Extreme Savings through Modern Storage Architecture

This 19-minute talk from the Open Compute Project features Kyle Lamb, Field CTO HPC at VAST DATA, discussing how modern storage architecture can dramatically reduce costs and improve analytics capabilities. Learn how traditional analytics architectures suffer from inefficiencies in data movement and search time due to storage technology limitations. Discover how a modern approach designed specifically for analytics and seamless integration of structured and unstructured data can cut costs by offloading search operations, reducing network strain, and minimizing record sizes—all while improving data resolution and lowering CPU and GPU usage. Explore how unifying data types enables deeper AI-driven insights through advanced pattern recognition, anomaly detection, and predictive analytics. See how modern data reduction techniques, erasure codes, and advanced hash functions optimize storage efficiency while reducing the overhead of maintaining multiple storage types. The presentation demonstrates how modernizing the storage layer can potentially reduce processing resource requirements by 50% and storage costs by 75% while simultaneously enhancing AI-driven intelligence capabilities.