- A
Use AWS Lambda with SageMaker
Why wrong: Lambda is for serverless compute but not designed for real-time model serving with scaling based on latency.
- B
Provision a fixed number of instances with Multi-Model Endpoints
Why wrong: Fixed instances do not scale automatically, potentially wasting resources or causing underprovisioning.
- C
Use a single large instance to handle peak traffic
Why wrong: This is overprovisioned during low traffic and may still be insufficient during spikes.
- D
Configure automatic scaling with a target tracking metric based on latency
Target tracking scaling adjusts instance count based on a metric like latency, optimizing cost and performance.
Question 357 of 1,000
AI0-001 AI Infrastructure and Technologies Practice Question
This AI0-001 practice question tests your understanding of ai infrastructure and technologies. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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.
A team is deploying a model on AWS SageMaker and needs to handle variable traffic patterns with automatic scaling based on request latency. They want to minimize costs during low traffic. Which endpoint configuration should they use?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"minimum / minimize"Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
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
✓
Configure automatic scaling with a target tracking metric based on latency
Option D is correct because SageMaker's automatic scaling with a target tracking metric based on latency allows the endpoint to dynamically adjust the number of instances in response to real-time request latency, ensuring cost efficiency during low traffic while maintaining performance during spikes. This approach uses a predefined or custom metric (e.g., SageMakerVariantInvocationsPerInstance) to trigger scaling policies, minimizing over-provisioning and idle 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 AWS Lambda with SageMaker
Why it's wrong here
Lambda is for serverless compute but not designed for real-time model serving with scaling based on latency.
- ✗
Provision a fixed number of instances with Multi-Model Endpoints
Why it's wrong here
Fixed instances do not scale automatically, potentially wasting resources or causing underprovisioning.
- ✗
Use a single large instance to handle peak traffic
Why it's wrong here
This is overprovisioned during low traffic and may still be insufficient during spikes.
- ✓
Configure automatic scaling with a target tracking metric based on latency
Why this is correct
Target tracking scaling adjusts instance count based on a metric like latency, optimizing cost and performance.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the misconception that Multi-Model Endpoints (Option B) provide automatic scaling, but they only optimize model hosting density, not dynamic instance scaling based on latency.
Detailed technical explanation
How to think about this question
SageMaker automatic scaling uses Application Auto Scaling with a target tracking policy that adjusts the desired instance count based on a chosen metric, such as average latency or invocations per instance, maintaining a target value (e.g., 500 ms latency). Under the hood, it integrates with CloudWatch alarms and step scaling policies, but target tracking simplifies this by continuously calculating the required capacity. A real-world scenario is an e-commerce site with flash sales: latency-based scaling ensures the endpoint adds instances before latency degrades user experience, then scales down during off-peak hours to save costs.
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 practitioner preparing for the AI0-001 exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
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.
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FAQ
Questions learners often ask
What does this AI0-001 question test?
AI Infrastructure and Technologies — This question tests AI Infrastructure and Technologies — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Configure automatic scaling with a target tracking metric based on latency — Option D is correct because SageMaker's automatic scaling with a target tracking metric based on latency allows the endpoint to dynamically adjust the number of instances in response to real-time request latency, ensuring cost efficiency during low traffic while maintaining performance during spikes. This approach uses a predefined or custom metric (e.g., SageMakerVariantInvocationsPerInstance) to trigger scaling policies, minimizing over-provisioning and idle costs.
What should I do if I get this AI0-001 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Last reviewed: Jul 4, 2026
This AI0-001 practice question is part of Courseiva's free CompTIA 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 AI0-001 exam.
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