AWS Certified AI Practitioner AIF-C01 Practice Question
A data science team launches Amazon SageMaker training jobs that must read objects in an encrypted Amazon S3 bucket. To avoid storing long-term access keys in the notebook code, which IAM construct should they configure for SageMaker to obtain temporary credentials?
Add a resource-based policy to the bucket that allows public read so credentials are unnecessary.
Create an IAM role that SageMaker is allowed to assume and attach a policy granting S3 access.
Create an IAM user with programmatic access keys and store the keys in AWS Secrets Manager.
Add the SageMaker notebooks to an IAM group that has a managed policy for S3 read access.
SageMaker can be granted permissions through an IAM role that the service assumes at runtime. A trust policy lists SageMaker as the principal allowed to call sts:AssumeRole, and an attached permissions policy grants the role access to the S3 bucket. When the job starts, SageMaker receives short-lived credentials derived from the role, eliminating the need to embed static access keys in code. An IAM user or group would still rely on long-term keys, and making the bucket public would remove security rather than enhance it.
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AWS Certified AI Practitioner AIF-C01
Security, Compliance, and Governance for AI Solutions
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