Ducati CTO reveals how data steers race results and motorcycle design

Every millisecond counts in motorcycle racing. In the Dubai MotoGP grand Prix in March, Ducati rider Andrea Dovizioso pipped reigning world champion Marc Márquez to the Grand Prix finishing line by just 0.023 seconds.

When the margins of victory are so minute, data can play a decisive role in results. Its potential has led the Ducati Corse team to install more than 60 sensors on its MotoGP bikes, which between them generate over 20 GB of data per race. In the pit lanes that run alongside the track, engineers analyse the information collected on NetApp’s hybrid cloud infrastructure (HCI) to find ways to tweak their setup and strategy.

After the race, the team return to their base in Bologna, Italy, where all the information is downloaded into Ducati’s principal data centre for more detailed analysis, alongside 15 years of historical data on everything from leaning angles to tire pressure.

“We transfer all the data that we leverage from the motorcycle directly off this HCI and transform it into information for the engineers and the riders to do the right setup for the motorcycle during the testing period,” Ducati CTO Konstantin Kostenarov told CIO UK at the NetApp Data Days event in Bologna last month.

Ducati is the only Moto GP team with a high-performance computing system on the track. Kostenarov believes that this gives his team a unique advantage, as an increase in computational power can add speed to the motorbikes. The setup also enables Ducati to link lessons from the racetrack to the rest of the business.

Riding range

MotoGP is not Ducati’s primary driver of revenue, but the sport does offer insights into how the company can design and sell over 50,000 motorbikes to the public every year.

The data from the race flows into the aerodynamics, engine architecture and components on the Ducati street bikes, such as the winglets that were recently adapted from the racetrack to the road. This information is further augmented through real-time feedback from customers and staff across the business.

Ducati describes the process as “race on Sunday, sell on Monday.”

“We combine this data to obtain information on how the road bikes can be improved in safety and in performance, and how the behaviours of the racing motorcycle can be changed in order to obtain a better lap,” said Kostenarov.

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Ducati has also used data to design apps for road riders. Customers can use the Ducati Link app to track their performance, configure and set electronic parameters, check information about maintenance intervals, register travel itineraries and share their experiences with other riders.

In the future, Ducati plans to integrate third-party services with the app’s proprietary data to further improve the road riding experience.

Kostenarov envisions it warning riders of bad weather and then guiding them to nearby accommodation provided by the likes of TripAdvisor and Booking.com.

This will be added to a growing stream of information provided to customers, covering speed, position, altitude, temperature, distance, fuel, and time on the road, which could combine to provide personalised advice that integrates conditions on the bike, road and rider.

Kostenarov will also continue to push for more speed in the future, which he believes could be increased through the use of 5G and quantum computing.

“This will give huge computational power for everyone,” he said.

Vendor strategy

In addition to the HCI used by the MotoGP team, Ducati has also deployed NetApp’s All Flash FAS (AFF) to manage around 200 applications, the FAS8200 high-performance computing cluster for racing data analysis and simulations, SaaS backup for Office 365 and Salesforce, and the FAS8200 disaster recovery system.

The company says that combining these solutions has created a data fabric that provides mobility, retrievability, security and availability at every endpoint across edge devices, data centres and the cloud.

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Ducati also works with a range of other vendors, including Lenovo for its PCs, tablets and high-performance servers, AWS for its public cloud computing, and smaller specialist companies for highly-specific components.

The choice of supplier is guided by a combination of benchmarking and advice from external analyst firms. Kostenarov prioritises performance, scalability, cloud agnosticism and speed of delivery in his decisions.

“The technologies, like our products, evolve very quickly, so if we choose one provider but they have too long a roadmap to put inside the market a new product, it’s no good,” he said.