On your customer's AFF A700, there are multiple volumes within the aggregate aggr1. Within aggr1, volumes vol1, vol2, and vol3 store similar data, and volumes vol4 and vol5 store unique data.
In this scenario, which feature would improve storage efficiency with the data stored in volumes vol1, vol2, and vol3?
Inline aggregate-level deduplication is the most suitable feature for improving storage efficiency with the data stored in volumes vol1, vol2, and vol3, as it eliminates duplicate blocks across multiple volumes within the same aggregate. Since these volumes store similar data, deduplication will significantly reduce the storage footprint by identifying and removing redundant data blocks.
C, Aggregate-level deduplication eliminates duplicate blocks across volumes belonging to the same aggregate . see : https://docs.netapp.com/ontap-9/topic/com.netapp.doc.dot-cm-vsmg/GUID-4D7038D7-F215-4A3C-AF6A-B7895AFA6A33.html
which feature would improve storage efficiency with the data stored in volumes vol1, vol2, and vol3--- Data "Stored" after the fact -- postcompression
vol1 vol2 and vol3 have similar data = deduplication.
ans is C
I think c
Think this is correct. Data Compaction is across one volume, not multilple volumes with similar data. Aggregate-Level spans multiple volumes.
I think C as well but you can enable compation at the aggregate level Enable data compaction on the aggregate and volume: For aggregates: node run –node node_name –command wafl compaction enable –A aggregate_name For volumes: node run –node node_name –command wafl compaction enable volume_name