DVA-C02: How to Build an Employee Directory with AWS Services

Learn how to migrate your legacy employee directory to AWS and use native AWS services to store and retrieve employee contact details and high-resolution photos. This tutorial will show you how to use Amazon S3, Amazon DynamoDB, and AWS APIs to create a scalable and secure solution.

Question

A company is migrating legacy internal applications to AWS. Leadership wants to rewrite the internal employee directory to use native AWS services. A developer needs to create a solution for storing employee contact details and high-resolution photos for use with the new application.

Which solution will enable the search and retrieval of each employee’s individual details and high-resolution photos using AWS APIs?

A. Encode each employee’s contact information and photos using Base64. Store the information in an Amazon DynamoDB table using a sort key.

B. Store each employee’s contact information in an Amazon DynamoDB table along with the object keys for the photos stored in Amazon S3.

C. Use Amazon Cognito user pools to implement the employee directory in a fully managed software-as-a-service (SaaS) method.

D. Store employee contact information in an Amazon RDS DB instance with the photos stored in Amazon Elastic File System (Amazon EFS).

Answer

B. Store each employee’s contact information in an Amazon DynamoDB table along with the object keys for the photos stored in Amazon S3.

Explanation

The correct answer is B. Store each employee’s contact information in an Amazon DynamoDB table along with the object keys for the photos stored in Amazon S3.

The reason is that Amazon DynamoDB is a NoSQL database service that can store and query structured or semi-structured data. Amazon S3 is an object storage service that can store any amount of data in objects. By using these two services together, the developer can create a solution for storing employee contact details and high-resolution photos for use with the new application.

To meet the solution, the developer can store each employee’s contact information, such as name, email, phone number, or department, in an Amazon DynamoDB table. The developer can use a unique identifier, such as employee ID, as the primary key of the table. The developer can also store each employee’s high-resolution photo as an object in an Amazon S3 bucket. The developer can use a naming convention, such as employee ID + photo extension, as the object key of the photo. The developer can then store the object key of the photo as an attribute in the DynamoDB table, along with the other contact information.

This solution will enable the search and retrieval of each employee’s individual details and high-resolution photos using AWS APIs. The developer can use the AWS SDK for the programming language or the AWS CLI to access the DynamoDB and S3 APIs. The developer can use the Query or GetItem API operations to get the contact information and the photo object key from the DynamoDB table by using the employee ID or other attributes. The developer can then use the GetObject API operation to get the photo object from the S3 bucket by using the photo object key.

Therefore, storing each employee’s contact information in an Amazon DynamoDB table along with the object keys for the photos stored in Amazon S3 will meet these requirements.

The other options are incorrect because they are not efficient, reliable, or applicable:

A. Encoding each employee’s contact information and photos using Base64 and storing them in a DynamoDB table using a sort key is not efficient or reliable. Base64 is a method of encoding binary data, such as images, into ASCII characters, which can increase the size of the data by about 33%. This option will incur higher storage costs and performance overhead for storing and retrieving large amounts of data in DynamoDB. Moreover, this option does not use a partition key for the DynamoDB table, which is required for distributing and accessing data across partitions.

C. Using Amazon Cognito user pools to implement the employee directory in a fully managed software-as-a-service (SaaS) method is not applicable. Amazon Cognito is a service that can provide user sign-up, sign-in, and access control for web and mobile applications. Amazon Cognito user pools are user directories that can store and manage user profiles and attributes. However, Amazon Cognito user pools are not designed for storing high-resolution photos or providing native AWS APIs for searching and retrieving data.

D. Storing employee contact information in an Amazon RDS DB instance with the photos stored in Amazon EFS is not efficient or reliable. Amazon RDS is a relational database service that can provide consistent and structured data storage and querying. Amazon EFS is a file system service that can provide scalable and shared storage for EC2 instances or on-premises servers. However, this option requires additional steps and costs to set up and maintain the RDS DB instance and the EFS file system. Moreover, this option does not provide native AWS APIs for accessing data from RDS or EFS.

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