Learn how to use AWS services such as DynamoDB, S3, and Cognito to create a solution for storing employee contact information and high-resolution photos. Compare different options and find out the best one for your use case.
Table of Contents
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.
This solution will enable the search and retrieval of each employee’s individual details and high-resolution photos using AWS APIs. Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability. Amazon S3 is an object storage service that offers industry-leading scalability, data availability, security, and performance. By storing the employee contact information in a DynamoDB table and the photos in S3, the developer can leverage the benefits of both services and avoid storing large binary data in DynamoDB, which can increase costs and reduce performance. The developer can use the object keys stored in DynamoDB to reference the photos stored in S3 and retrieve them using the S3 API.
The other options are not suitable for this use case because:
Option A. Encode each employee’s contact information and photos using Base64. Store the information in an Amazon DynamoDB table using a sort key.
This option is not recommended because it will increase the size of the data stored in DynamoDB by approximately 33%, which will increase storage costs and reduce performance. Additionally, encoding and decoding the photos using Base64 will add complexity and overhead to the application logic.
Option C. Use Amazon Cognito user pools to implement the employee directory in a fully managed software-as-a-service (SaaS) method.
This option is not appropriate because Amazon Cognito user pools are designed for user authentication and authorization, not for storing employee contact details and high-resolution photos. Amazon Cognito user pools have limits on the amount and size of user attributes that can be stored, and they do not support storing binary data such as photos.
Option D. Store employee contact information in an Amazon RDS DB instance with the photos stored in Amazon Elastic File System (Amazon EFS).
This option is not optimal because it will require more operational overhead and cost than using DynamoDB and S3. Amazon RDS is a fully managed relational database service that supports various database engines, but it requires provisioning, scaling, patching, and backup of database instances. Amazon EFS is a fully managed file system service that provides scalable, elastic, concurrent file storage for use with AWS cloud services and on-premises resources. However, using EFS to store photos will incur additional network latency and cost compared to using S3, which is optimized for object storage.
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