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Replication can be handled in several ways and at different levels in the technology stack: Disk storage system Data write operations that take place in a disk storage system (such as a SAN or NAS) can be transmitted over a network to another disk storage system, where the same data will be written to the other disk storage system Operating system The operating system can control replication so that updates to a particular file system can be transmitted to another server where those updates will be applied locally on that other server Database management system The database management system (DBMS) can manage replication by sending transactions to a DBMS on another server Transaction management system The transaction management system (TMS) can manage replication by sending transactions to a counterpart TMS located elsewhere Application The application can write its transactions to two different storage systems This method is not often used Replication can take place from one system to another system, called primary-backup replication This is the typical setup when data on an application server is sent to a distant storage system for data recovery or disaster recovery purposes Replication can also be bi-directional, between two active servers, called multiprimary or multimaster This method is more complicated, because simultaneous transactions on different servers could conflict with one another (such as two reservation agents trying to book a passenger in the same seat on an airline flight) Some form of concurrent transaction control would be required, such as a distributed lock manager In terms of the speed and integrity of replicated information, there are two types of replication: Synchronous replication Here, writing data to a local and to a remote storage system are performed as a single operation, guaranteeing that data on the remote storage system is identical to data on the local storage system Synchronous replication incurs a performance penalty, as the speed of the entire transaction is slowed to the rate of the remote transaction Asynchronous replication Writing data to the remote storage system is not kept in sync with updates on the local storage system Instead, there may be a time lag, and you have no guarantee that data on the remote system is identical to that on the local storage system However, performance is improved, because transactions are considered complete when they have been written to the local storage system only Bursts of local updates to data will take a finite period to replicate to the remote server, subject to the available bandwidth of the network connection between the local and remote storage systems
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NOTE Replication is often used for applications where the recovery time objective (RTO) is smaller than the time necessary to recover data from backup media For example, if a critical application s RTO is established to be two hours, then recovery from backup tape is probably not a viable option, unless backups are performed every two hours While more expensive than recovery from backup media, replication ensures that up-to-date information is present on a remote storage system that can be put online in a short period Server Clusters A cluster is a characteristic of two or more servers to appear as a single server resource Clusters are often the technology of choice for applications that require a high degree of availability and a very small RTO (recovery time objective), measured in minutes When an application is implemented on a cluster, even if one of the servers in the cluster fails, the other server (or servers) in the cluster will continue to run the application, usually with no user awareness that such a failure occurred There are two typical configurations for clusters, active/active and active/passive In active/active mode, all servers in the cluster are running and servicing application requests This is often used in high-volume applications where many servers are required to service the application workload In active/passive mode, one or more servers in the cluster are active and servicing application requests, while one or more servers in the cluster are in a standby mode; they can service application requests, but won t do so unless one of the active servers fails or goes offline for any reason When an active server goes offline and a standby server takes over, this event is called a failover A typical server cluster architecture is shown in Figure 7-9
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