MLS-C01 exam dumps

MLS-C01 practice question 320 of 389

AWS Certified Machine Learning - Specialty. Expert level, Amazon Web Services. Free question with the correct answer and a full explanation.

MLS-C01 Question 320

Select 2

You are deploying a machine learning model using Amazon SageMaker and notice that your training job fails due to a 'ResourceLimitExceeded' error. Upon investigation, you find that the instance type you are using has hit its service quota for your AWS account in that region. What steps can you take to resolve this issue?

  1. A

    Request a service quota increase for the specific instance type from the AWS Service Quotas console.

  2. B

    Switch to a different instance type that has available capacity in your current quota.

  3. C

    Manually terminate other running instances in your account to free up capacity for the training job.

  4. D

    Enable auto-scaling for your SageMaker training job to dynamically adjust quotas.

  5. E

    Contact AWS Support to request a temporary bypass of the service quota limit.

Show answer and explanation

Correct answers: A, B

Explanation

AWS service quotas define the maximum number of resources you can provision for a specific service in a region. When you encounter a 'ResourceLimitExceeded' error, you can resolve it either by requesting a service quota increase or by switching to a different instance type with available capacity. Terminating other instances, auto-scaling, or bypassing quotas are not valid solutions to this issue.

  • A. Correct.

    This is a correct step. You can request a service quota increase for the specific instance type from the AWS Service Quotas console or through the AWS Management Console.

  • B. Correct.

    This is a correct step. You can opt for a different instance type that has sufficient capacity within your existing service quota.

  • C. Incorrect.

    This is incorrect. Terminating other instances does not affect the service quota limits set by AWS for your account.

  • D. Incorrect.

    This is incorrect. Auto-scaling is not applicable to SageMaker training jobs and does not influence service quotas.

  • E. Incorrect.

    This is incorrect. AWS Support does not provide temporary bypasses for service quota limits. You must either request an increase or adjust your instance usage.

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