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Figure 3.9 The completed outage lifecycle timeline.
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Table 3.5 Comparing Two Sets of Technologies and Their Effects on Downtime after the Same Outage LIFECYCLE PHASE Lost data WITH SUPERIOR PROTECTION Synchronous data replication results in data being up-todate and available at the disaster recovery site. There should be no lost data whatsoever. WITH INFERIOR PROTECTION Weekly full backups that are sent off-site must be retrieved and restored at the remote site. The restore process can take days or weeks. Data written after the most recent weekly backup is lost. System administrators must manually bring up each application at the disaster recovery site. This process could take days. The operations are in degraded mode while the primary site is down. But work can continue normally using systems at the disaster recovery site. If another disaster should occur, the results would be catastrophic. When the primary site has been restored to service, a downtime, similar to the amount of downtime when the outage occurred, will be incurred as data and applications are migrated back.
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Through remote clustering, applications are automatically brought up at the disaster recovery site.
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The operations are in degraded mode while the primary site is down. But work can continue normally using systems at the disaster recovery site. If another disaster should occur, the results would be catastrophic. When the primary site has been restored to service, a brief amount of downtime, similar to the amount of downtime when the outage occurred, will be incurred as data and applications are migrated back.
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In truth, of course, the outage lifecycle model is a very simple one. Outages and failures do not occur in a vacuum. While the effects of a second outage that is related to the first are accounted for in the lifecycle s Degraded Mode, one outage can bring about another in less predictable ways. One failure can cause another failure because of the additional load that the first failure puts on some other component for example, a clustered database server that handles all of the load on a single node may run out of log space or suffer from network connection loading problems. The formal analysis for evaluating multiple
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failure modes, and how a system moves from one state to another based on the probability of an individual failure, is known as a chain analysis. Chain in this context refers to the sequence of events that take the system from one state to another. If we assume that the first failure of any component in the system is sufficient to cause user-visible disruption and we concentrate on repairing those failures, then we can take a simplified view of the world and treat the overall system health, over time, as a series of single lifecycle events described previously. As mentioned in 2, making sure your system is renewable that it has the same MTBF characteristics after a failure has been repaired will allow you to simplify your view of the outage lifecycle to that of a series of individual events.
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NO MATTER WHERE YOU GO, THERE YOU ARE
It helps to know what failure is most likely, or what you should plan for in sequence. When I was about 10 years old, I was infatuated with Estes model rockets, spending at least one Sunday a month launching and frequently losing them into nearby fields. Estes sold a low-end movie camera that could be mounted on the rocket, giving you a shaky bird s-eye view of the flight. The proprietor of our local hobby shop told me that shelling out the $100 for the camera was a no-lose proposition, because if you ever lost the rocket, you could simply develop the film, watch the movie to see where the rocket landed, and then go pick it up it s impossible to lose the camera. It took me longer than it should have to decide that my $100 was better spent on something else. Hal