MLS-C01 Practice Question: Machine Learning Implementation and Operations
A team wants to automate the retraining of a model weekly using new data that arrives in S3. Which combination of services should they use?
⚠ Common exam trap
Test-takers frequently confuse event-driven triggers (Lambda + S3 events) with the need for a full MLOps pipeline, overlooking that SageMaker Pipelines provides the orchestration, model registry integration, and step-level caching that Lambda alone cannot offer.
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 SageMaker Pipelines and S3 events
Amazon SageMaker Pipelines natively supports automated retraining workflows triggered by S3 events. When new data arrives in S3, an event notification can invoke a Lambda function that starts a pipeline execution, which includes steps for data processing, training, evaluation, and model registration. This provides a fully managed, repeatable, and auditable MLOps pipeline without custom orchestration code.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
AWS Lambda and S3 events
Why it's wrong here
Lambda has time limits, not suitable for training jobs.
- ✗
Amazon SageMaker Processing jobs
Why it's wrong here
Processing is for data preprocessing, not full training pipeline.
- ✗
AWS Step Functions and AWS Glue
Why it's wrong here
Step Functions can orchestrate but lacks ML-specific integration.
- ✓
Amazon SageMaker Pipelines and S3 events
Why this is correct
SageMaker Pipelines is designed for ML workflows and can be triggered by S3 events.
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 |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.