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For some mission-critical applications, uptime and availability are of the utmost concern. It s important to determine the information associated with how long a backup operation may take. This period is often called the backup window. In calculating the time available for performing backups, you ll need to consider the nature of the system and details about your business operations. For example, if your organization is multinational and requires OLTP systems to be available 24 hours per day, your backup requirements must be scheduled for times that are least busy, to avoid adversely affecting users. If the majority of employees work in a single time zone from 8:00 A.M. to 5:00 P.M., however, you will be able to find much larger windows of time for these operations. Note that it s possible that what you think are the busiest hours may not be. Different types of users might perform operations (such as scheduled jobs) at times that you would not have otherwise expected. Be sure to monitor database activity before jumping to conclusions. In later chapters, we ll use the information about the backup window to decide what type of hardware to implement.
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Recovery Requirements
When planners are evaluating business needs, they may forget to factor in the potential time for recovering information. The question they should ask is the following: If we lose data due to failure or corruption, how long will it take to get it back In some cases, the answer will be based on the technical limitations of the hardware you select. For example, if you back up 13GB of data to tape media and then lose it all, the recovery time might be two hours. But what if that s not fast enough Suppose your systems must be available within half that time one hour. In that case, you ll need to make some important decisions. An obvious choice is to find suitable backup hardware to meet these constraints. If budgetary considerations don t allow that, however, you ll need to find another way. In later chapters, we ll look at several technical solutions. For now, consider how long your business can realistically tolerate having certain information unavailable.
Budgeting for Data Protection
When you are developing the real business constraints for your backup plan, higher-level managers often ask the question What is this solution going to cost Information technology professionals, on the other hand, ask What is the budget for this solution Both questions are valid, but neither can be answered without first determining how expensive the alternative is: losing information. Indeed, the types of solutions you choose will depend on your actual budget constraints. Nobody likes to experience data loss. It s frustrating, and can undermine productivity. Unfortunately, similar complaints are often heard about backup operations that they take up time and other resources. Somewhere in the middle is an optimal solution
1:
Evaluating Corporate Data Requirements
that provides adequate (though not perfect) data protection methodologies. When presenting a data protection strategy to upper management, you ll likely be asked why certain types of failures should be protected against at all. Though the answer may seem obvious at first, we need to quantify our preconceptions of the impact of data loss. Thus, we ll now look at how to prioritize the value of your data, based on some simple questions.
Estimating the Cost of Downtime
Let s start by trying to weigh the costs of losing information. This can be quite difficult in most situations, because exact values often aren t known, and you may have to do your homework before you can calculate what your data is worth. In many cases, however, it s not important to have exact values; approximations are enough. Using these ideas, let s look at the how we might calculate the costs of downtime for an e-mail server. First, you might start by figuring out how many users depend on the server. However, this information alone doesn t give you everything you need. It s a simple fact of business that not all e-mail being sent is mission-critical. Plus, the company might be impacted more if an executive can t send messages than if administrative assistants can t send messages. In any case, you can attempt to get more information (such as the average number of e-mail messages that are sent to and from the server per hour) and assemble a best guess on the value of the machine. Also, the longer a server is down, the greater the cost of the downtime. If the accounting department is down for only 15 minutes, clerks might be able to catch up with their workload by the end of the day without missing any deadlines. However, if the server is down for a whole day, many business processes might be disrupted. It is these ripple effects that are most difficult to calculate. Table 1-3 offers some guesses as to what downtime for various machines might cost an example organization. Remembering our goal to find the value of data protection we could further complicate matters by factoring in the probability that these machines will be unavailable. If your company has kept good historical logs of downtime, this might be possible. However, it s probably more likely that you ll assume that the probability for downtime is a constant. Of course, the costs associated with downtime are only part of the picture. The preceding example assumes that information will not be lost. But what about situations when it is
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