hardMultiple ChoiceObjective-mapped
PMLE Practice Question: A hospital wants to deploy a machine learning…
A hospital wants to deploy a machine learning model for detecting anomalies in patient vital signs. The model was trained on historical data but must comply with HIPAA regulations. The model serving must be low-latency (under 100 ms) and handle up to 1000 requests per second. Which architecture should they use on Google Cloud?
⚠ Common exam trap
Google Cloud often tests the distinction between batch and online prediction, and candidates mistakenly choose Cloud Run because it offers low latency, but they overlook the HIPAA data isolation requirement that VPC Service Controls uniquely satisfy in a managed ML context.
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
✓
Deploy the model to Vertex AI Prediction with a private endpoint and use VPC Service Controls for data isolation
Vertex AI Prediction with a private endpoint and VPC Service Controls meets all requirements: it provides low-latency (sub-100ms) online predictions for up to 1000 QPS, enforces HIPAA compliance by isolating the model within a VPC and preventing data exfiltration, and supports autoscaling. Batch Prediction (A) cannot meet the latency requirement, BigQuery ML (B) is designed for analytical queries not real-time serving, and Cloud Run (C) lacks native HIPAA-compliant data isolation controls.
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 Vertex AI Batch Prediction to run predictions in batch jobs every hour
Why it's wrong here
Batch prediction is not real-time; it would not meet the live monitoring requirement.
- ✗
Use BigQuery ML to run predictions directly from a BigQuery table
Why it's wrong here
BigQuery ML is for analytical queries, not real-time, low-latency serving.
- ✗
Deploy the model as a container on Cloud Run with a load balancer
Why it's wrong here
Cloud Run cold starts and scaling may cause latency spikes above 100 ms at high throughput.
- ✓
Deploy the model to Vertex AI Prediction with a private endpoint and use VPC Service Controls for data isolation
Why this is correct
Vertex AI Prediction with private endpoints offers low latency and VPC-SC provides HIPAA-compliant data boundaries.
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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.