Question 1,637 of 1,755
Machine Learning Implementation and OperationseasyMultiple ChoiceObjective-mapped

Quick Answer

The answer is that the endpoint name is not specified in the configuration, but this is actually not a missing field—it is the correct behavior. The endpoint configuration object itself only requires at least one production variant, which includes the model name and instance count, both of which are present here. The endpoint name is a separate parameter provided when you call the CreateEndpoint API, not a field inside the endpoint configuration. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this question tests your understanding of the distinction between the endpoint configuration resource and the endpoint resource itself, a common trap where candidates assume the endpoint name belongs inside the config. A reliable memory tip is to think of the endpoint configuration as a reusable blueprint: you define the model, instance type, and count in the blueprint, but you give the actual endpoint its name when you build the house.

MLS-C01 Practice Question: Machine Learning Implementation and Operations

This MLS-C01 practice question tests your understanding of machine learning implementation and operations. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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.

{
  "EndpointConfigName": "my-endpoint-config",
  "ProductionVariants": [
    {
      "VariantName": "variant1",
      "ModelName": "my-model",
      "InitialInstanceCount": 1,
      "InstanceType": "ml.m5.large"
    }
  ]
}

A SageMaker endpoint configuration is shown in the exhibit. The company wants to deploy the model to a real-time endpoint. What is missing from this configuration to successfully create the endpoint?

Question 1easymultiple choice
Full question →

Exhibit

Refer to the exhibit.

{
  "EndpointConfigName": "my-endpoint-config",
  "ProductionVariants": [
    {
      "VariantName": "variant1",
      "ModelName": "my-model",
      "InitialInstanceCount": 1,
      "InstanceType": "ml.m5.large"
    }
  ]
}

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 endpoint name is not specified in the configuration

Option C is correct because the endpoint configuration requires at least one production variant, which is present, but the endpoint name is specified when creating the endpoint, not in the config. Option A is wrong because the model name is specified. Option B is wrong because instance count is set. Option D is wrong because accelerator type is optional. Option E is wrong because data capture config is optional.

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 model name is missing

    Why it's wrong here

    ModelName is present.

  • The endpoint name is not specified in the configuration

    Why this is correct

    Endpoint name is provided when creating the endpoint, not in the config.

    Related concept

    Read the scenario before looking for a memorised answer.

  • The initial instance count is missing

    Why it's wrong here

    InitialInstanceCount is set to 1.

  • The accelerator type is missing

    Why it's wrong here

    Accelerator type is optional.

  • The data capture configuration is missing

    Why it's wrong here

    Data capture is optional.

Common exam traps

Common exam trap: answer the scenario, not the keyword

Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.

Detailed technical explanation

How to think about this question

This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.

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.
  • Use explanations to understand the rule behind the answer.

TExam Day Tips

  • Underline the problem statement mentally.
  • 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 MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.

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?

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: The endpoint name is not specified in the configuration — Option C is correct because the endpoint configuration requires at least one production variant, which is present, but the endpoint name is specified when creating the endpoint, not in the config. Option A is wrong because the model name is specified. Option B is wrong because instance count is set. Option D is wrong because accelerator type is optional. Option E is wrong because data capture config is optional.

What should I do if I get this MLS-C01 question wrong?

Identify which MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Last reviewed: Jun 20, 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.