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MLA-C01 Practice Question: A company uses SageMaker Ground Truth to create a…
A company uses SageMaker Ground Truth to create a labeled dataset, then trains a model using SageMaker Training. They want to automate the pipeline so that whenever a labeling job is completed, it triggers the training job. Which architecture meets this requirement with minimal latency?
⚠ Common exam trap
Test-takers frequently assume S3 event notifications are the simplest event-driven trigger, but they overlook the fact that S3 events can fire on intermediate writes (e.g., partial output files) rather than waiting for the labeling job's definitive `Completed` state, leading to data integrity issues.
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
✓
Use Amazon CloudWatch Events (EventBridge) to detect the completed labeling job and trigger a SageMaker Pipeline execution.
Amazon EventBridge can natively capture SageMaker job state changes (e.g., `SageMaker Labeling Job State Change` to `Completed`) and directly trigger a SageMaker Pipeline execution. This event-driven approach eliminates polling overhead and provides the lowest latency by reacting immediately when the labeling job finishes.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use AWS Step Functions to poll the labeling job status and then start training.
Why it's wrong here
Polling is inefficient and adds latency compared to event-driven approach.
- ✗
Configure an S3 event notification on the labeling job output bucket to trigger a Lambda function that starts training.
Why it's wrong here
S3 events are not directly tied to labeling job completion status; there is a delay and potential race condition.
- ✓
Use Amazon CloudWatch Events (EventBridge) to detect the completed labeling job and trigger a SageMaker Pipeline execution.
Why this is correct
EventBridge directly supports SageMaker events and can start a pipeline execution with minimal latency.
- ✗
Set up a scheduled cron job in EventBridge to check for completed labeling jobs every hour and start training if found.
Why it's wrong here
Scheduling introduces latency and is not event-driven.
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