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.
An ML team uses SageMaker Pipelines to automate retraining. After a pipeline failure, they need to reprocess only the failed step without rerunning the entire pipeline. What should they do?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use SageMaker Pipelines Cache with step-level caching.
SageMaker Pipelines Cache with step-level caching allows you to reuse outputs from previous successful runs of unchanged steps. When a pipeline fails, only the failed step and any downstream steps that depend on it need to be re-executed, because cached results from prior successful steps are automatically retrieved. This avoids rerunning the entire pipeline, saving time and compute resources.
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.
✗
Create a new pipeline version for each run.
Why it's wrong here
Creating new versions does not help with reprocessing a single step.
✗
Use SageMaker Model Monitor to detect drift and trigger retraining.
Why it's wrong here
Model Monitor is for monitoring inference quality, not for pipeline step recovery.
✓
Use SageMaker Pipelines Cache with step-level caching.
Why this is correct
Caching enables the pipeline to skip completed steps and resume from the failed step.
Related concept
Read the scenario before looking for a memorised answer.
✗
Manually rerun the pipeline with updated parameters.
Why it's wrong here
Manual rerun would repeat all steps, wasting time and resources.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse SageMaker Pipelines Cache with Model Monitor's drift detection, assuming that monitoring automatically handles retraining failures, when in fact caching is the correct mechanism for step-level reuse.
Detailed technical explanation
How to think about this question
Step-level caching in SageMaker Pipelines works by hashing the step's input parameters, source code, and configuration; if the hash matches a previous successful run, the cached output artifact is used. This is particularly valuable in large pipelines with expensive steps like hyperparameter tuning or data preprocessing, where a single failure can waste hours of compute. A subtle behavior is that caching is disabled by default and must be explicitly enabled on each step definition via the `CacheConfig` property.
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
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: Use SageMaker Pipelines Cache with step-level caching. — SageMaker Pipelines Cache with step-level caching allows you to reuse outputs from previous successful runs of unchanged steps. When a pipeline fails, only the failed step and any downstream steps that depend on it need to be re-executed, because cached results from prior successful steps are automatically retrieved. This avoids rerunning the entire pipeline, saving time and compute resources.
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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Question Discussion
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