Serverless Data Processing Using AWS Lambda and Amazon Kinesis

Abstract: Cloud computing has significantly transformed the development and deployment of modern applications. One of the most important advancements in cloud technology is serverless computing, which enables developers to build scalable applications without managing server infrastructure. This paper presents a serverless data processing architecture using Amazon Web Services (AWS), specifically utilizing AWS Lambda and Amazon Kinesis Data Streams to process real-time e-commerce order data.

The proposed system integrates multiple AWS services including Amazon API Gateway, AWS Lambda, Amazon Kinesis Data Streams, and Amazon S3. The frontend application collects order information from users and sends it to an API endpoint. API Gateway triggers a Lambda function that sends the order data to a Kinesis stream. Another Lambda function consumes the streaming records, processes the order information, and stores the processed data in Amazon S3. The system demonstrates how serverless architecture can efficiently process streaming data while eliminating the need for server management. Experimental results show that the system can handle real-time data processing effectively while providing scalability, reliability, and cost efficiency. This study highlights the potential of serverless computing for building scalable cloud-based data processing systems.

Keywords: Serverless Computing, AWS Lambda, Amazon Kinesis, Cloud Computing, Real-Time Data Processing, Event-Driven Architecture.