Which NetApp technology enables prepopulating a subset of data for AI workloads?

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

Answer: (B)

Caching data close to the compute to accelerate AI workloads is what this item is testing. FlexCache provides a caching layer that sits in front of a primary NetApp data source, allowing a subset of data to be cached at the compute site. By prepopulating or warming the cache with the data the AI jobs will access, you reduce latency and back-end storage traffic, enabling faster data access for training or inference. This caching of hot data across a cache member and the origin is precisely what helps AI workloads get quicker, more predictable I/O performance.

Flash Cache is a local, on-controller flash cache to speed up reads but typically accelerates a single system’s own data access rather than preloading a specific subset for remote AI workloads. SnapVault focuses on backup and data protection, not caching for AI data access. Flash Pool combines SSDs and HDDs within a single aggregate for tiering, not a remote caching layer designed to prepopulate data for AI compute.