DEA-C01 Question 310
Single answerYou are designing a data processing pipeline on AWS and want to process large amounts of data in near real-time. Your application will receive streaming data through API calls and must process the data within seconds. Which AWS service combination should you use to efficiently manage the API calls and process the data?
- A
Amazon API Gateway and AWS Lambda
- B
Amazon API Gateway and Amazon EMR
- C
Amazon API Gateway and Amazon Kinesis Data Streams
- D
Amazon API Gateway and Amazon S3
Show answer and explanation
Correct answer: A
Explanation
The combination of Amazon API Gateway and AWS Lambda is an ideal solution for processing data from API calls in near real-time. API Gateway efficiently handles the API requests and forwards the data to Lambda, which processes it with minimal latency. This architecture is serverless, scales automatically, and is cost-efficient for real-time workloads.
- A. Correct.
Amazon API Gateway and AWS Lambda is the correct choice because API Gateway can handle the incoming API calls and trigger Lambda, which can process the data in near real-time. This setup is highly scalable and cost-effective for near real-time processing.
- B. Incorrect.
Amazon API Gateway and Amazon EMR is not the best option for near real-time data processing. EMR is better suited for batch processing of large datasets rather than handling streaming data from API calls.
- C. Incorrect.
Amazon API Gateway and Amazon Kinesis Data Streams is a good choice for streaming scenarios, but it requires additional components for processing the data, such as AWS Lambda or Kinesis Data Analytics. It’s not a direct solution for processing API call data in near real-time.
- D. Incorrect.
Amazon API Gateway and Amazon S3 is not suitable for streaming or near real-time processing. S3 is an object storage service, and while it can store the data, it cannot process it in real-time.