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PowerStore storage volumes are created and mapped to the host for each disk or mount point that is presented to SQL Server.
There is a balance between manageability and performance that is unique to each environment. Generally, fewer volumes are easier to manage while more volumes enable better performance and optimize for features such as storage replication, Metro Volume, filegroup backups, and piecemeal restores.
When creating a new database, if there is a possibility your SQL Server workload will require performance from multiple volumes, create the database with multiple data files. It is much easier to simply relocate a data file in the future than to add additional database data files and rebalance the data.
There are many types of files that are part of a SQL Server instance. These types of data often have different performance and snapshot requirements. For performance-sensitive applications, Dell Technologies recommends creating at least five volumes for an instance of SQL Server as shown in the following table.
Table 2. Volume provisioning recommendations
File type | Number of volumes per instance | Typical performance requirements | Typical snapshot requirements |
User DB data | 1+ | Lower performance may be acceptable | Frequent snapshots, same volume group as log volumes |
User DB transaction log | 1+ | High performance required | Frequent snapshots, same volume group as data volumes |
Data root directory (includes system DBs) | 1 | Lower performance may be acceptable | Infrequent snapshots, independent schedule |
Tempdb data and transaction log | 1 | High performance required | No snapshots |
Native SQL Server backup | 1 | Lower performance may be acceptable | Snapshots optional, independent schedule |
Memory-optimized filegroup (if used) | 1+ | High performance required | Frequent snapshots, same schedule as log volume |
Associate databases that span multiple volumes within a volume group. This helps ensure that other features such as snapshots, replication, and thin clones will be configured properly and maintain data consistency.