- A
The training job is using spot instances; switch to on-demand instances.
Why wrong: No indication of spot instance usage.
- B
The instance type is not available in the current region; switch to a different region.
Why wrong: The error is about service limits, not availability.
- C
The account has not requested a limit increase for ml.p3.8xlarge; submit a limit increase request via AWS Support.
ResourceLimitExceeded indicates the current limit is zero; a limit increase is needed.
- D
The instance type is too large; use a smaller instance type like ml.m5.large.
Why wrong: The error is about limit, not size; smaller instance may also have zero limit.
Quick Answer
The correct answer is to submit a limit increase request via AWS Support, because the error message explicitly states that the account-level service limit for ml.p3.8xlarge for training job usage is 0, meaning the account has never been granted any capacity for that instance type. AWS enforces service quotas per account per region, and for GPU-intensive instances like ml.p3.8xlarge, the default limit is often set to zero unless a formal limit increase has been requested and approved. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this scenario tests your understanding of SageMaker service limits versus resource exhaustion—a common trap is confusing a ResourceLimitExceeded error with insufficient instance availability or spot instance interruptions, when the real issue is a quota that hasn’t been raised. Remember the key distinction: a limit of 0 means no capacity has been allocated, not that capacity is temporarily unavailable. Memory tip: “Zero quota means zero chance—request a raise before you train.”
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.
A data scientist is using Amazon SageMaker to train a neural network. The training job fails with the error 'ResourceLimitExceeded: The account-level service limit for ml.p3.8xlarge for training job usage is 0.' What is the most likely cause and solution?
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 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
The account has not requested a limit increase for ml.p3.8xlarge; submit a limit increase request via AWS Support.
The error message explicitly states that the account-level service limit for ml.p3.8xlarge for training job usage is 0, which means the account has not been granted any capacity for that instance type. AWS enforces service quotas (limits) per account per region, and for GPU-intensive instances like ml.p3.8xlarge, the default limit is often 0 unless a limit increase request has been submitted and approved. Therefore, the correct solution is to request a limit increase via AWS Support.
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 training job is using spot instances; switch to on-demand instances.
Why it's wrong here
No indication of spot instance usage.
- ✗
The instance type is not available in the current region; switch to a different region.
Why it's wrong here
The error is about service limits, not availability.
- ✓
The account has not requested a limit increase for ml.p3.8xlarge; submit a limit increase request via AWS Support.
Why this is correct
ResourceLimitExceeded indicates the current limit is zero; a limit increase is needed.
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.
- ✗
The instance type is too large; use a smaller instance type like ml.m5.large.
Why it's wrong here
The error is about limit, not size; smaller instance may also have zero limit.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse a service limit error with instance availability or spot instance issues, but the specific phrase 'limit is 0' directly points to an unrequested quota increase, not a regional or pricing model problem.
Detailed technical explanation
How to think about this question
AWS service quotas are enforced at the account level per region, and for GPU instances (e.g., P3, P4, G4dn), the default limit is often set to 0 to prevent accidental provisioning of expensive resources. The limit increase request must be submitted through the AWS Service Quotas console or via AWS Support, and approval can take minutes to days depending on the instance type and region. In SageMaker, the same quota applies to both training jobs and notebook instances, so a limit increase for training usage also covers other SageMaker workloads using that instance type.
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 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 exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
- →
Modeling — study guide chapter
Learn the concepts, then practise the questions
- →
Modeling practice questions
Targeted practice on this topic area only
- →
All MLS-C01 questions
1,755 questions across all exam domains
- →
AWS Certified Machine Learning Specialty MLS-C01 study guide
Full concept coverage aligned to exam objectives
- →
MLS-C01 practice test guide
How to use practice tests most effectively before exam day
Related practice questions
Related MLS-C01 practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
Data Engineering practice questions
Practise MLS-C01 questions linked to Data Engineering.
Machine Learning Implementation and Operations practice questions
Practise MLS-C01 questions linked to Machine Learning Implementation and Operations.
Modeling practice questions
Practise MLS-C01 questions linked to Modeling.
Exploratory Data Analysis practice questions
Practise MLS-C01 questions linked to Exploratory Data Analysis.
MLS-C01 fundamentals practice questions
Practise MLS-C01 questions linked to MLS-C01 fundamentals.
MLS-C01 scenario practice questions
Practise MLS-C01 questions linked to MLS-C01 scenario.
MLS-C01 troubleshooting practice questions
Practise MLS-C01 questions linked to MLS-C01 troubleshooting.
Practice this exam
Start a free MLS-C01 practice session
Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.
FAQ
Questions learners often ask
What does this MLS-C01 question test?
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: The account has not requested a limit increase for ml.p3.8xlarge; submit a limit increase request via AWS Support. — The error message explicitly states that the account-level service limit for ml.p3.8xlarge for training job usage is 0, which means the account has not been granted any capacity for that instance type. AWS enforces service quotas (limits) per account per region, and for GPU-intensive instances like ml.p3.8xlarge, the default limit is often 0 unless a limit increase request has been submitted and approved. Therefore, the correct solution is to request a limit increase via AWS Support.
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 →
Keep practising
More MLS-C01 practice questions
- A company is using Amazon Kinesis Data Streams to ingest real-time clickstream data. The data is consumed by a Lambda fu…
- A team is building a data pipeline to process terabytes of log data daily using Amazon EMR. The data arrives in 5-minute…
- A data science team is building a real-time fraud detection system. Transactions are streamed via Amazon Kinesis Data St…
- A company uses Amazon SageMaker to train and deploy machine learning models. The training data is stored in Amazon S3 (P…
- A data engineer is building a data pipeline to process user clickstream data. The data arrives as JSON files in an S3 bu…
- A data engineering team is designing a data lake on AWS for machine learning workloads. The data includes structured, se…
Last reviewed: Jun 24, 2026
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.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.