NetApp’s Novus tackles metadata bottlenecks in AI data infrastructure
AI data infrastructure must support growing GPU clusters while making enterprise data usable for models and agents. NetApp Inc. is tying intelligent data infrastructure to production AI through a unified approach to storage and data management. Fragmented data and governance designed around manually applied policies can prevent enterprises from realizing returns on AI investments, according […]…
NetApp Inc. has developed a unified approach to storage and data management called Novus, designed to tackle metadata bottlenecks in AI data infrastructure. By separating metadata management from stored data, NetApp's Data Director allows for independent scaling and provides applications with a unified view of files across multiple storage clusters.
Additionally, NetApp's AI Data Engine aims to accelerate data preparation for AI agents by discovering, classifying, and vectorizing enterprise data, potentially reducing the time required from six to nine months. NetApp also plans to integrate open standards and acquire PEAK:AIO Ltd. to bring parallel file system technology built on the pNFS protocol, allowing for seamless integration with existing systems.
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