Question 125 of 507
Deployment and Orchestration of ML WorkflowsmediumMultiple ChoiceObjective-mapped

MLA-C01 Deployment and Orchestration of ML Workflows Practice Question

This MLA-C01 practice question tests your understanding of deployment and orchestration of ml workflows. 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.

Exhibit

Refer to the exhibit.
```
Pipeline definition snippet:
{
  "Steps": [
    {
      "Name": "Preprocess",
      "Type": "Processing",
      "Arguments": {
        "ProcessingResources": {
          "ClusterConfig": {
            "InstanceCount": 1,
            "InstanceType": "ml.m5.large",
            "VolumeSizeInGB": 10
          }
        }
      }
    },
    {
      "Name": "Train",
      "Type": "Training",
      "DependsOn": ["Preprocess"],
      "Arguments": {
        "AlgorithmSpecification": {
          "TrainingImage": "123456789012.dkr.ecr.us-east-1.amazonaws.com/my-training:latest",
          "TrainingInputMode": "File"
        },
        "ResourceConfig": {
          "InstanceCount": 2,
          "InstanceType": "ml.p3.2xlarge",
          "VolumeSizeInGB": 30
        }
      }
    }
  ]
}
```

A data scientist runs this pipeline but the Train step fails with "ResourceLimitExceeded". 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.

Question 1mediummultiple choice
Full question →

Exhibit

Refer to the exhibit.
```
Pipeline definition snippet:
{
  "Steps": [
    {
      "Name": "Preprocess",
      "Type": "Processing",
      "Arguments": {
        "ProcessingResources": {
          "ClusterConfig": {
            "InstanceCount": 1,
            "InstanceType": "ml.m5.large",
            "VolumeSizeInGB": 10
          }
        }
      }
    },
    {
      "Name": "Train",
      "Type": "Training",
      "DependsOn": ["Preprocess"],
      "Arguments": {
        "AlgorithmSpecification": {
          "TrainingImage": "123456789012.dkr.ecr.us-east-1.amazonaws.com/my-training:latest",
          "TrainingInputMode": "File"
        },
        "ResourceConfig": {
          "InstanceCount": 2,
          "InstanceType": "ml.p3.2xlarge",
          "VolumeSizeInGB": 30
        }
      }
    }
  ]
}
```

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 a limit of 0 for ml.p3.2xlarge instances.

The 'ResourceLimitExceeded' error indicates that the requested instance type (ml.p3.2xlarge) exceeds the account's service quota for that specific instance family. In AWS SageMaker, each account has a default limit of 0 for certain GPU instance types like ml.p3.2xlarge unless a quota increase has been requested and approved. This error occurs at the Train step because SageMaker attempts to launch the training job with an instance type that is not allowed by the current quota.

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 account has a limit of 0 for ml.p3.2xlarge instances.

    Why this is correct

    A zero limit or insufficient quota results in ResourceLimitExceeded.

    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 volume size is too small for training.

    Why it's wrong here

    Small volume would cause a disk full error, not ResourceLimitExceeded.

  • The Preprocess step did not complete successfully.

    Why it's wrong here

    Preprocess failure would cause a different error, not ResourceLimitExceeded.

  • The training image is not accessible.

    Why it's wrong here

    Inaccessible image causes a different error (e.g., image not found).

Common exam traps

Common exam trap: answer the scenario, not the keyword

AWS often tests the distinction between resource limits (quotas) and other failure modes; the trap here is that candidates may confuse 'ResourceLimitExceeded' with a generic 'insufficient capacity' error, but the error specifically refers to account-level service quotas, not AWS resource availability.

Detailed technical explanation

How to think about this question

AWS SageMaker service quotas are enforced at the account level per Region, and the default quota for GPU instances like ml.p3.2xlarge is often set to 0 to prevent accidental high-cost usage. The 'ResourceLimitExceeded' error is thrown by the SageMaker API when the DescribeTrainingJob call detects that the requested instance count would exceed the current quota. This is a common issue when migrating from CPU-based training to GPU-based training without first requesting a quota increase via the Service Quotas console or AWS Support.

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 company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.

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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Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.

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FAQ

Questions learners often ask

What does this MLA-C01 question test?

Deployment and Orchestration of ML Workflows — This question tests Deployment and Orchestration of ML Workflows — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: The account has a limit of 0 for ml.p3.2xlarge instances. — The 'ResourceLimitExceeded' error indicates that the requested instance type (ml.p3.2xlarge) exceeds the account's service quota for that specific instance family. In AWS SageMaker, each account has a default limit of 0 for certain GPU instance types like ml.p3.2xlarge unless a quota increase has been requested and approved. This error occurs at the Train step because SageMaker attempts to launch the training job with an instance type that is not allowed by the current quota.

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: Jun 30, 2026

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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.