- A
Set a higher min replica count (e.g., 3)
Why wrong: Wastes resources during low traffic.
- B
Enable autoscaling with minReplicaCount=1 and maxReplicaCount=10
Autoscaling adjusts replicas based on load, balancing latency and cost.
- C
Use a larger machine type (e.g., n1-highmem-8)
Why wrong: May reduce latency but does not autoscale, and can be costly.
- D
Switch to batch prediction to handle spikes
Why wrong: Batch prediction is not real-time.
Question 30 of 1,000
PDE Operationalizing machine learning models Practice Question
This PDE practice question tests your understanding of operationalizing machine learning models. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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 production model deployed on Vertex AI Endpoint is experiencing high latency during traffic spikes. The current configuration uses a single replica. What is the most efficient solution?
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 autoscaling with minReplicaCount=1 and maxReplicaCount=10
Option B is correct because enabling autoscaling with minReplicaCount=1 and maxReplicaCount=10 allows Vertex AI Endpoint to dynamically add replicas during traffic spikes, distributing inference requests across multiple instances and reducing latency. This is the most efficient solution as it scales resources up only when needed, avoiding over-provisioning and minimizing cost during low traffic periods.
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.
- ✗
Set a higher min replica count (e.g., 3)
Why it's wrong here
Wastes resources during low traffic.
- ✓
Enable autoscaling with minReplicaCount=1 and maxReplicaCount=10
Why this is correct
Autoscaling adjusts replicas based on load, balancing latency and cost.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use a larger machine type (e.g., n1-highmem-8)
Why it's wrong here
May reduce latency but does not autoscale, and can be costly.
- ✗
Switch to batch prediction to handle spikes
Why it's wrong here
Batch prediction is not real-time.
Common exam traps
Common exam trap: answer the scenario, not the keyword
A common mistake is thinking that manually increasing the minimum replica count or using a larger machine type (static scaling) is the best way to reduce latency during spikes. However, Vertex AI Endpoint's autoscaling (with minReplicaCount=1 and maxReplicaCount=10) dynamically adjusts replicas based on traffic, avoiding over-provisioning and reducing cost. This is a key operational excellence principle in Google Cloud: design for elasticity.
Detailed technical explanation
How to think about this question
Vertex AI Endpoint autoscaling uses the Horizontal Pod Autoscaler (HPA) under the hood, which monitors CPU utilization or custom metrics (e.g., request latency) to adjust the number of replicas. The scaling decision is based on the ratio of current utilization to the target utilization (default 60%), and it can take up to 30 seconds to provision new replicas, so pre-warming with a minReplicaCount of 1 and a reasonable max ensures cost-efficiency while handling sudden bursts. In real-world scenarios, combining autoscaling with a load balancer (e.g., Google Cloud HTTP(S) Load Balancer) can further distribute traffic and reduce tail latency.
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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Questions learners often ask
What does this PDE question test?
Operationalizing machine learning models — This question tests Operationalizing machine learning models — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Enable autoscaling with minReplicaCount=1 and maxReplicaCount=10 — Option B is correct because enabling autoscaling with minReplicaCount=1 and maxReplicaCount=10 allows Vertex AI Endpoint to dynamically add replicas during traffic spikes, distributing inference requests across multiple instances and reducing latency. This is the most efficient solution as it scales resources up only when needed, avoiding over-provisioning and minimizing cost during low traffic periods.
What should I do if I get this PDE 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.
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Last reviewed: Jul 4, 2026
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