Question 740 of 1,755
ModelingmediumMultiple ChoiceObjective-mapped

Quick Answer

The correct answer is that the training image URI is for a different AWS region. This error occurs because SageMaker validates that the specified Amazon ECR image URI is accessible from the region where the training job is launched; when the URI points to a repository in another region, SageMaker cannot resolve the image and throws the InvalidInstanceType exception, even though the instance type itself (like ml.m5.large) is perfectly valid for XGBoost. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this question tests your understanding of how SageMaker training jobs depend on regional resource alignment—a common trap is assuming the error is about instance availability when it is actually a cross-region URI mismatch. Remember the memory tip: "Region first, instance second"—always verify that your ECR image URI’s region matches the SageMaker job’s region before troubleshooting instance types.

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.

Exhibit

Refer to the exhibit.

$ aws sagemaker create-training-job \
    --training-job-name my-job \
    --algorithm-specification TrainingImage=382416733822.dkr.ecr.us-west-2.amazonaws.com/xgboost:latest,TrainingInputMode=File \
    --role-arn arn:aws:iam::123456789012:role/SageMakerRole \
    --input-data-config "[{\"ChannelName\": \"train\", \"DataSource\": {\"S3DataSource\": {\"S3DataType\": \"S3Prefix\", \"S3Uri\": \"s3://my-bucket/train/\", \"S3DataDistributionType\": \"FullyReplicated\"}}}]" \
    --output-data-config "{\"S3OutputPath\": \"s3://my-bucket/output/\"}" \
    --resource-config "{\"InstanceType\": \"ml.m5.large\", \"InstanceCount\": 1}" \
    --stopping-condition "{\"MaxRuntimeInSeconds\": 86400}"

Refer to the exhibit. A data scientist runs the AWS CLI command to create a SageMaker training job. The job fails immediately with 'ValidationException: Invalid instance type'. What is the most likely issue?

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.

  • Clue: "immediately / without restart"

    Why it matters: Time or reboot constraint — the correct answer must take effect right away without requiring a reboot or reload.

Question 1mediummultiple choice
Full question →

Exhibit

Refer to the exhibit.

$ aws sagemaker create-training-job \
    --training-job-name my-job \
    --algorithm-specification TrainingImage=382416733822.dkr.ecr.us-west-2.amazonaws.com/xgboost:latest,TrainingInputMode=File \
    --role-arn arn:aws:iam::123456789012:role/SageMakerRole \
    --input-data-config "[{\"ChannelName\": \"train\", \"DataSource\": {\"S3DataSource\": {\"S3DataType\": \"S3Prefix\", \"S3Uri\": \"s3://my-bucket/train/\", \"S3DataDistributionType\": \"FullyReplicated\"}}}]" \
    --output-data-config "{\"S3OutputPath\": \"s3://my-bucket/output/\"}" \
    --resource-config "{\"InstanceType\": \"ml.m5.large\", \"InstanceCount\": 1}" \
    --stopping-condition "{\"MaxRuntimeInSeconds\": 86400}"

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 training image URI is for a different AWS region

The error 'ValidationException: Invalid instance type' occurs because the training image URI specified in the command points to an Amazon ECR repository in a different AWS region than where the SageMaker training job is being created. SageMaker validates that the image URI is accessible from the current region; if the URI references a region that does not contain the XGBoost image or the instance type is not supported in that region's ECR, the validation fails. The instance type itself (ml.m5.large) is valid for XGBoost, but the mismatch between the image's region and the job's region triggers the exception.

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 IAM role ARN is invalid

    Why it's wrong here

    Would cause AccessDenied.

  • The S3 bucket 'my-bucket' does not exist or the role lacks permissions

    Why it's wrong here

    Would cause AccessDenied, not ValidationException.

  • The instance type ml.m5.large does not support the XGBoost image

    Why it's wrong here

    XGBoost supports ml.m5.large.

  • The training image URI is for a different AWS region

    Why this is correct

    The account ID corresponds to us-east-1, but the CLI command is running in us-west-2.

    Clue confirmation

    The clue words "most likely", "immediately / without restart" 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

The trap here is that candidates assume 'Invalid instance type' always means the instance is unsupported by the algorithm, when in reality SageMaker uses this generic error for any validation failure related to the training job's resource configuration, including regional mismatches in the image URI.

Detailed technical explanation

How to think about this question

SageMaker training jobs require the ECR image URI to be in the same region as the job, as the service pulls the container from the local regional registry. The image URI format is 'account_id.dkr.ecr.region.amazonaws.com/...'; if the region in the URI (e.g., 'us-west-2') differs from the job's region (e.g., 'us-east-1'), SageMaker's validation fails because it cannot resolve the registry endpoint in the current region. This is a common pitfall when copying commands from documentation or cross-region scripts without updating the region identifier.

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.

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.

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.

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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 training image URI is for a different AWS region — The error 'ValidationException: Invalid instance type' occurs because the training image URI specified in the command points to an Amazon ECR repository in a different AWS region than where the SageMaker training job is being created. SageMaker validates that the image URI is accessible from the current region; if the URI references a region that does not contain the XGBoost image or the instance type is not supported in that region's ECR, the validation fails. The instance type itself (ml.m5.large) is valid for XGBoost, but the mismatch between the image's region and the job's region triggers the exception.

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", "immediately / without restart". 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 24, 2026

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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.