The answer is that the models are collocated on the same instances, leading to resource contention. When a multi-model endpoint on Vertex AI deploys both a small, low-latency model and a large, high-latency model on shared infrastructure, any traffic hitting the larger model consumes CPU and memory, starving the smaller model of resources and degrading its performance. This scenario directly tests your understanding of multi-model endpoint resource contention, a key concept in the Google Professional Machine Learning Engineer exam where you must distinguish between traffic splitting (which distributes requests) and resource isolation (which prevents interference). A common trap is assuming that traffic splitting alone guarantees performance isolation, but Vertex AI’s multi-model endpoint collocates models on the same instances unless you deploy separate endpoints. Memory tip: think of it as a shared apartment—when one roommate (Model B) throws a big party, the other (Model A) can’t study in peace.
PMLE Serving and scaling models Practice Question
This PMLE practice question tests your understanding of serving and scaling models. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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.
Your team deploys a multi-model endpoint on Vertex AI with two models: Model A (small, low latency) and Model B (large, high latency). You configure traffic splitting so that 90% goes to Model A and 10% to Model B. However, you notice that the latency for Model A increases when Model B receives traffic. What is the most likely cause?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The models are collocated on the same instances, leading to resource contention.
In a multi-model endpoint, all models share the underlying infrastructure. When Model B handles requests, it consumes resources (CPU/memory), causing contention that degrades Model A's latency. Collocation of models on the same instance is the issue.
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.
✗
Model A is being overloaded because autoscaling is based on aggregate traffic.
Why it's wrong here
Autoscaling usually monitors per-model metrics.
✗
The traffic split is misconfigured, causing requests to be routed incorrectly.
Why it's wrong here
Traffic split works correctly; latency increase due to contention.
✓
The models are collocated on the same instances, leading to resource contention.
Why this is correct
Multi-model endpoints share replicas; Model B's work impacts Model A.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Model B's logging is generating too much output, slowing down the predictor.
Why it's wrong here
Logging overhead is minimal and not model-specific in this case.
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.
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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
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.
Serving and scaling models — This question tests Serving and scaling models — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: The models are collocated on the same instances, leading to resource contention. — In a multi-model endpoint, all models share the underlying infrastructure. When Model B handles requests, it consumes resources (CPU/memory), causing contention that degrades Model A's latency. Collocation of models on the same instance is the issue.
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.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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