MLS-C01 Data Engineering Practice Question
A data engineering team needs to orchestrate a complex workflow that involves multiple AWS Glue jobs, Lambda functions, and S3 operations. The workflow must run on a schedule and allow monitoring of each step. Which AWS service should they use?
⚠ Common exam trap
Test-takers frequently confuse AWS Step Functions with Amazon CloudWatch Events (EventBridge) because both can schedule tasks, but they fail to recognize that EventBridge only triggers a single target per rule and cannot orchestrate multi-step workflows with conditional logic, retries, or parallel execution.
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 a serverless orchestration service that lets you coordinate multiple AWS services, including AWS Glue jobs, Lambda functions, and S3 operations, into a state machine workflow. It provides built-in scheduling via Amazon EventBridge (formerly CloudWatch Events) and offers visual monitoring, logging, and error handling for each step, making it the ideal choice for complex, multi-step workflows that require observability.
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 Simple Workflow Service (SWF)
Why it's wrong here
SWF is an older service; Step Functions is preferred for new projects.
- ✓
AWS Step Functions
Why this is correct
Step Functions provides state machines to orchestrate multi-step workflows.
- ✗
AWS Data Pipeline
Why it's wrong here
Data Pipeline is designed for data movement and transformation, not general orchestration.
- ✗
Amazon CloudWatch Events
Why it's wrong here
CloudWatch Events can invoke targets but lacks orchestration capabilities.
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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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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