The Value of Availability in .NET

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The Value of Availability
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Figure 3.6 Four different technologies that can reduce downtime after a data center failure.
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This example only considers one type of outage. There are, of course, any number of failures that can cause system downtime, and each of them has its own set of protective measures. For many failures, proper protection will mean zero downtime for example, the failure of a disk in a system where disks are protected with RAID technology, such as disk mirroring. For a detailed discussion of RAID technology, please refer to 7, Highly Available Data Management.
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Figure 3.7 shows that outages don t only reach forward in time; they can also reach backwards and affect data that users have already entered and believed was committed. Sometimes the data may have been acted upon by other processes. For example, an e-commerce site could bill a customer s credit card and then lose the data that would have permitted them to ship product to the customer. That s bad for everybody.
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Figure 3.7 The outage lifecycle timeline: The lost data interval.
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The lost data duration reaches backwards in time from Time T1 to Time T0, the time of the last relevant data protection event. Depending on the nature of the outage, that event could be the most recent tape backup, data replication, or mirrored disk write. As with downtime, though, there are technologies that can protect critical systems against lost data; the type of frequency of the data protection events will ultimately determine how much data will be lost in an outage. Some of these technologies, once again using a lost data center as an example, are shown in Figure 3.8. In this case, many of the same technologies that can reduce downtime also reduce lost data. That will not be the case for all types of outages. The technical term for lost data is Recovery Point Objective, or RPO. The technology choices that can affect the amount of lost data after the loss of a data center are as follows: Synchronous replication. Under synchronous replication, data arrives at the secondary host as soon as it is written to the primary data center. The downside to synchronous replication is in performance; since data must be sent across the network to the remote site, and then confirmation must come back, for each write, performance can be seriously impacted. More information on replication can be found in 18. Asynchronous replication. With asynchronous replication, you get back the performance that you lose with synchronous replication, but in return, a small number of transactions may be delayed in being sent to the secondary site. That could mean a small amount of lost data (usually less than a minute s worth), but in return for the performance boost, many enterprises consider the lost data a worthwhile trade-off. Periodic or batch replication. The data is sent from time to time under periodic replication. This means that the network load is reduced, but the data at the secondary data center could be hours, or even days out of date. Tape backup. Because backups are not taken continuously, it is almost impossible for them to be up-to-date. Backups are normally taken once a day or so, so a restore from such a backup tape will, on average, be half a day out of date. If backup tapes are not shipped off-site every day, as is often the case, then the data loss could be considerably more than half a day. Nothing. If the only copy of a data set is lost, then there is nothing to recover from, and work must restart from the time that the system and its applications went into service. Different systems running different applications across an enterprise will have different requirements for downtime and lost data, and those requirements, balanced with the cost of implementing the desired solutions, will lead the decision as to what technology will be implemented.
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