Amazon Web Services, (AWS), has entered into an agreement with Ferrari to become its official cloud, machine learning, and artificial intelligence provider.
Together, the companies will accelerate the pace of innovation across the entire Ferrari organisation, including their road cars department, GT Competitions, the Ferrari Challenge, and the Scuderia Ferrari FORMULA 1 (F1) team.
Ferrari will use AWS’s services and global infrastructure, including the AWS Europe (Milan) region, to streamline design and testing of its cars, giving customers the most exciting driving experiences possible. In addition, Scuderia Ferrari will leverage AWS to launch a digital fan engagement platform, via its mobile app, to engage hundreds of millions of fans worldwide with exclusive, personalized content.
Mattia Binotto, principal of Scuderia Ferrari, said: “Ferrari and AWS both represent excellence in their fields. As our Official Cloud Provider, I firmly believe AWS will enable our company to become a data-driven organisation that uses the power of technology to improve our products, increase engagement with Ferrari enthusiasts worldwide, and deliver continuously more exciting driving experiences.
“We chose AWS because of their relentless focus on innovation, unmatched portfolio of capabilities, and proven experience supporting partners in the automotive and sports industries. Throughout our storied history, Ferrari has had racing and innovation at our core, and now we look forward to applying AWS machine learning, advanced analytics, and high performance computing across the company to deliver deeper insights and even more powerful cars.”
As a manufacturer of some of the world’s highest-performing cars, Ferrari will rely on AWS’ advanced analytics, machine learning, compute, storage and database capabilities to rapidly achieve insights into car design and performance on the road and track. Ferrari will leverage Amazon Elastic Compute Cloud (Amazon EC2), with a range of specialized instance types for efficient high performance computing (HPC), to run complex simulations that test car performance under a wide variety of driving conditions and racing scenarios.
As Ferrari moves from simulation to assembly of its new road vehicle prototypes, it will apply AWS analytics and Amazon SageMaker (AWS’s service that helps developers and data scientists build, train and deploy machine learning models quickly in the cloud and at the edge) to inform testing and gain deeper insights into how its parts and cars perform under real world conditions.
To support this work and its simulations, Ferrari will build a data lake with Amazon Simple Storage Service (Amazon S3) and use AWS Lake Formation to quickly and securely gather, catalogue and clean hundreds of petabytes of data. Ferrari will examine factors that impact car performance and driver handling, such as engine temperature at different vehicle speeds, vehicle vibration patterns on different road surfaces, and suspension loads that affect how the vehicle grips the road.
Ferrari will also leverage AWS to make it easier for current and prospective customers to build, purchase and maintain their cars. Using Amazon Elastic Kubernetes Service (Amazon EKS) and Amazon DynamoDB (AWS’ fully managed key-value database), Ferrari will be able to quickly create, deploy and scale improved digital experiences such as the Ferrari Car Configurator. Consumers can use the Configurator to custom-build their car and then immerse themselves in it using high-resolution 2D and 3D visualisations.
In addition, for F1 racing fans, Scuderia Ferrari will use AWS compute, containers and media services to power a new digital fan engagement platform via its mobile app that will inform, educate, and entertain their fans. Upon creating customised profiles, fans will receive exclusive content such as virtual access to the Scuderia Ferrari garage and hospitality suite on race days. Moving forward, Ferrari plans to build virtual and augmented reality experiences on AWS that bring fans into the garage to interact with drivers and team personnel.