The answer is to use Vertex AI Model Registry to deploy version v2 to a dedicated endpoint and update the model alias. This approach provides full resource isolation by moving the problematic model version to its own compute resources, preventing it from consuming CPU or memory that other versions on the shared endpoint need. In a multi-tenant serving system, a single endpoint with multiple model versions shares the underlying infrastructure, so a resource-heavy version like v2 can cause latency spikes across all deployments. On the Google Professional Machine Learning Engineer exam, this scenario tests your understanding of Vertex AI’s deployment architecture and the trade-off between endpoint consolidation and isolation. A common trap is assuming a load balancer or traffic splitting can isolate resource usage, but those only distribute requests, not compute resources. Remember the memory tip: “One endpoint, shared pain; separate endpoint, clean gain.”
PMLE Serving and scaling models Practice Question
This PMLE practice question tests your understanding of serving and scaling models. 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.
You manage a multi-tenant serving system on Vertex AI Prediction where multiple models are deployed in a single endpoint using model versioning. One particular model version (v2) is consuming excessive resources, causing latency spikes for other versions. You need to isolate this model to prevent interference. The models are all in TensorFlow SavedModel format. What is the best approach?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "best"
Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use Vertex AI Model Registry to deploy v2 to a dedicated endpoint and update the model alias.
Option B is correct because creating a separate endpoint for v2 provides full resource isolation. Option A is similar but less direct (load balancer still distributes to same endpoint). Option C is not possible in Vertex AI Prediction. Option D is complex and error-prone.
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.
✗
Shard the models across multiple replicas using a custom routing logic in the container.
Why it's wrong here
Complex and fragile; dedicated endpoint is simpler.
✗
Set resource limits on the container using Kubernetes resource requests/limits, but Vertex AI Prediction does not support that.
Why it's wrong here
Not supported in Vertex AI Prediction.
✓
Use Vertex AI Model Registry to deploy v2 to a dedicated endpoint and update the model alias.
Why this is correct
Dedicated endpoint ensures resource isolation.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Create a separate endpoint for v2 and redirect traffic using a load balancer.
Why it's wrong here
Involves additional routing complexity; B is more direct.
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: Use Vertex AI Model Registry to deploy v2 to a dedicated endpoint and update the model alias. — Option B is correct because creating a separate endpoint for v2 provides full resource isolation. Option A is similar but less direct (load balancer still distributes to same endpoint). Option C is not possible in Vertex AI Prediction. Option D is complex and error-prone.
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: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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