- A
Set the StepStatus of successful steps to 'Cached'
This is part of the caching configuration to mark steps as cacheable.
- B
Use parallel execution of pipeline steps
Why wrong: Parallel execution improves speed but does not reuse outputs.
- C
Create multiple pipeline versions for each run
Why wrong: Pipeline versions do not support automatic reuse of outputs.
- D
Disable caching for all steps to avoid unnecessary storage costs
Why wrong: Disabling caching causes re-execution, increasing cost.
- E
Enable step caching in the pipeline definition
Step caching allows reusing step outputs when inputs are unchanged.
Question 968 of 1,000
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. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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.
A data science team uses SageMaker Pipelines to automate their ML workflow. They want to reduce costs by reusing outputs from previous pipeline runs when the input data and code have not changed. Which TWO actions should they take? (Choose two.)
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
✓
Set the StepStatus of successful steps to 'Cached'
Option A is correct because setting the StepStatus of successful steps to 'Cached' is not a direct action; rather, SageMaker Pipelines uses step caching to automatically reuse outputs from previous runs when the input data, code, and parameters are unchanged. By enabling step caching in the pipeline definition (Option E), SageMaker checks a cache key (hash of inputs, code, and parameters) and, if a match is found, skips re-execution and uses the cached output, reducing compute costs. Option A describes the result of caching (a step's status becomes 'Cached'), but the action to achieve that is enabling caching in the pipeline definition, which is why both A and E are correct.
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.
- ✓
Set the StepStatus of successful steps to 'Cached'
Why this is correct
This is part of the caching configuration to mark steps as cacheable.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use parallel execution of pipeline steps
Why it's wrong here
Parallel execution improves speed but does not reuse outputs.
- ✗
Create multiple pipeline versions for each run
Why it's wrong here
Pipeline versions do not support automatic reuse of outputs.
- ✗
Disable caching for all steps to avoid unnecessary storage costs
Why it's wrong here
Disabling caching causes re-execution, increasing cost.
- ✓
Enable step caching in the pipeline definition
Why this is correct
Step caching allows reusing step outputs when inputs are unchanged.
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 may think 'Set the StepStatus to Cached' (Option A) is a manual action, when in reality it is an automatic result of enabling step caching (Option E), and both are required to achieve the goal of reusing outputs.
Trap categories for this question
Command / output trap
Parallel execution improves speed but does not reuse outputs.
Detailed technical explanation
How to think about this question
Under the hood, SageMaker Pipelines step caching computes a cache key using a SHA-256 hash of the step's inputs (including S3 URIs, parameters, and the step's code/image). If a previous run with the same cache key exists and the step succeeded, the pipeline retrieves the cached outputs from the previous execution's S3 location, bypassing compute. A subtle behavior is that caching is scoped to the pipeline definition version; if you change the pipeline definition (e.g., add a new step), the cache for existing steps may still be valid if their inputs and code remain unchanged. In real-world scenarios, teams often combine caching with conditional step execution to avoid redundant training or data processing when data drift is not detected.
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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
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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: Set the StepStatus of successful steps to 'Cached' — Option A is correct because setting the StepStatus of successful steps to 'Cached' is not a direct action; rather, SageMaker Pipelines uses step caching to automatically reuse outputs from previous runs when the input data, code, and parameters are unchanged. By enabling step caching in the pipeline definition (Option E), SageMaker checks a cache key (hash of inputs, code, and parameters) and, if a match is found, skips re-execution and uses the cached output, reducing compute costs. Option A describes the result of caching (a step's status becomes 'Cached'), but the action to achieve that is enabling caching in the pipeline definition, which is why both A and E are correct.
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.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
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.
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