The correct answer is that the TrainingStep fails because it expects a single artifact as input, but the preceding TuningStep produces multiple artifacts. In SageMaker Pipelines, a TuningStep launches multiple training jobs to find the best hyperparameters, and each job generates its own output artifact. When a downstream TrainingStep is configured to receive a single artifact reference—for example, using a `TrainingInput` that points to a specific property—the pipeline cannot resolve which of the multiple artifacts to pass, triggering the 'Invalid output reference' error. On the AWS Certified Machine Learning Engineer Associate MLA-C01 exam, this scenario tests your understanding of how pipeline step outputs are typed and referenced; a common trap is assuming TuningStep behaves like a single TrainingStep. Remember that TuningStep outputs are a list of artifacts, not a single one. Memory tip: "Tuning yields many, Training expects one—if you don't index, the pipeline is done."
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.
Refer to the exhibit. A SageMaker Pipeline fails with 'Invalid output reference' at the TrainingStep. 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 the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The TrainingStep expects a single artifact but TuningStep produces multiple
Option C is correct because in SageMaker Pipelines, a `TrainingStep` that expects a single artifact as input will fail with 'Invalid output reference' if the preceding `TuningStep` produces multiple artifacts (e.g., from multiple training jobs). The pipeline cannot resolve which specific artifact to pass, causing the error.
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 TuningStep output name is misspelled
Why it's wrong here
A misspelling would cause an 'undefined reference' error, not 'invalid output reference'.
✗
The pipeline role lacks permissions
Why it's wrong here
Permission errors would show access denied, not invalid reference.
✓
The TrainingStep expects a single artifact but TuningStep produces multiple
Why this is correct
Tuning step outputs multiple models; directly passing to training step causes ambiguity.
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 instance type is incompatible
Why it's wrong here
Instance type issues cause resource errors, not invalid output reference.
Common exam traps
Common exam trap: answer the scenario, not the keyword
AWS often tests the subtle distinction between output reference errors caused by naming mismatches versus those caused by cardinality mismatches, where candidates mistakenly focus on permissions or spelling instead of the pipeline's inability to handle multiple artifacts.
Trap categories for this question
Command / output trap
A misspelling would cause an 'undefined reference' error, not 'invalid output reference'.
Detailed technical explanation
How to think about this question
Under the hood, SageMaker Pipeline steps use `PropertyFile` or `JsonGet` to reference specific outputs. When a `TuningStep` runs multiple training jobs, it produces a list of model artifacts; the `TrainingStep` must use a `JsonGet` expression with a specific index (e.g., `$.TuningStep.OutputData[0].ModelArtifacts`) to disambiguate. Without this, the pipeline validation fails because it cannot map a single expected artifact to multiple candidates.
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.
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 TrainingStep expects a single artifact but TuningStep produces multiple — Option C is correct because in SageMaker Pipelines, a `TrainingStep` that expects a single artifact as input will fail with 'Invalid output reference' if the preceding `TuningStep` produces multiple artifacts (e.g., from multiple training jobs). The pipeline cannot resolve which specific artifact to pass, causing the error.
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.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
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.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.