A large trading company is using an on-premise system to analyze the trade data. After the trading day closes, the data, including the day’s transaction costs, execution reporting, and market performance, is sent to a Redhat server that runs big data analytics tools for next-day trading predictions. A bash script is used to configure resources and schedule when to run the data analytics workloads. How should the on-premise system be migrated to AWS with appropriate tools? (Select THREE)

Answer options:

A.Create an S3 bucket to store the trade data that is used for post-processing.
B.Send the trade data from various sources to a dedicated SQS queue.
C.Use AWS Batch to execute the bash script using a proper job definition.
D.Use AWS ECS to handle the big data analytics workloads.
E.Use CloudWatch Events to schedule data analytics jobs.

Correct Answer – A, C and E
There are several parts of the on-premise system. The first is the place to store the data from several sources. The second is the bash script that is used to schedule the data to analyze the task. And the third part is the big data analysis. All of these three parts need to be considered when being migrated. Refer to the below chart as a reference.
Option A is CORRECT: Because S3 is an ideal place to store trade data as it is highly available, durable, and cost-efficient.
Option B is incorrect: Because the SQS queue is inappropriate to store source data. The trade data is very large which needs a durable store such as S3.
Option C is CORRECT: Because AWS Batch is suitable to run a bash script using a job. The AWS Batch scheduler evaluates when, where, and how to run jobs.
Option D is incorrect: Because you should set up compute resources through AWS Batch instead of ECS. ECS is not supported by AWS Batch.
Option E is CORRECT: Because CloudWatch Events can be used to schedule and trigger AWS Batch jobs to perform data analytics.