DEA-C01 Question 94
Select 2A financial services company is building a real-time fraud detection system. They need to process payment transaction data immediately after it is sent by the payment gateway and trigger alerts if fraudulent activity is detected. Which combination of AWS services is most suitable for implementing an event-driven architecture to meet these requirements?
- A
Amazon Kinesis Data Streams and AWS Lambda
- B
Amazon S3 and Amazon Athena
- C
Amazon SNS and Amazon SQS
- D
Amazon EventBridge and AWS Lambda
- E
Amazon RDS and AWS Glue
Show answer and explanation
Correct answers: A, D
Explanation
Event-driven architectures are designed to respond to events in real time. In this scenario, the company needs to process payment transaction data as soon as it is generated. Amazon Kinesis Data Streams is ideal for ingesting real-time data streams, and AWS Lambda can process this data for fraud detection. Similarly, Amazon EventBridge can route events to AWS Lambda for processing. These combinations ensure low-latency, event-driven workflows suitable for real-time fraud detection.
- A. Correct.
Correct: Amazon Kinesis Data Streams allows you to ingest real-time data streams, and AWS Lambda can be used to process the data for fraud detection. This combination is well-suited for event-driven, real-time processing.
- B. Incorrect.
Incorrect: Amazon S3 and Amazon Athena are primarily used for batch processing and querying stored data, not for real-time, event-driven architectures.
- C. Incorrect.
Incorrect: While Amazon SNS and SQS are useful for message delivery and decoupling components, they are not ideal for real-time stream processing and immediate event handling.
- D. Correct.
Correct: Amazon EventBridge can be used to build event-driven architectures by routing events, and AWS Lambda can process these events to implement real-time fraud detection logic.
- E. Incorrect.
Incorrect: Amazon RDS and AWS Glue are designed for relational database management and ETL processes, respectively, and are not suitable for real-time event-driven architectures.