Amazon Web Services Data-Engineer-Associate Exam With Confidence Using Practice Dumps

In AWS Glue, table partitions are managed as metadata objects within the AWS Glue Data Catalog. To add a new partition to an existing table, the correct and supported approach is to use the AWS Glue Data Catalog API, such as the CreatePartition operation, or equivalent console or SDK actions.

Updating the table schema alone does not create partitions or inform Glue about new partition values. Editing metadata files directly in Amazon S3 is unsupported and can corrupt the Data Catalog. Manually modifying the S3 bucket structure without registering partitions in Glue will result in Athena and other query engines being unable to recognize the partitions.

By adding partitions through the Glue Data Catalog API, query engines such as Amazon Athena and Amazon Redshift Spectrum can perform partition pruning, which significantly improves query performance by scanning only relevant data.

This method aligns with AWS best practices, ensures metadata consistency, and avoids unnecessary operational risk. Therefore, Option C is the correct solution.

AWS Secrets Manager is a service that allows you to securely store and manage secrets, such as database credentials, API keys, passwords, etc. You can use Secrets Manager to encrypt, rotate, and audit your secrets, as well as to control access to them using fine-grained policies. AWS Glue is a fully managed service that provides a serverless data integration platform for data preparation, data cataloging, and data loading. AWS Glue jobs allow you to transform and load data from various sources into various targets, using either a graphical interface (AWS Glue Studio) or a code-based interface (AWS Glue console or AWS Glue API).

Storing the credentials in AWS Secrets Manager and granting the AWS Glue job 1AM role access to the stored credentials will meet the requirements, as it will remediate the security vulnerability in the AWS Glue job and securely store the credentials. By using AWS Secrets Manager, you can avoid hard coding the credentials in the job script, which is a bad practice that exposes the credentials to unauthorized access or leakage. Instead, you can store the credentials as a secret in Secrets Manager and reference the secret name or ARN in the job script. You can also use Secrets Manager to encrypt the credentials using AWS Key Management Service (AWS KMS), rotate the credentials automatically or on demand, and monitor the access to the credentials using AWS CloudTrail. By granting the AWS Glue job 1AM role access to the stored credentials, you can use the principle of least privilege to ensure that only the AWS Glue job can retrieve the credentials from Secrets Manager. You can also use resource-based or tag-based policies to further restrict the access to the credentials.

The other options are not as secure as storing the credentials in AWS Secrets Manager and granting the AWS Glue job 1AM role access to the stored credentials. Storing the credentials in the AWS Glue job parameters will not remediate the security vulnerability, as the job parameters are still visible in the AWS Glue console and API. Storing the credentials in a configuration file that is in an Amazon S3 bucket and accessing the credentials from the configuration file by using the AWS Glue job will not be as secure as using Secrets Manager, as the configuration file may not be encrypted or rotated, and the access to the file may not be audited or controlled. References:

AWS Secrets Manager

AWS Glue

AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide, Chapter 6: Data Integration and Transformation, Section 6.1: AWS Glue

Scheduling an AWS Glue crawler to periodically update the Data Catalog automates the process of detecting new partitions and updating the catalog, which minimizes manual maintenance and operational overhead.