- A
Amazon CloudWatch Events
Why wrong: CloudWatch Events can trigger a Lambda on schedule but cannot orchestrate a pipeline.
- B
AWS Lambda
Why wrong: Lambda functions are stateless and limited to 15 minutes, not suitable for long-running pipelines.
- C
AWS Step Functions
Step Functions can orchestrate multiple SageMaker API calls and handle retries.
- D
AWS Data Pipeline
Why wrong: Data Pipeline is legacy and less integrated with SageMaker than Step Functions.
Question 277 of 1,755
MLS-C01 Practice Question: Machine Learning Implementation and Operations
This MLS-C01 practice question tests your understanding of machine learning implementation and operations. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 company is using Amazon SageMaker to train a model and wants to automatically retrain the model every week using new data. Which AWS service should be used to orchestrate the retraining pipeline?
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
✓
AWS Step Functions
AWS Step Functions is the correct choice because it provides a serverless workflow orchestration service that can coordinate multiple AWS services (e.g., SageMaker training jobs, Lambda functions, and data processing) into a state machine. It supports scheduling via Amazon EventBridge (formerly CloudWatch Events) to trigger the pipeline weekly, and it can handle retries, error handling, and parallel execution, making it ideal for automating a retraining pipeline.
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.
- ✗
Amazon CloudWatch Events
Why it's wrong here
CloudWatch Events can trigger a Lambda on schedule but cannot orchestrate a pipeline.
- ✗
AWS Lambda
Why it's wrong here
Lambda functions are stateless and limited to 15 minutes, not suitable for long-running pipelines.
- ✓
AWS Step Functions
Why this is correct
Step Functions can orchestrate multiple SageMaker API calls and handle retries.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
AWS Data Pipeline
Why it's wrong here
Data Pipeline is legacy and less integrated with SageMaker than Step Functions.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse a scheduling service (CloudWatch Events) with a workflow orchestrator (Step Functions), or assume that a single Lambda function can handle the entire pipeline, overlooking the need for state management, error handling, and multi-step coordination.
Detailed technical explanation
How to think about this question
Under the hood, AWS Step Functions uses Amazon States Language (ASL) to define state machines, which can include tasks like StartTrainingJob, Wait, and Choice states to handle model evaluation and conditional retraining. A real-world scenario might involve a Step Functions workflow that first checks if new data is available (via a Lambda), then launches a SageMaker training job, waits for completion, evaluates the model’s accuracy, and only deploys the new model if it meets a threshold—all with built-in retry logic and CloudWatch logging. This approach avoids the complexity of managing orchestration logic in Lambda or the limitations of Data Pipeline’s batch-centric design.
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 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.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
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.
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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: AWS Step Functions — AWS Step Functions is the correct choice because it provides a serverless workflow orchestration service that can coordinate multiple AWS services (e.g., SageMaker training jobs, Lambda functions, and data processing) into a state machine. It supports scheduling via Amazon EventBridge (formerly CloudWatch Events) to trigger the pipeline weekly, and it can handle retries, error handling, and parallel execution, making it ideal for automating a retraining pipeline.
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.
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 →
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Last reviewed: Jul 4, 2026
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.
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