Ferrari Taps AWS to Bring Cloud Computing to Its Luxury and Race Cars
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The Ferrari sports cars that many of us dream of owning—even if we can’t afford them—will soon feature innovations powered by cutting-edge compute technologies. The company recently named Amazon Web Services (AWS) as the official cloud, machine learning and artificial intelligence provider for Scuderia Ferrari, the carmaker’s Formula 1 team. The breakthroughs Ferrari hopes to unlock with AWS will be used to enhance its high-performance vehicles—whether it’s on the freeway or at the Grand Prix.
The Italian carmaker will deploy AWS technologies to supercharge innovation across all of Ferrari’s product lines—from its luxury sports cars to its racing teams. Ferrari will leverage AWS to achieve in-depth insights into vehicle design and performance.
For vehicle design, Ferrari will use Amazon Elastic Compute Cloud (Amazon EC2) to create and run sophisticated simulations that will test car performance in a variety of driving and racing conditions. These simulations will be run on Amazon’s custom-built Graviton2 processors—the workhorses of Amazon EC2-based simulation instances that Amazon claims this will consistently deliver up to 40 percent better price performance compared to x86-based instances.
By using AWS cloud and high-performance computing (HPC) capabilities, Ferrari will be able to run thousands of simulations concurrently—a rate much faster than if the company were to run them on-site—accelerating access to innovation. This will provide Ferrari designers and engineers with the agility to experiment with new designs, which could allow the carmaker to bring performance innovations to the market, or the race pit, significantly faster.
Once the new prototypes are designed, they will need to be tested. That’s when Ferrari will utilize AWS analytics and Amazon SageMaker. This is the AWS machine learning platform developers and data scientists use to create, train and deploy cloud-based machine learning models. These technologies will be used to analyze prototypes in real-world conditions to generate deeper insights into the performance of individual components and entire prototype vehicles alike.
These processes are bound to create an intimidating amount of data. To store the information, Ferrari uses Amazon Simple Storage Service (Amazon S3) to build a data lake: a centralized repository that can store data at various scales. In a data lake, structured and unstructured data can be stored on equal terms—from relational data that comes from business applications to nonrelational data from sources like IoT devices and social media.
Once data is stored, the carmaker will rely on AWS Lake Formation to collect, categorize and clean what will likely be hundreds of petabytes of data.
With these tools at its disposal, Ferrari will be able to examine, in considerable detail, the factors that influence the performance of the car and the driver—factors that range from engine temperature at different speeds, vibration patterns caused by different road surfaces and the effect of suspension loads on tire grip. And how fans react to these instances.
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