Which approach should a solutions architect take to migrate this solution to AWS?
Rehost the Db2 database in Amazon Fargate. Migrate all the data. Enable caching in Fargate. Refactor the API to use the Fargate Db2 database. Implement Amazon API Gateway and enable API caching.
Use AWS DMS to migrate data to Amazon DynamoDB using a continuous replication task. Refactor the API to use the DynamoDB data. Implement the refactored API in Amazon API Gateway and enable API caching.
Create a local cache on the mainframe to store query outputs. Use SFTP to sync to Amazon S3 on a daily basis. Refactor the API to use Amazon EFS. Implement Amazon API Gateway and enable API caching.
Extract data daily and copy the data to AWS Snowball for storage on Amazon S3. Sync daily. Refactor the API to use the S3 data. Implement Amazon API Gateway and enable API caching.
Explanations:
Rehosting the Db2 database in Amazon Fargate is not an effective solution as it does not address the underlying performance issues and licensing costs associated with Db2. Additionally, Fargate is designed for running containerized applications, not for database workloads, and enabling caching in Fargate may not resolve the timeout issues.
Migrating the data to Amazon DynamoDB using AWS DMS allows for a NoSQL solution that is highly performant and scales well for read-heavy workloads. Refactoring the API to utilize DynamoDB will significantly reduce latency for read operations, meeting the requirement for data retrieval within 3 seconds. Using API Gateway with caching further enhances performance by reducing load on the database.
Creating a local cache on the mainframe and syncing to Amazon S3 is inefficient, as it introduces latency in data retrieval. Refactoring the API to use Amazon EFS is not suitable for read-heavy applications and does not align with the need for low-latency access to frequently accessed data.
Using AWS Snowball for daily data transfer to S3 is not appropriate for real-time or near-real-time access requirements. This method creates significant delays in data availability, making it unsuitable for an application that needs to retrieve user data quickly upon login. Refactoring the API to use S3 data also introduces latency compared to using a database or DynamoDB.