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SCS-C02 · Question #123

A company's data scientists want to create artificial intelligence and machine learning (AI/ML) training models by using Amazon SageMaker. The training models will use large datasets in an Amazon S3…

The correct answer is A. Configure an S3 Lifecycle rule on the S3 bucket to delete objects after 45 days. Option A is correct because S3 Lifecycle rules are the native, fully managed AWS mechanism for automatically expiring (deleting) objects after a set number of days - no custom code, no maintenance, and no additional infrastructure required. It directly maps to the policy…

Submitted by miguelv· Mar 6, 2026Data Protection

Question

A company's data scientists want to create artificial intelligence and machine learning (AI/ML) training models by using Amazon SageMaker. The training models will use large datasets in an Amazon S3 bucket. The datasets contain sensitive information. On average, the data scientists need 30 days to train models. The S3 bucket has been secured appropriately. The company's data retention policy states that all data that is older than 45 days must be removed from the S3 bucket. Which action should a security engineer take to enforce this data retention policy?

Options

  • AConfigure an S3 Lifecycle rule on the S3 bucket to delete objects after 45 days.
  • BCreate an AWS Lambda function to check the last-modified date of the S3 objects and delete
  • CCreate an AWS Lambda function to check the last-modified date of the S3 objects and delete
  • DConfigure S3 Intelligent-Tiering on the S3 bucket to automatically transition objects to another

How the community answered

(37 responses)
  • A
    76% (28)
  • B
    3% (1)
  • C
    14% (5)
  • D
    8% (3)

Explanation

Option A is correct because S3 Lifecycle rules are the native, fully managed AWS mechanism for automatically expiring (deleting) objects after a set number of days - no custom code, no maintenance, and no additional infrastructure required. It directly maps to the policy requirement: objects older than 45 days are automatically removed.

Options B and C (both Lambda-based approaches) are over-engineered solutions. While a Lambda function could check object ages and delete them, this requires writing custom code, scheduling execution (e.g., via EventBridge), handling edge cases, and ongoing maintenance - all unnecessary when S3 already provides this natively.

Option D (Intelligent-Tiering) is a cost-optimization feature that moves objects between storage classes based on access frequency - it does not delete objects, so it cannot enforce a deletion-based retention policy.

Memory tip: Think of S3 Lifecycle rules as the "set it and forget it" tool for object management. If the question involves automatically deleting or transitioning objects based on age, Lifecycle rules are almost always the answer. Intelligent-Tiering = cost savings; Lifecycle = time-based automation.

Topics

#S3 Lifecycle#Data Retention#Data Deletion#Amazon S3

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