- A
The type of machine learning model architecture (e.g., CNN vs RNN)
Why wrong: Both can be used in either mode.
- B
Cost per prediction: batch is often cheaper per request
Batch prediction is typically more cost-effective for large volumes.
- C
Latency requirements (real-time vs. asynchronous)
Online prediction requires low latency; batch can be delayed.
- D
Traffic pattern: sporadic vs. sustained load
Online prediction suits sustained or sporadic real-time; batch fits periodic large loads.
- E
Availability of GPU instances in the region
Why wrong: GPU availability affects both similarly.
Question 68 of 1,000
mediumMultiple SelectObjective-mapped
Online vs Batch Prediction on Vertex AI
This PMLE practice question tests your understanding of pmle exam topics. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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.
Which THREE factors should you consider when deciding between online prediction and batch prediction on Vertex AI?
Quick Answer
The answer is latency requirements, cost structure, and data volume patterns. These three factors are critical because online prediction demands low latency for real-time inference, typically using a deployed endpoint that incurs per-hour serving costs, while batch prediction processes large volumes asynchronously, often at a lower per-prediction cost but with higher latency. On the Google Professional Machine Learning Engineer exam, this question tests your ability to match deployment strategies to business constraints, often appearing as a scenario where you must choose between the two based on traffic patterns like sporadic versus sustained load. A common trap is confusing model architecture with prediction type—Vertex AI supports both online and batch for any model, so focus on operational needs instead. Remember the mnemonic “L-C-D”: Latency, Cost, and Data volume drive your decision.
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
✓
Cost per prediction: batch is often cheaper per request
Latency requirements, cost structure, and data volume patterns are key factors. Instance availability is similar for both; model architecture does not dictate prediction type.
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.
- ✗
The type of machine learning model architecture (e.g., CNN vs RNN)
Why it's wrong here
Both can be used in either mode.
- ✓
Cost per prediction: batch is often cheaper per request
Why this is correct
Batch prediction is typically more cost-effective for large volumes.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Latency requirements (real-time vs. asynchronous)
Why this is correct
Online prediction requires low latency; batch can be delayed.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Traffic pattern: sporadic vs. sustained load
Why this is correct
Online prediction suits sustained or sporadic real-time; batch fits periodic large loads.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Availability of GPU instances in the region
Why it's wrong here
GPU availability affects both similarly.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Trap categories for this question
Similar concept trap
GPU availability affects both similarly.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- 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 PMLE exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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FAQ
Questions learners often ask
What does this PMLE question test?
Read the scenario before looking for a memorised answer.
What is the correct answer to this question?
The correct answer is: Cost per prediction: batch is often cheaper per request — Latency requirements, cost structure, and data volume patterns are key factors. Instance availability is similar for both; model architecture does not dictate prediction type.
What should I do if I get this PMLE question wrong?
Identify which PMLE exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
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Last reviewed: Jun 24, 2026
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.
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