SAP-C02 Question 487
Select 4A company operates a multi-region application and wants to replicate their data across regions to ensure durability and low-latency access for users globally. Their data consists of large files that need to be replicated as soon as they are uploaded. Which of the following AWS services or features can be used to achieve this?
- A
Amazon S3 Cross-Region Replication (CRR)
- B
Amazon RDS Read Replicas
- C
AWS DataSync
- D
Amazon DynamoDB Global Tables
- E
Amazon EFS Replication
Show answer and explanation
Correct answers: A, C, D, E
Explanation
Amazon S3 Cross-Region Replication (CRR) and AWS DataSync are well-suited for replicating large files across AWS regions. Amazon DynamoDB Global Tables and Amazon EFS Replication are also valid choices for replicating data across regions, though they are designed for specific use cases (DynamoDB tables and NFS-based file systems, respectively). Amazon RDS Read Replicas, however, are not applicable as they are designed for database read scalability and do not address the replication of large files.
- A. Correct.
Amazon S3 Cross-Region Replication (CRR) allows you to automatically and asynchronously replicate objects across AWS regions, making it ideal for distributing large files globally.
- B. Incorrect.
Amazon RDS Read Replicas are used for database read scalability across regions, but they are not designed for replicating large files like the ones described in the scenario.
- C. Correct.
AWS DataSync can be used to replicate or transfer large files between AWS services or regions, making it a valid option for this scenario.
- D. Correct.
Amazon DynamoDB Global Tables enable multi-region, multi-active replication for DynamoDB tables, which allows for low-latency access to replicated data globally. While it is specific to DynamoDB workloads, it applies to scenarios needing data replication across regions.
- E. Correct.
Amazon EFS Replication provides asynchronous replication of NFS-based file systems across AWS regions, making it suitable for replicating large files efficiently.