The answer is to deploy one model per base model and use separate endpoints with routing logic per tenant. This approach is correct because it leverages dynamic routing to direct each tenant’s requests to an isolated endpoint while sharing the underlying base model, achieving both cost efficiency and strict data isolation. On the Microsoft Azure AI Engineer Associate AI-102 exam, this scenario tests your understanding of multi-tenant architecture patterns in Azure AI Foundry, where the common trap is confusing shared endpoints with tenant IDs in headers—that risks data leakage—or assuming each tenant needs its own fine-tuned model, which inflates costs. The key is remembering that isolation lives at the routing layer, not the model layer. Memory tip: “One model, many doors—route tenants to their own floor.”
AI-102 Implement generative AI solutions Practice Question
This AI-102 practice question tests your understanding of implement generative ai solutions. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 company is building a multi-tenant SaaS application using Azure AI Foundry. Each tenant (customer) should have isolated model deployments and data, but you want to share the base models across tenants to reduce costs. Which approach should you use?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Deploy one model per base model and use separate endpoints with routing logic per tenant.
Option D is correct because deploying a single model and using separate endpoints per tenant with dynamic routing enables isolation while sharing the base model. Option A is wrong because fine-tuned models per tenant increase costs. Option B is wrong because shared endpoints with tenant IDs in headers may cause data leakage. Option C is wrong because separate model deployments per tenant increases costs.
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.
✗
Use a single model deployment and a shared endpoint with tenant ID in the header.
Why it's wrong here
Shared endpoint may risk data leakage between tenants.
✗
Create separate fine-tuned models for each tenant.
Why it's wrong here
Fine-tuning per tenant increases cost and complexity.
✗
Deploy separate base models for each tenant.
Why it's wrong here
Separate deployments increase cost.
✓
Deploy one model per base model and use separate endpoints with routing logic per tenant.
Why this is correct
Separate endpoints with routing isolate tenants while sharing the model.
Related concept
Read the scenario before looking for a memorised answer.
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 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 AI-102 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.
Implement generative AI solutions — This question tests Implement generative AI solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Deploy one model per base model and use separate endpoints with routing logic per tenant. — Option D is correct because deploying a single model and using separate endpoints per tenant with dynamic routing enables isolation while sharing the base model. Option A is wrong because fine-tuned models per tenant increase costs. Option B is wrong because shared endpoints with tenant IDs in headers may cause data leakage. Option C is wrong because separate model deployments per tenant increases costs.
What should I do if I get this AI-102 question wrong?
Identify which AI-102 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.
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Question Discussion
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