AWS Certified Data Engineer Associate DEA-C01 Practice Question
A data engineering team is creating a Python ETL script on AWS Glue that needs to connect to an existing Amazon RDS for PostgreSQL instance using a database user and password. Company policy requires automatic credential rotation, no code changes during rotation, and minimal operational overhead. Which approach satisfies these requirements?
Store credentials in AWS Systems Manager Parameter Store as SecureString and schedule a Lambda function to rotate and update the parameters.
Store the credentials in AWS Secrets Manager, enable automatic rotation using an AWS-provided RDS PostgreSQL rotation template, and reference the secret in the Glue connection.
Store credentials as plaintext in AWS Glue job parameters and manually update them monthly.
Enable IAM database authentication on the RDS instance and use AWS Glue's IAM role to obtain a temporary token.
Storing the database credentials in AWS Secrets Manager and turning on managed rotation for Amazon RDS uses an AWS-provided Lambda function to generate and apply a new password on a defined schedule. The secret's ARN can be referenced in an AWS Glue connection, so Glue retrieves the current password at run time without any code changes. Parameter Store would demand custom rotation logic and maintenance; plaintext parameters are insecure; and IAM database authentication eliminates passwords rather than rotating them, so it does not meet the stated requirement to continue using the existing user/password.
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What is AWS Secrets Manager, and how does it help with credential management?
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What is an ARN, and why is it important in referencing secrets in AWS?
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How does automatic credential rotation work in AWS Secrets Manager?
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What is AWS Secrets Manager?
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How does automatic credential rotation work in AWS Secrets Manager?
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Why is AWS Secrets Manager preferred over Parameter Store for this use case?
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AWS Certified Data Engineer Associate DEA-C01
Data Security and Governance
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