AI-102 Implement computer vision solutions Practice Question
This AI-102 practice question tests your understanding of implement computer vision solutions. 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.
You are deploying a Custom Vision model to an Azure Machine Learning managed endpoint using the above ARM template snippet. The deployment fails with a timeout error. Which parameter should you adjust?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Increase scoringTimeout to 'PT10M'
The deployment fails due to a timeout error, which indicates that the model inference is taking longer than the default scoring timeout (typically 5 seconds for Azure ML managed endpoints). Increasing the scoringTimeout parameter to 'PT10M' (ISO 8601 duration for 10 minutes) extends the allowed time for the endpoint to respond, resolving the timeout without altering compute or authentication settings.
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.
✗
Change model version to 2
Why it's wrong here
Version change unrelated to timeout.
✗
Change compute to 'GPU'
Why it's wrong here
May improve speed but timeout is the issue.
✗
Change authMode to 'AAD'
Why it's wrong here
Authentication mode doesn't affect timeout.
✓
Increase scoringTimeout to 'PT10M'
Why this is correct
Extends timeout to accommodate slow inference.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse timeout errors with performance issues and incorrectly choose GPU compute (Option B), not realizing that the default timeout is a hard limit that must be explicitly increased via the scoringTimeout parameter.
Detailed technical explanation
How to think about this question
Azure ML managed endpoints enforce a default scoring timeout of 5 seconds for HTTP requests, defined in ISO 8601 format (e.g., 'PT5S'). For Custom Vision models with complex preprocessing or large images, inference can exceed this limit, causing a 504 Gateway Timeout. The scoringTimeout parameter in the ARM template overrides this default, allowing longer-running requests; values must be specified as ISO 8601 durations (e.g., 'PT10M' for 10 minutes).
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 company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.
Visual reference
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.
Implement computer vision solutions — This question tests Implement computer vision solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Increase scoringTimeout to 'PT10M' — The deployment fails due to a timeout error, which indicates that the model inference is taking longer than the default scoring timeout (typically 5 seconds for Azure ML managed endpoints). Increasing the scoringTimeout parameter to 'PT10M' (ISO 8601 duration for 10 minutes) extends the allowed time for the endpoint to respond, resolving the timeout without altering compute or authentication settings.
What should I do if I get this AI-102 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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Question Discussion
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