Formula-1 Business Transformation Case Study: Using AWS Cloud Service Provider



Do you all wonder how organizations transform their businesses by adopting the right digital transformation strategy?

Well, if yes then this article is for you. We will discuss how cutting-edge Machine Learning, High-performance computing, and data analytics AWS services help Formula 1 in achieving its business goal.

Business Problem

In formula 1 split-second difference is a matter of loss and win. And, being one of the most technologically advanced motorsports they required technology that can help them innovate faster by reducing vehicle design time, and increasing fan engagement by providing real-time insight using predictive machine learning models.

It can be achieved by designing a scalable architecture that meets computational power, reduces the simulation cycle time, and provides predictive insight into real-time events using machine learning models.

To achieve all of the requirements, without spending a big sum of money they needed industry experts who could architect their requirements. And, here Cloud comes into play which can provide them with all of the above requirements without overhead management so that they focus on their business priorities. Formula 1 decided to opt for AWS.

Business Solution

To achieve all of the desired outcomes they decided to move the computational Fluid Dynamics simulation over to the cloud which reduced their vehicle design time from 4 days to less than 12 hours, and able to visualize data input from the car and teams by giving real-time insight to the fans that made Formula 1 more exciting than ever.

Vehicle Design:

Formula 1 requires High-performance computing power to run simulations. With their current system using 192 cores, they were able to run simulations in four days, which is still slow to make rapid development. But with AWS they rebuild their simulation on Amazon HPC using 1,152 EC2, c5n instances and reducing their simulation time from 4 days to less than 12 hours.

It not only helped them innovate faster and experiment more but within six months of continual refinement, it was delivering the performance of a supercomputer that could cost millions of dollars to set up and manage.

Fan Engagement:

Formula 1 is not only just about the most technologically advanced motor sport but it’s also about the strategy and decisions that drivers and teams make during the race. Milliseconds of difference can be a difference between winning and losing. Choosing different settings on the car steering wheel, changing the car tire, or deciding when to pit can affect the race result. But, often these small details are left unnoticed by viewers because of 20 drivers and 10 teams on track it becomes difficult from a fan’s perspective to understand every detail. To give fans real-time experience about what is happening on the track, between the car, and how one decision can affect race results require a predictive Machine learning solution with the data that each team is collecting.

For real-time prediction, they used machine learning models built on Amazon SageMaker. Using Amazon SageMaker AWS and formula 1 was able to analyze and visualize all the data. Each racecar has 120 sensors and it produces 1.1 million telemetry data points per second during the race. Using all the live data and previous race data they trained machine learning models to predict race results and provide visualized results to the fan watching worldwide.


Architecture Component

  • Amazon API Gateway: Act as the entry point for the HTTP call from the F1 infrastructure.

  • AWS Lambda: For hosting applications and race logic.

  • DynamoDB: For storing race state.

  • Amazon SageMaker: Hosted on Ec2 instance for machine learning, and visualization.

  • Amazon S3: Incoming data stored in object storage.

  • Amazon CloudWatch: For monitoring.

Benefits achieved by Formula 1

  • Reduced simulation time by 80% from 60 hours to 12 hours.

  • Reduced cost of operation by 30% as compared to on-premise using an on-demand service model of the cloud.

  • Reduced downforce loss from 50% to 15%, increasing stability and driver safety.

  • Digitally transformed the business by innovating car simulation, and fan engagement.


  • Digital transformation is not about technology, technology is only a tool to achieve business transformation.

  • Business transformation using the cloud is more than a technology. It’s about understanding and overcoming four key areas culture, skills, organization, and risk management. Any industry can digitally transform its business, they need to have a good understanding of its business, the goal it wanted to achieve when moving on-prem to the cloud, the risk associated, and the return on investment with the capital expense and operational expense.

  • Understanding all of the factors Formula 1 is one of the examples of digital transformation. They used cutting-edge machine learning and data analytics technology of the cloud. And, used a pay-as-you-go or on-demand model. It helps them achieve cost saving and their desired result.