Redesign a retail order platform as serverless microservices with EventBridge
A retail company wants to improve its application architecture. The company's applications register new orders, handle returns of merchandise, and provide analytics. The applications store retail data in a MySQL database and an Oracle OLAP analytics database. All the applications and databases are hosted on Amazon EC2 instances. Each application consists of several components that handle different parts of the order process. These components use incoming data from different sources. A separate ETL job runs every week and copies data from each application to the analytics database. A solutions architect must redesign the architecture into an event-driven solution that uses serverless services. The solution must provide updated analytics in near real time. Which solution will meet these requirements?
Community Votes
100% of anonymous learners picked answer C. Votes are pick records left by other test-takers — they are not the verified answer.
Community Insight
The weekly ETL job is the root of the analytics latency, so replacing it with an event bus that fans every incoming data event out to both the microservices and the analytics database removes the batch window entirely and delivers the near real-time requirement.
A retail company's order registration, returns handling, and analytics applications are multi-component applications running on EC2 with MySQL and an Oracle OLAP database, and a weekly ETL job copies data into the analytics database. The redesign must be event-driven, use serverless services, and provide analytics in near real time.
Using SQS as the fan-out mechanism. SQS is a queue where each message is consumed by a single consumer, so competing consumers would each need their own queue and the analytics database would not receive the same events as the microservices, making near real-time distribution to both awkward.
Community Discussion (4 comments)
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Expert Analysis
Why the Answer Is Correct
Amazon EventBridge is an event bus that delivers each event to every interested consumer, which is exactly the fan-out pattern the architecture needs: incoming data goes to the bus and both the application microservices and the analytics path receive it. The applications become microservices on EKS with Fargate, which is serverless at the compute layer, so the team does not manage EC2 instances. The retail MySQL database moves to Aurora Serverless MySQL and the Oracle OLAP analytics database moves to Redshift Serverless, so the data stores are also serverless. Because the ETL job is replaced by the event bus, the analytics warehouse is updated as events arrive rather than weekly, which delivers the near real-time requirement.Why the Other Options Are Wrong
A: Amazon Neptune is a graph database, which is the wrong data model for retail order and returns analytics, and keeping MySQL on EC2 leaves a server-managed database in an architecture that must use serverless services. B: Fixed-size Auto Scaling groups of EC2 instances and Aurora MySQL are not serverless, and SNS notification delivery is not the mechanism to route each event's data to specific processing components, so the redesign requirement is not met. D: AppStream 2.0 is a managed desktop application streaming service and AWS IoT Core is an IoT device messaging service, so neither is a general application event bus, making this option irrelevant to the workload described.Community Comment Notes
The community voted 100 to 0 for C, and the top-voted comment identified the two decisive disqualifiers in A and B, that SQS is not for near real-time distribution and that MySQL on EC2 is not serverless, while option D uses AppStream for desktop streaming and IoT Core for IoT. Another commenter noted the single-word reason, serverless.Official Reference
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