In this world class racing series, where victories are measured in milliseconds, data management has become as crucial as engine performance. This case study examines how two elite teams leverage Cloudian’s enterprise storage solutions to manage their exponentially growing data needs and maintain competitive advantage in one of the world’s most technologically advanced sports.
The Data-Driven Nature of Modern Racing
Modern racing teams generate massive amounts of data from every aspect of their operations, especially in this series where annual budgets run into the hundreds of millions of USD per year. From wind tunnel testing to real-time telemetry data from cars during races, teams collect hundreds of gigabytes of data per car during each race weekend.
This data drives critical decisions about vehicle optimization, race strategy, and performance improvements. Engineers analyze everything from steering angles to engine sounds, using sophisticated AI models to extract competitive insights from both their own data and their competitors’ performance.
Cloudian Implementation and Benefits
Both teams chose Cloudian’s object storage solution for several key reasons.
For one team, the primary use case centers on backing up critical wind tunnel testing data. Using Rubrik software with Cloudian’s on-premises storage ensures both high performance and stringent data security. The solution provides a cost-effective way to manage large datasets while maintaining complete control over sensitive technical information.
The other team employs a hybrid approach, utilizing both AWS and on-premises storage. Their in-house software leverages S3 compatibility, making Cloudian a natural fit. During races, they collect vital telemetry data and send it to both AWS and Cloudian, maintaining redundant copies for reliability. The team particularly values Cloudian’s high S3 compatibility and its ability to run on their preferred HPE DL-series servers in an all-flash configuration.
The Future of Racing Data Management
As this premier series continues to evolve, data management requirements are growing exponentially. Both teams anticipate significant increases in their data collection and analysis needs. One plans to expand their storage of real-time telemetry and video data from cars, which generates petabytes of information from each car during every race. The other is considering moving more data on-premises, strengthening their investment in local storage infrastructure.
The rising prominence of AI in this series is a key driver of future storage requirements. Teams are increasingly using machine learning models for everything from virtual sensor implementation to competitor analysis. Cloudian’s compatibility with GPU-accelerated computing through GPUDirect makes it particularly well-suited for these emerging AI workloads.
Looking ahead, both teams recognize that their competitive advantage will increasingly depend on their ability to collect, store, and analyze ever-larger datasets. With Cloudian’s scalable architecture and high-performance capabilities, these teams are well-positioned to manage their growing data requirements while maintaining the security and accessibility their high-performance operations demand.
The combination of Cloudian’s enterprise-grade storage capabilities with the team’s cutting-edge technical requirements demonstrates how modern object storage can meet the demands of even the most data-intensive and performance-critical applications. As this elite series continues its evolution toward even greater reliance on data analytics and AI, these implementations provide a blueprint for managing the intersection of high-performance computing and massive data storage requirements.
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