easyMultiple ChoiceObjective-mapped
MLA-C01 Practice Question: A team wants to automate the retraining and…
A team wants to automate the retraining and deployment of an ML model whenever new labeled data arrives in S3. The workflow includes data preprocessing, training, evaluation, and conditional deployment. Which AWS service is best suited for orchestrating this end-to-end pipeline?
⚠ Common exam trap
Many exam-takers choose AWS Step Functions (Option A) because it is a general-purpose orchestrator, but they overlook that SageMaker Pipelines provides tighter integration with ML-specific steps and reduces custom code overhead.
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 triggered by S3 events via EventBridge.
Amazon SageMaker Pipelines is purpose-built for ML workflows, offering native integration with SageMaker for training, evaluation, and conditional deployment steps. Triggered by S3 events via Amazon EventBridge, it automates the end-to-end pipeline from data preprocessing to conditional model deployment without requiring 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 Step Functions with Lambda functions for each step.
Why it's wrong here
Step Functions can orchestrate, but SageMaker Pipelines offers ML-specific features like model evaluation and registry integration.
- ✗
AWS Glue workflows with triggers based on S3 events.
Why it's wrong here
Glue workflows are for ETL, not full ML pipeline with training and deployment.
- ✗
AWS CodePipeline with source from S3 and build from CodeBuild.
Why it's wrong here
CodePipeline is for CI/CD of applications, not specialized for ML models.
- ✓
Amazon SageMaker Pipelines triggered by S3 events via EventBridge.
Why this is correct
SageMaker Pipelines is designed for ML workflows and supports S3 event triggers.
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 |
Go deeper
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About these practice questions
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Same concept, more angles
1 more way this is tested on MLA-C01
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A team is using SageMaker Pipelines to automate retraining and deployment. They want to trigger the pipeline automatically when new training data is available in an S3 bucket. Which approach should they use?
medium- ✓ A.Create an Amazon EventBridge rule that triggers the pipeline execution on S3 PutObject events
- B.Register the pipeline as a model package in SageMaker Model Registry
- C.Configure a cron job to run the pipeline every hour
- D.Use AWS Step Functions to poll the S3 bucket and start the pipeline when a new object appears
Why A: Amazon EventBridge can directly capture S3 PutObject events and invoke a SageMaker Pipeline execution as a target. This provides a fully event-driven, serverless integration without polling or manual intervention, aligning with best practices for automating ML workflows when new data arrives.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.