This topic describes advanced data management settings for dSources.
When linking a dSource, you can use custom data management settings to improve overall performance and match the needs of your specific server and data environment. If no specific settings are required, leverage default data management settings.
Accessing Data Management Settings
There are three ways to set or modify data management settings for dSources:
During the dSource linking process, in the Policies tab of the Add dSource wizard, select the Retention Policy.
Or select Manage, then select Policies. To manage retention on target after the dSource snapshots have been deleted from the replication source, select the Replica Retention tab.
In the Policies screen, select the Retention tab.
To add a new retention policy click the +Retention button, and to add a new replica retention policy on the replication target, click the +Replica Retention button.
This will open the Retention Policy wizard. Enter a policy name, select your retention periods and click Submit.
For more information, see Policies for Scheduled Jobs.
Retention Policies - Retention/Replica Retention
Retention policies define the length of time Delphix Engine retains snapshots within its storage. To support longer retention times, you may need to allocate more storage to the Delphix Engine. The retention policy – in combination with the SnapSync policy – can significantly impact the performance and storage consumption of the Delphix Engine.
Replica Retention policies define how long the snapshots are retained on replicated namespaces for dSources and VDBs after they have been deleted on the replication source. Normally, the snapshots that have been deleted on the replication source engine are also deleted on the replication target engine. A new retention policy is introduced to provide an extended lifetime of such snapshots on the replication target.
Benefits of Longer Retention
With increased retention time for snapshots and logs, you allow a longer (older) rollback period for your data.
Common use cases for longer retention include:
Frequent application changes and development
Caution and controlled progression of data
Reduction of project risk
Restore to older snapshots