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It is never a bad thing to reevaluate it again if you need to implement a new solution Another aspect that is easier with database mirroring is spanning distance With failover clustering, you need a specialized geographically dispersed cluster solution that most likely has some sort of physical limitation (eg, fiber is only rated at certain distances), which you cannot avoid Database mirroring involves two separate installations that can reside on any supported hardware (clustered or not), and is not bound by distance but by the limitations of your network bandwidth and the speed of applying the transactions Last but not least, with failover clustering, you have a definite single point of failure in your disk subsystem.

The meaning of L is a bit different in the day of the month field than for the day of the week When used in the day of the month field, it means the last day of the month (March 31, February 28 or 29, and so on) When used in the day of the week field, it has the same value as 7 Saturday The L special character is most useful when you use it with a specific day of the week value For example, 6L in the day of the week field means the last Friday of each month W is only allowed for the day of the month field and specifies the nearest weekday (Monday Friday) to the given day of the same month Set the value to 7W, and the trigger will be fired on the sixth day if the seventh happens to be a Saturday.

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Configuring your disks with some sort of RAID gives you some redundancy, but if you are not deploying a geographically dispersed failover cluster, your disks are all part of the same set of enclosures in one data center and become your single point of failure Database mirroring s architecture enables redundancy across distance to another data center..

If the seventh day is a Sunday, the trigger fires on Monday, the eighth day Note that a trigger due on Saturday the first will actually fire on the third..

Once you have attached the database, you can move on to loading the sample reports into the VS or BIDS project. The project is in the C:\Program Files\Report Packs\CRM\ Report Definition Files folder and is named CRM Report Pack.rptproj. If you have been using the Pro_SSRS solution throughout the book, you can simply add this project to the Pro_SSRS solution by right-clicking the Pro_SSRS solution in Solution Explorer and selecting Add an Existing Project. Navigate to the CRM Report Pack.rptproj file, and click Open. With the project open, you can see one data source and six reports. The data source, Adventure_Works_Cycle_MSCRM.rds, points to local host by default, so if your Microsoft CRM sample database was attached to the local instance of SQL Server, you should not have to change it. If your database is on another server, you will have to double-click the data source and change the Data Source value to point to your server by name. Let s open one of the sample reports, Lead Summary, and look at what it offers. When you double-click the Lead Summary.rdl file in the CRM Report Pack project, the first thing you should notice is a dialog box informing you that the report must be converted to the current report definition format and that the report cannot be edited in previous versions of Report Designer, as shown in Figure 10-3.

Log shipping is hard to compare to failover clustering in a meaningful way, as it does not act or feel like clustering at all. Log shipping is based on a core functionality of the SQL Server engine: backup and restore. It only protects a single database, has no options for automatic failover, and the server

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switch is not abstracted from the client connections. The one thing that log shipping has on failover clustering is that it is easy to implement over long distances. Can log shipping provide the same availability as failover clustering In some cases the answer is absolutely yes, but your deployment would need to know all the caveats that go along with log shipping. Log shipping works much better as a disaster recovery technology than as a high availability technology and can complement failover clustering in this capacity.

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