Drivers win races— this is an undisputed fact. However, drivers don’t reach the podium on their own. Behind them are dedicated teams ensuring all assets are leveraged in order to secure victory, including every available data.

This is why racing teams Aston Martin, Ducati, and Porsche have renewed partnerships with NetApp, in order to innovate faster on and off the track. The three teams were all present during the NetApp INSIGHT 2024 conference in Las Vegas, to share details of the partnerships, as well as their data strategy coming into the races in their respective leagues.

“The drivers and the team behind them are important factors for winning a race, but you have to give them the best opportunities and possibilities to work with. For this, they need to have access to the latest tools and data available,” noted Paul Stiegle, IT Product Owner and Software Engineer, Porsche Motorsport.

Racing for success

For Formula One team Aston Martin, partnering with NetApp was primarily for two reasons. The first one, was to ensure that the platforms it deploys are robust, durable, and effective, both at the races, and at its factory headquarters.

Secondly, Aston Martin leverages NetApp to improve business decisions, particularly with pre-sales engagements and strategic mapping. According to Stuart Bailey, Aston Martin F1’s Head of Infrastructure, the team just deployed a storage grid on-premises on a petabyte scale, which will bring all their data in one place, and give them a platform to leverage AI capabilities.

Aside from this, the team just commissioned a new FlexPod unit in its factory, which shall become its new computing cluster. FlexPod is NetApp’s hybrid platform combining compute, storage, networking, and management to help customers accelerate the delivery of modern workloads and future-proof their environments.

Generally, Aston Martin F1 runs extensive data analytics across all parts of the business.

“We’ve got an in-house developed vehicle simulation model, which we use for tweaking conflicts and parameters on the car for anything, from set ups for one particular corner to an entire lap, that helps drive decisions for the track side environment when we’re running out on a race and we want to set up a car in an optimal manner,” Bailey said.

For running computational fluid dynamics, as well as finite element analysis, the latter in order to see how structures react to load and force, Aston Martin F1 leverages a high-performance computing platform, which is a restricted aerodynamic analytics platform. 

“This helps drive our decisions as to how we develop the car, what parts to develop, and how we design this and that. It’s great to be able to understand how the tires and the entire car are going to react to the load before we manufacture something. Those insights allow us to make good decisions about how we develop the vehicle,” he said.

Pedal to the metal

Meanwhile, at Formula E, Tag Heuer Porsche team finished second during the 2023-2024 season, with a total of 332 points. During the first race this season at the São Paulo Grand Prix, the team placed third, while driver António Félix da Costa snagged P2. 

According to Stiegle, tons of data gets produced every millisecond that the team runs its cars. Therefore, it’s very important to harness the insights out of these data in order to improve both driver and vehicle performance.

“We measure the vehicle speed, every position of the brake pedal, every temperature, and every tire pressure,” he shared.

Infrastructure-wise, Porsche decided to go with cloud deployment, using NetApp Cloud Volumes ONTAP data management platform.

“With ONTAP, we have the possibility to have a unified structure of our data there, and we have flexibility whether we’re at the track, at our development centre, or if we’re using it with automation in the cloud,” Stiegle explained.

Like many of its peers, Porsche has also explored the use of AI to harness intelligent data insight, particularly for car setup during simulator sessions.

“In the past, we used this very complicated model to compute what happens when we would use this car setup, or that setup, and this took several minutes to compute until we have a result. Often, you do not have so much time, hence, you need to know exactly what changes to make quickly,” the software engineer added.

To fix the issue, Porsche trained an AI model, which shifted compute time from minutes to seconds.

“We need to have the data prepared, and we often need to retrain the model based on what we’ve seen on the track so far. Therefore, we need to be able to get data fast from the car into our storage, and then we model onto it,” he continued.

Sharp curves

Over at MotoGP, Ducati bagged first place, both at the Team’s Championship and Constructors’ Championship categories for the 2024 season. With the new season just started, the racing team is determined to hold onto its title. 

Pivotal to Ducati’s success is the support from NetApp. Ducati leverages NetApp both on and off the track, with both teams working seamlessly.

“All of them are receiving the data that we get as soon as the motorcycle enters the garage, and they are working on such data very, very quickly with our tools, because we need to define the new settings of the motorbike in a very, very short time to be able to give an advantage to our riders. It’s very important to have a partner that allows us to exchange data at the speed of light,” noted Roberto Canè, eMobility Director, Ducati Motor Holding. 

In contrast to Porsche, the MotoGP team favoured on-premises infrastructure, although it is not closing the doors on cloud.

“For the moment, we use on-premises structure and dedicated structure at the racetrack. We are thinking about cloud, but we are a little bit worried about the confidentiality of data. So for the moment we’re still staying with on-premises data and track side servers. It was very important to have a partner like NetApp who was able to provide us with the FlexCache product, for example, in order to be sure that such data goes back and forth to Ducati in a safe way,” he shared.

Podium finish

On the track, a lot of delays can happen— a tire replacement could take a few seconds too long, communication systems may be malfunctioning, or the vehicle can suddenly lose power. While inevitable in a competitive sport, a lot of these challenges can be alleviated with AI and data analytics.

“No delay would be the best delay, but that would be impossible. However, with every second you save, you have more time to decide what you’re going to do, especially during the endurance race. That’s very important when you need to decide when to do the next pit stop and so on. With every second we have, we gain opportunities to maybe have the pit stops later or earlier, or change something in the setup,” Stiegle said.

Indeed, access to data in today’s enterprise landscape cannot be delayed — not when speed is the name of the game. This is especially true with Ducati, which had trouble accessing data at the factories during the pandemic. With most of its staff at home, there was no way to get real-time data. Following its partnership with NetApp, the company made a complete 360, culminating in its major wins during the 2024 season.