Disaster Tolerance and Recovery in a Serviceguard Cluster

Disaster Tolerant Architecture Guidelines

Protecting Data through Replication

The most significant losses during a disaster are the loss of access to data, and the loss of data itself. You protect against this loss through data replication, that is, creating extra copies of the data. Data replication should:

•Ensure data consistency by replicating data in a logical order so that it is immediately usable or recoverable. Inconsistent data is unusable and is not recoverable for processing. Consistent data may or may not be current.

•Ensure data currency by replicating data quickly so that a replica of the data can be recovered to include all committed disk writes that were applied to the local disks.

•Ensure data recoverability so that there is some action that can be taken to make the data consistent, such as applying logs or rolling a database.

•Minimize data loss by configuring data replication to address consistency, currency, and recoverability.

Different data replication methods have different advantages with regards to data consistency and currency. Your choice of which data replication methods to use will depend on what type of disaster tolerant architecture you require.

Off-line Data Replication

Off-line data replication is the method most commonly used today. It involves two or more data centers that store their data on tape and either send it to each other (through an express service, if need dictates) or store it off-line in a vault. If a disaster occurs at one site, the off-line copy of data is used to synchronize data and a remote site functions in place of the failed site.

Because data is replicated using physical off-line backup, data consistency is fairly high, barring human error or an untested corrupt backup. However, data currency is compromised by the time delay in sending the tape backup to a remote site.

Off-line data replication is fine for many applications for which recovery time is not an issue critical to the business. Although data might be replicated weekly or even daily, recovery could take from a day to a week

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Chapter 1