SmartTier and other features supported by heterogeneous LUNs


Heterogeneous LUNs support HyperSnap, HyperReplication, SmartMigration, HyperMirror, SmartQoS, SmartMulti-tenant and SmartPartition. However, Heterogeneous LUNs do not support the SmartTier feature.

Other related questions:
Do HyperMetro LUNs support value-added features such as snapshots and remote replication?
A LUN that has been added in the HyperMetro domain support snapshots and can function as the primary LUN in remote replication, that is, the active-active data center solution can be expanded to the 3DC disaster recovery solution. In addition, active-active LUNs are compatible with value-added features such as SmartQoS, SmartCache, and SmartTier.

Migration modes supported by SmartTier
See section "Configuring a SmartTier Policy" in SmartTier Feature Guide, which is available at

Whether the SmartTier feature of the OceanStor V3 Series supports cross-engine data migration
The SmartTier feature does not support cross-engine data migration.

Feature of stripe depth of LUNs
The stripe depth refers to the size of blocks in a stripe of a disk array that uses striped data mapping. It also refers to the size of consecutively addressed virtual blocks mapped to a consecutively addressed disk blocks on a single member extent of a disk array. Therefore, choose the most appropriate stripe depth based on the size of data I/Os. If the storage system is used to store a large number of sequential data, such as media data, a large stripe depth is recommended. The recommended stripe depth is more than 64 KB. If the storage system is used for storing a large number of random data, such as the transaction processing data, a smaller stripe depth is recommended. The recommended stripe depth is 32 KB.

Feature of the LUN variable prefetch policy
1. After receiving a data read request, the storage system prefetches data to the cache based on a multiple of the read length specified in the I/O request. 2. This policy applies to sequential read applications with variable-size data or to multi-user concurrent read applications with an unknown data prefetch amount, for example, multi-user Video on Demand (VOD) initiated by users at different bit rates.

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