SAA-C03 · Question #363
A company has an application with a REST-based interface that allows data to be received in near- real time from a third-party vendor. Once received, the application processes and stores the data for
The correct answer is A. Use Amazon Kinesis Data Streams to ingest the data. Process the data using AWS Lambda. Amazon Kinesis Data Streams provides a highly scalable and durable service for ingesting real- time streaming data. By decoupling ingestion and processing, Kinesis can handle large spikes in traffic without service disruption. Lambda functions (or other consumers) can then proces
Question
A company has an application with a REST-based interface that allows data to be received in near- real time from a third-party vendor. Once received, the application processes and stores the data for further analysis. The application is running on Amazon EC2 instances. The third-party vendor has received many 503 Service Unavailable Errors when sending data to the application. When the data volume spikes, the compute capacity reaches its maximum limit and the application is unable to process all requests. Which design should a solutions architect recommend to provide a more scalable solution?
Options
- AUse Amazon Kinesis Data Streams to ingest the data. Process the data using AWS Lambda
- BUse Amazon API Gateway on top of the existing application. Create a usage plan with a quota
- CUse Amazon Simple Notification Service (Amazon SNS) to ingest the data. Put the EC2 instances
- DRepackage the application as a container. Deploy the application using Amazon Elastic Container
How the community answered
(27 responses)- A85% (23)
- B4% (1)
- C7% (2)
- D4% (1)
Explanation
Amazon Kinesis Data Streams provides a highly scalable and durable service for ingesting real- time streaming data. By decoupling ingestion and processing, Kinesis can handle large spikes in traffic without service disruption. Lambda functions (or other consumers) can then process the data as it arrives, scaling automatically. This pattern avoids 503 errors due to compute saturation and delivers a resilient, serverless, and highly scalable architecture.
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