The answer is that automatic scaling is not configured for the endpoint. This is the most likely reason because a SageMaker endpoint without an Application Auto Scaling policy will stubbornly remain at its initial instance count, even under heavy traffic load—the service simply has no instruction to add instances. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this scenario tests your understanding of the difference between endpoint status (InService) and scaling behavior; a common trap is assuming a healthy status means scaling is active. Remember, an endpoint can be InService and still fail to scale if no scaling policy is attached. Memory tip: InService does not mean AutoScale—if you see traffic but no growth, check the scaling policy first.
MLS-C01 Modeling Practice Question
This MLS-C01 practice question tests your understanding of modeling. 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.
Network Topology
Refer to the exhibit. A data scientist checks the status of a SageMaker endpoint and sees the output above. The endpoint is receiving traffic, but the data scientist notices that the number of instances has not increased to the desired count. What is the most likely reason?
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
✓
Automatic scaling is not configured for the endpoint
Option D is correct because the endpoint is receiving traffic but not scaling out, which indicates that automatic scaling (Application Auto Scaling) has not been configured for the SageMaker endpoint. Without a scaling policy, the endpoint will only use the initial instance count, regardless of traffic load. The status shown does not indicate any update or quota issue, so the lack of scaling is the most likely cause.
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.
✗
The endpoint is performing a rolling update
Why it's wrong here
No evidence of rolling update; status is InService.
✗
The endpoint is currently being updated
Why it's wrong here
The status is InService, not Updating.
✗
The account has reached its instance limit
Why it's wrong here
If limit exceeded, the endpoint status would show a failure.
✓
Automatic scaling is not configured for the endpoint
Why this is correct
The desired instance count will not be applied automatically without a scaling policy; it's just a target.
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.
Common exam traps
Common exam trap: answer the scenario, not the keyword
AWS often tests the distinction between endpoint status (e.g., 'InService' vs. 'Updating') and scaling configuration, trapping candidates who assume that any traffic increase automatically triggers scaling without an explicit scaling policy.
Trap categories for this question
Command / output trap
If limit exceeded, the endpoint status would show a failure.
Detailed technical explanation
How to think about this question
SageMaker endpoints use Application Auto Scaling with target tracking, step, or scheduled policies to dynamically adjust instance count based on CloudWatch metrics like InvocationsPerInstance or CPUUtilization. Without a registered scalable target and scaling policy, the endpoint will only use the initial instance count specified at creation, even under heavy load. In production, this is a common misconfiguration that leads to throttling or latency spikes, as the endpoint cannot react to traffic surges.
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 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 exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Modeling — This question tests Modeling — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Automatic scaling is not configured for the endpoint — Option D is correct because the endpoint is receiving traffic but not scaling out, which indicates that automatic scaling (Application Auto Scaling) has not been configured for the SageMaker endpoint. Without a scaling policy, the endpoint will only use the initial instance count, regardless of traffic load. The status shown does not indicate any update or quota issue, so the lack of scaling is the most likely cause.
What should I do if I get this MLS-C01 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: "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.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. Refer to the exhibit. A data scientist checks the status of a SageMaker endpoint and sees the output above. What does this indicate?
easy
A.The endpoint has failed
B.The endpoint is running at full capacity
C.The endpoint is out of service
✓ D.The endpoint is scaling up to meet desired capacity
Why D: Option B is correct because the endpoint is InService but the current instance count (2) is less than the desired count (5), indicating scaling is in progress. Option A is wrong because the status is InService, not OutOfService. Option C is wrong because the endpoint is running but at lower capacity. Option D is wrong because the endpoint is not failed.
Last reviewed: Jun 30, 2026
Question Discussion
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This MLS-C01 practice question is part of Courseiva's free Amazon Web Services 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 MLS-C01 exam.
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