How a top tier European soccer team sped up their data processing and reduced costs by 50%

What this post added

This post details how a European soccer team used Modal for processing spatio-temporal match data on GPUs. It highlights the use of Modal's serverless batch processing capabilities, rapid container startup times (seconds vs. minutes), usage-based pricing leading to a 50% cost reduction, and automatic scaling for high parallelization. The team also built an in-memory vector database on Modal for semantic search with embeddings, demonstrating cost-effectiveness compared to managed solutions. The post also mentions the ease of integrating with cloud storage and switching between CPU and GPU types.