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Answer: Create a new AWS Key Management Service (AWS KMS) encryption key. Use AWS Secrets Manager to create a new secret that uses the KMS key with the appropriate credentials. Associate the secret with the Aurora DB cluster. Configure a custom rotation period of 14 days.
## Explanation **Correct Answer: A** AWS Secrets Manager is specifically designed for managing secrets like database credentials with built-in features for: 1. **Automatic rotation** - Can be configured to rotate secrets automatically on a schedule (14 days in this case) 2. **KMS encryption** - Automatically encrypts secrets using AWS KMS 3. **Integration with Aurora** - Can directly associate secrets with Aurora DB clusters 4. **Least operational effort** - Requires minimal custom code and maintenance **Why other options are incorrect:** **B. Systems Manager Parameter Store** - Parameter Store is good for configuration data but not ideal for secrets requiring automatic rotation - Requires custom Lambda function for rotation (more operational effort) - Doesn't have built-in integration with Aurora for automatic credential rotation **C. EFS with custom Lambda** - Requires complex setup with EFS mounting across all EC2 instances - Needs custom Lambda function for rotation - File-based approach is less secure and more error-prone - Higher operational overhead for maintenance **D. S3 with custom Lambda** - Requires application to regularly download credentials from S3 - Needs custom Lambda function for rotation - S3 is not designed for secrets management - Credentials could be exposed in transit or at rest **Key AWS Services for This Scenario:** - **AWS Secrets Manager**: Purpose-built for secrets management with automatic rotation - **AWS KMS**: Provides encryption for secrets at rest - **Amazon Aurora**: Integrates natively with Secrets Manager for credential management **Best Practice:** Always use purpose-built services like AWS Secrets Manager for secrets management rather than building custom solutions, as it reduces operational overhead and improves security posture.
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A company hosts a multi-tier web application that uses an Amazon Aurora MySQL DB cluster for storage. The application tier is hosted on Amazon EC2 instances. The company's IT security guidelines mandate that the database credentials be encrypted and rotated every 14 days.
What should a solutions architect do to meet this requirement with the LEAST operational effort?
A
Create a new AWS Key Management Service (AWS KMS) encryption key. Use AWS Secrets Manager to create a new secret that uses the KMS key with the appropriate credentials. Associate the secret with the Aurora DB cluster. Configure a custom rotation period of 14 days.
B
Create two parameters in AWS Systems Manager Parameter Store: one for the user name as a string parameter and one that uses the SecureString type for the password. Select AWS Key Management Service (AWS KMS) encryption for the password parameter, and load these parameters in the application tier. Implement an AWS Lambda function that rotates the password every 14 days.
C
Store a file that contains the credentials in an AWS Key Management Service (AWS KMS) encrypted Amazon Elastic File System (Amazon EFS) file system. Mount the EFS file system in all EC2 instances of the application tier. Restrict the access to the file on the file system so that the application can read the file and that only super users can modify the file. Implement an AWS Lambda function that rotates the key in Aurora every 14 days and writes new credentials into the file.
D
Store a file that contains the credentials in an AWS Key Management Service (AWS KMS) encrypted Amazon S3 bucket that the application uses to load the credentials. Download the file to the application regularly to ensure that the correct credentials are used. Implement an AWS Lambda function that rotates the Aurora credentials every 14 days and uploads these credentials to the file in the S3 bucket.