Abstract

In research work uses serverless app to process real-time data streams. It builds infrastructure for a fictional ride-sharing company. In this case, This work enable operations personnel at a fictional Wild Rydes headquarters to monitor the health and status of their unicorn fleet. Each unicorn is equipped with a sensor that reports its location and vital signs. This work uses AWS to build applications to process and visualize this data in real-time. In this paper AWS Lambda is used to process real-time streams, Amazon DynamoDB to persist records in a NoSQL database, Amazon Kinesis Data Analytics to aggregate data, Amazon Kinesis Data Firehose to archive the raw data to Amazon S3, and Amazon Athena to run ad-hoc queries against the raw data. Serverless computing allows you to build and run applications and services without thinking about servers. Serverless applications don't require you to provision, scale, and manage any servers. You can build them for nearly any type of application or backend service, and everything required to run and scale your application with high availability is handled for you. Building serverless applications means that you can focus on your core product instead of worrying about managing and operating servers or runtimes, either in the cloud or on- premises. This reduced overhead lets you reclaim time and energy that you can spent on developing great products which scale and that are reliable. This method considered a “server-less” platform / “Server-less Computing Execution Model” to build the real-time dataprocessing app. Architecture is based on managed services provided by AWS.