MLS-C01 Practice Question: Machine Learning Implementation and Operations
A company is using Amazon SageMaker to train a model and wants to track hyperparameter tuning jobs. Which AWS service is BEST suited to store and query metadata such as tuning job configurations and results?
⚠ Common exam trap
Candidates often confuse CloudWatch Logs for tracking metadata because it is the default logging service, but it is designed for unstructured logs, not structured experiment metadata, and lacks the search and comparison capabilities of SageMaker Experiments.
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 Experiments
Amazon SageMaker Experiments is purpose-built for tracking, organizing, and querying metadata from machine learning training runs, including hyperparameter tuning jobs. It automatically captures configurations, metrics, and results, and provides a Python SDK and SDK API to search and compare trials, making it the best choice for this use case.
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 CloudWatch Logs
Why it's wrong here
CloudWatch Logs stores unstructured logs, not structured experiment metadata.
- ✗
Amazon S3 with Amazon Athena
Why it's wrong here
Athena can query data in S3 but is not the primary service for tracking SageMaker experiments.
- ✓
Amazon SageMaker Experiments
Why this is correct
SageMaker Experiments is the native solution for tracking tuning jobs and their results.
- ✗
Amazon DynamoDB
Why it's wrong here
DynamoDB can store metadata but requires custom code and is not the best fit for SageMaker experiments.
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JA
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.