost-effective for audit archives. Therefore, this option meets completeness but not the cost-minimization goal as well as the storage-bucket approach.
- ✗
Enable request-response logging with a sampling rate of 0.5 and configure a BigQuery sink for analysis.
Why it's wrong here
A sampling rate of 0.5 logs only half of predictions, violating the audit requirement. BigQuery is useful for analysis but not necessary here and may add cost. The primary need is complete logging with minimal storage expense. This option fails on completeness and does not directly address cost minimization for archival storage. The correct approach must log every prediction and use a low-cost storage tier with lifecycle management.
- ✓
Enable request-response logging with a sampling rate of 1.0 and set the logging destination to a Cloud Storage bucket with a lifecycle policy to delete objects after 30 days.
Why this is correct
A sampling rate of 1.0 logs every prediction, which satisfies the audit requirement that every prediction be recorded with its input features. Directing logs to Cloud Storage and applying a lifecycle policy to delete after 30 days controls storage costs while meeting the retention need. This combination ensures completeness for compliance and cost efficiency, unlike sampling or shorter retention that would violate the audit mandate.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Google Cloud exam blueprint
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.