AWS Case Study

Vivek Singare
2 min readMar 15, 2021

--

AWS is one of the top cloud computing service provided by Amazon. It is the on demand availability of computer system resources, especially data storage (cloud storage) and computing power, without direct active management by the user . AWS is a comprehensive, easy to use computing platform offered Amazon. The platform is developed with a combination of infrastructure as a service (IaaS), platform as a service (PaaS) and packaged software as a service (SaaS) offerings.

Amazon Web Services offers a wide range of different business purpose global cloud-based products. The products include storage, databases, analytics, networking, mobile, development tools, enterprise applications, with a pay-as-you-go pricing model.

Companies benefitted from AWS:

Netflix:

Netflix is the world’s leading internet television network, with more than 100 million members in more than 190 countries enjoying 125 million hours of TV shows and movies each day. Netflix uses AWS for nearly all its computing and storage needs, including databases, analytics, recommendation engines, video trans-coding, and more — hundreds of functions that in total use more than 100,000 server instances on AWS.

Netflix’s infrastructure, built on AWS, makes it possible to be extremely resilient, even when the company is running services in many AWS Regions simultaneously.

BMW:

The BMW Group is using AWS for its new connected-car application that collects sensor data from BMW 7 Series cars to give drivers dynamically updated map information. BMW Group is one of the leading manufacturers of premium cars and mobility services in the world, with brands such as Rolls Royce, BMW, and Mini. BMW built its new car-as-a-sensor (CARASSO) service in only six months leveraging Amazon Simple Storage Service (Amazon S3), Amazon Simple Queue Service (Amazon SQS), Amazon DynamoDB, Amazon Relational Database Service (Amazon RDS), and AWS Elastic Beanstalk. By running on AWS, CARASSO can adapt to rapidly changing load requirements that can scale up and down by two orders of magnitude within 24 hours. By 2018 CARASSO is expected to process data collected by a fleet of 100,000 vehicles traveling more than eight billion kilometers.

--

--