- A
The algorithm's learning rate is too high
Why wrong: Learning rate affects training dynamics, not resource limits.
- B
The dataset is too large for the instance
Why wrong: If the dataset is too large, the job would likely fail with an out-of-memory error, not ResourceLimitExceeded.
- C
The training script has a syntax error
Why wrong: A syntax error would result in a ScriptError or ClientError, not ResourceLimitExceeded.
- D
The account's instance limit for the chosen instance type has been reached
ResourceLimitExceeded indicates the account has exceeded the allowed number of instances for that instance type.
Question 609 of 1,000
mediumMultiple ChoiceObjective-mapped
SageMaker ResourceLimitExceeded Error Cause
This MLA-C01 practice question tests your understanding of mla-c01 exam topics. 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.
During model training on Amazon SageMaker, the training job fails with a 'ResourceLimitExceeded' error. What is the most likely cause?
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's instance limit for the chosen instance type has been reached
The 'ResourceLimitExceeded' error in Amazon SageMaker indicates that the AWS account has reached its service quota for the specified instance type. Each AWS account has default limits on the number of concurrent instances (e.g., ml.p3.2xlarge) that can be used for training jobs. When a training job requests more instances than the account's limit allows, SageMaker throws this error. This is distinct from dataset size or algorithmic issues.
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 algorithm's learning rate is too high
Why it's wrong here
Learning rate affects training dynamics, not resource limits.
- ✗
The dataset is too large for the instance
Why it's wrong here
If the dataset is too large, the job would likely fail with an out-of-memory error, not ResourceLimitExceeded.
- ✗
The training script has a syntax error
Why it's wrong here
A syntax error would result in a ScriptError or ClientError, not ResourceLimitExceeded.
- ✓
The account's instance limit for the chosen instance type has been reached
Why this is correct
ResourceLimitExceeded indicates the account has exceeded the allowed number of instances for that instance type.
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 resource-level errors (quotas) versus data-level or code-level errors; the trap here is confusing a 'ResourceLimitExceeded' error with a dataset size issue or a training script bug, leading candidates to pick Option B or C.
Detailed technical explanation
How to think about this question
AWS service quotas (formerly called limits) for SageMaker are per-region and per-instance-family. For example, the default limit for ml.p3.2xlarge is typically 1 or 2 instances. You can request a quota increase via the Service Quotas console. The error is thrown at the API level when SageMaker attempts to provision the compute resources, before any training code runs. This is different from Amazon EC2 limits, as SageMaker has its own separate quotas for training jobs, endpoint instances, and notebook instances.
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.
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FAQ
Questions learners often ask
What does this MLA-C01 question test?
Read the scenario before looking for a memorised answer.
What is the correct answer to this question?
The correct answer is: The account's instance limit for the chosen instance type has been reached — The 'ResourceLimitExceeded' error in Amazon SageMaker indicates that the AWS account has reached its service quota for the specified instance type. Each AWS account has default limits on the number of concurrent instances (e.g., ml.p3.2xlarge) that can be used for training jobs. When a training job requests more instances than the account's limit allows, SageMaker throws this error. This is distinct from dataset size or algorithmic issues.
What should I do if I get this MLA-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.
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Last reviewed: Jul 4, 2026
This MLA-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 MLA-C01 exam.
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