AWS Certified Data Engineer Associate DEA-C01 Practice Question
An organization stores datasets in the S3 bucket "analytics-bkt". AWS Glue jobs assume GlueJobRole and Athena queries run under AthenaRole. GlueJobRole must write only to processed/, while AthenaRole must read from processed/ but not list or access other objects. Using policy-based authorization and least privilege, which approach needs the fewest managed policies or resources?
Attach separate inline IAM identity policies to GlueJobRole and AthenaRole granting their required S3 actions on analytics-bkt; leave the bucket without a bucket policy.
Create two S3 Access Points, one for each role, with policies restricting operations to the processed/ prefix; keep Block Public Access enabled on the bucket.
Attach one bucket policy to analytics-bkt that grants GlueJobRole s3:PutObject on processed/*, grants AthenaRole s3:GetObject and ListBucket limited to the processed/ prefix, and denies any other S3 actions for either role.
Use S3 object ACLs to grant GlueJobRole write permission and AthenaRole read permission on objects under the processed/ prefix, and disable the bucket policy.
A single resource-based bucket policy on analytics-bkt can mention both IAM roles. One statement grants GlueJobRole only s3:PutObject on arn:aws:s3:::analytics-bkt/processed/*, and another grants AthenaRole s3:GetObject on the same ARN plus s3:ListBucket on the bucket, scoped with a Condition key s3:prefix equal to "processed/". An explicit Deny for other S3 actions on these roles further enforces least privilege. Separate identity policies would require two policies, and S3 Access Points or ACLs add extra resources or legacy mechanisms. Therefore, the single bucket policy is the simplest and most maintainable solution.
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AWS Certified Data Engineer Associate DEA-C01
Data Security and Governance
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