Which NetApp technology enables prepopulating a subset of data for an AI Center of Excellence?

• A. Flash Cache
• B. SnapVault
• C. FlexCache
• D. Flash Pool

Answer: (C)

Preloading data closer to the AI compute environment is about caching frequently used data so the AI workloads don’t have to repeatedly fetch it from a distant store. FlexCache creates a caching layer that sits between your AI compute cluster and the primary data source, caching a selected subset of data locally. By pre-warming this cache with the data you expect to use, you reduce latency and improve throughput for training or inference tasks. This makes it ideal for an AI Center of Excellence that wants fast access to a known working set.

Flash Cache caches hot data on the array’s own flash, but within the storage controller rather than across a separate compute edge; it doesn’t provide the edge-local prepopulation of a remote data set. SnapVault is focused on backups, not caching for AI workloads. Flash Pool speeds up the storage array itself by using flash within the array, not by creating a cross-cluster caching layer for AI data.