SOA-C02 · Question #644
A company has implemented a data ingestion pipeline to process files in the form of messages. A frontend application accepts user input and stores the input in Amazon S3. A backend application uses…
The correct answer is D. Implement an Amazon Simple Queue Service (Amazon SQS) queue between the frontend and. Implementing an Amazon SQS queue between the frontend and backend decouples the processing pipeline. The queue can buffer messages, allowing the backend to process them at its own pace, and preventing message loss during traffic spikes. This solution requires minimal…
Question
A company has implemented a data ingestion pipeline to process files in the form of messages. A frontend application accepts user input and stores the input in Amazon S3. A backend application uses Amazon EC2 instances to process the object that was uploaded to Amazon S3. The company recently experienced a significant increase in customer traffic. The frontend application is now sending more messages at one time than the backend application can handle, resulting in some lost messages. Which action will resolve this problem with the LEAST operational effort?
Options
- ARedevelop the backend application as a series of AWS Lambda functions.
- BImplement an Amazon Kinesis data stream to replace the backend application.
- CImplement an Application Load Balancer to distribute message traffic across the backend
- DImplement an Amazon Simple Queue Service (Amazon SQS) queue between the frontend and
How the community answered
(36 responses)- A17% (6)
- B8% (3)
- C3% (1)
- D72% (26)
Explanation
Implementing an Amazon SQS queue between the frontend and backend decouples the processing pipeline. The queue can buffer messages, allowing the backend to process them at its own pace, and preventing message loss during traffic spikes. This solution requires minimal operational effort and can be integrated with the existing architecture without a major redesign.
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