Leveraging AWS Serverless Architecture for Efficient Data Processing and Analytics
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Abstract
This paper introduces an innovative approach to data ingestion utilizing serverless architecture on Amazon Web Services (AWS). Traditional data ingestion methods frequently encounter challenges such as scalability constraints and substantial operational overhead. Serverless computing emerges as a compelling alternative by abstracting the complexities of infrastructure management and automatically scaling resources in response to demand. Through rigorous experimentation and performance analysis, we demonstrate the superiority of our approach in terms of scalability, resource efficiency, and cost-effectiveness when compared to conventional methods. The paper delves into the design considerations, implementation strategies, and best practices for deploying and managing a serverless data ingestion framework on AWS. Our framework not only offers a robust solution for seamlessly ingesting data into cloud environments but also enhances scalability, flexibility, and cost savings. By leveraging serverless architecture, the framework ensures automatic scaling and resource provisioning, thereby minimizing operational overhead and optimizing overall costs
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