- A
Amazon S3
S3 events can trigger the pipeline.
- B
Amazon EC2
Why wrong: EC2 is not required for this automation.
- C
AWS Lambda
Lambda can react to S3 events and start training.
- D
Amazon SageMaker
SageMaker runs the training job.
- E
AWS Glue
Why wrong: Glue is for ETL, not needed.
Question 416 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 uses Amazon SageMaker to train models. The data scientist wants to automate the retraining process whenever new data arrives in an S3 bucket. Which THREE services can be used together to achieve this? (Choose THREE.)
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
✓
Amazon S3
Amazon S3 is correct because it acts as the event source, emitting notifications (e.g., s3:ObjectCreated:*) when new data arrives. These events can be captured by AWS Lambda, which is correct because it can run a function that invokes Amazon SageMaker to start a retraining job. Amazon SageMaker is correct because it performs the actual model training. Together, S3 triggers the pipeline, Lambda orchestrates the invocation, and SageMaker executes the retraining. Options B (EC2) and E (Glue) are not directly required for this automated retraining workflow; EC2 is a compute service that would add unnecessary complexity, and Glue (data transformation) is not needed for the core trigger-and-train flow.
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 S3
Why this is correct
S3 events can trigger the pipeline.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Amazon EC2
Why it's wrong here
EC2 is not required for this automation.
- ✓
AWS Lambda
Why this is correct
Lambda can react to S3 events and start training.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Amazon SageMaker
Why this is correct
SageMaker runs the training job.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
AWS Glue
Why it's wrong here
Glue is for ETL, not needed.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often select AWS Glue (Option E) thinking it is needed for data transformation before retraining, but the question asks for services that directly enable the automation of retraining when new data arrives, and Glue is not required for the core trigger-and-train flow.
Detailed technical explanation
How to think about this question
Under the hood, the typical architecture uses an S3 event notification to invoke an AWS Lambda function, which then calls the SageMaker CreateTrainingJob API with the new data location. The Lambda function can also check for data drift or schema changes before triggering retraining. In a real-world scenario, you might combine this with Amazon EventBridge for more complex scheduling or filtering, but the core three services (S3, Lambda, SageMaker) form the minimal serverless retraining trigger.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
What to study next
Got this wrong? Here's your next step.
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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: Amazon S3 — Amazon S3 is correct because it acts as the event source, emitting notifications (e.g., s3:ObjectCreated:*) when new data arrives. These events can be captured by AWS Lambda, which is correct because it can run a function that invokes Amazon SageMaker to start a retraining job. Amazon SageMaker is correct because it performs the actual model training. Together, S3 triggers the pipeline, Lambda orchestrates the invocation, and SageMaker executes the retraining. Options B (EC2) and E (Glue) are not directly required for this automated retraining workflow; EC2 is a compute service that would add unnecessary complexity, and Glue (data transformation) is not needed for the core trigger-and-train flow.
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.
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Last reviewed: Jul 4, 2026
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