- A
Use a different AWS Region.
Why wrong: Different regions may have different limits but the root cause is account limit.
- B
Request a service limit increase for the instance type.
The error indicates the instance limit is reached; requesting an increase resolves it.
- C
Reduce the training dataset size.
Why wrong: The error is not about data size but about instance count limit.
- D
Switch to a different instance type with lower resource requirements.
Why wrong: This avoids the limit but does not increase capacity for the required instance type.
Question 1,082 of 1,755
Handling SageMaker ResourceLimitExceeded: How to Increase Your Instance Quota
This MLS-C01 practice question tests your understanding of machine learning implementation and operations. 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 SageMaker to train a model. The training job is failing with a 'ResourceLimitExceeded' error. Which action should be taken to resolve this issue?
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
✓
Request a service limit increase for the instance type.
The 'ResourceLimitExceeded' error in SageMaker indicates that the AWS account has reached the maximum number of allowed resources (e.g., instances, vCPUs, or storage) for a given instance type in the current region. Requesting a service limit increase via the AWS Service Quotas console or API directly resolves this by raising the cap for that specific instance type, allowing the training job to proceed.
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 different AWS Region.
Why it's wrong here
Different regions may have different limits but the root cause is account limit.
- ✓
Request a service limit increase for the instance type.
Why this is correct
The error indicates the instance limit is reached; requesting an increase resolves it.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Reduce the training dataset size.
Why it's wrong here
The error is not about data size but about instance count limit.
- ✗
Switch to a different instance type with lower resource requirements.
Why it's wrong here
This avoids the limit but does not increase capacity for the required instance type.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse 'ResourceLimitExceeded' with an out-of-memory or insufficient capacity error, leading them to choose dataset reduction or instance type changes instead of recognizing it as a quota-based limit that requires a service limit increase.
Detailed technical explanation
How to think about this question
AWS Service Quotas are per-account, per-region limits that govern resources like SageMaker training instances (e.g., ml.p3.2xlarge). The 'ResourceLimitExceeded' error is thrown when the requested number of instances exceeds the soft limit, which can be increased by submitting a support ticket or using the Service Quotas API. In practice, this error often occurs when running multiple concurrent training jobs or using large instance families (e.g., GPU instances) that have lower default quotas.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
Visual reference
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this MLS-C01 question test?
Machine Learning Implementation and Operations — This question tests Machine Learning Implementation and Operations — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Request a service limit increase for the instance type. — The 'ResourceLimitExceeded' error in SageMaker indicates that the AWS account has reached the maximum number of allowed resources (e.g., instances, vCPUs, or storage) for a given instance type in the current region. Requesting a service limit increase via the AWS Service Quotas console or API directly resolves this by raising the cap for that specific instance type, allowing the training job to proceed.
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.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 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.
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