How does log shipping work in SharePoint Server?
Log shipping replays the logs from the file share in the Azure environment to the primary replica in the SQL Server AlwaysOn availability group in the recovery environment. Log-shipped databases are not attached to the SharePoint Server farm until a recovery exercise is performed.
What are the features of SharePoint Server 2013?
SharePoint Server 2013 supports several versions of SQL Server. Depending on the installed version, you can use specific features of SQL Server, such as reporting and business intelligence (BI).
Why does log shipping not work in SQL Server?
The SQL Server logins are domain accounts that have the permission levels needed for log shipping. The log-shipping stored procedures require membership in the sysadmin fixed server role. The primary database must use the full or bulk-logged recovery model. If you switch the database to simple recovery, log shipping will stop working.
Are there any high availability options for SharePoint?
When you evaluate a high availability or a disaster recovery option for SharePoint, you must understand that not all of the options are supported by each SharePoint database. This is because of design requirements and feature characteristics. This article identifies the supported option for each SharePoint database.
How is log shipping used in SQL Server?
In the scenario described here, SQL Server log shipping is used together with Distributed File System Replication (DFSR) to copy databases and transaction logs to the recovery farm in Microsoft Azure as illustrated below.
Why do we use log shipping in azure?
Log shipping is used to copy logs from the secondary database server in the on-premises environment to the local file share. DFSR copies files from the file share in the on-premises environment to the file share in the Azure environment. In a WAN scenario, DFSR is more efficient than shipping the logs directly to the secondary server in Azure.
How is the amount of log shipped data affected?
The amount of log shipped data is affected by the daily amount of change in the content databases. The percentage of change can vary greatly depending on the content, maintenance changes, and usage peaks.