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the SLA. Thus, you should specify the user count for which the agreement is valid, and you can consider specifying how much notice you should be given for an addition of new users, as shown in the sample SLA in Figure 6-1. This notice gives you time to add hardware if necessary. Create an agreement that you can live up to. You should make sure that the SLA is something that you can meet and exceed. You must then develop metrics and processes for measuring your system in order to validate that the SLA is being met.

1. On the Microsoft Windows task bar, click Start and then click Computer . 2. In Windows Explorer, navigate to the C:\Microsoft Press\Analysis Services 2008 SBS \ 15\AdventureWorks BI\AdventureWorks SSAS\bin folder . Note that there are four files in this directory . These files are created when the build process is executed from BIDS . Table 15-7 describes these four files .

Figure 6-1

7. After you have selected all the files you want to delete, click OK. 8. Click Yes to confirm that you want to proceed with the deletion. As Disk Cleanup completes the selected operations, a progress bar indicates how the cleanup is proceeding. You can cancel the cleanup at any point during the operation. The Disk Cleanup dialog box closes when the operation is complete.

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The fundamentals of sizing and capacity planning are based on queuing theory. Queuing theory is the mathematics that governs the effects of multiple entities all using the same resources. For those of you hoping that you would never have to do mathematics again, I apologize. Sizing, capacity planning, and performance tuning are all about mathematics. The concept of queuing theory is quite straight-forward. Before jumping into queuing theory we will start by defining two terms: service time and wait time, or queue time. Service

6

time is the time that the action that you are measuring takes to complete. Wait time, or queue time, is the time that the action that you are measuring is waiting for all of the jobs ahead of it to complete. The response time of your job is equal to the service time plus the queue time, as this formula shows:

TABLe 15-7

For example, the time it takes you to make a deposit at the bank is the sum of the time it takes to make the deposit, plus the time you have spent waiting in line Total task time is measured in the same way with almost every operation in your computer hardware and software The amount of time spent queuing depends on the capacity of the resource used In some cases there is no queuing, and in other cases there is significant queuing In Figure 4-4 in 4, I/O Subsystem Planning and RAID Configuration, you saw how latencies increased as you neared the capacity of the disk drive This is true throughout the computer system A lightly used resource might experience no queuing, but the closer you get to the capacity of the resource, the higher the chance of queuing.

When you reach the capacity of a device you are guaranteed to queue For example, if there are four bank tellers, and four customers arrive at the bank at the same time, there is a chance that you won t have to wait in line (if there is nobody already in line) However, if five people arrive in line at exactly the same time, then there is a 100 percent probability that someone will have to wait If there is one teller, if it takes one minute for each transaction, and if there are 10 people arriving over a 10-minute period, there is a chance that they won t have to wait (if they arrive at exactly one-minute intervals) Thus, the closer you get to the maximum capacity of any resource, such as bank tellers, disk drives, CPU, and so on, the more chance you have of queuing.

When you reach the maximum capacity of the resource, you have a 100 percent chance of queuing, and then queuing increases as the utilization increases The chance of having to wait depends on how close you are to the capacity of the resource, as Figure 6-2 shows Queuing theory, as it pertains to sizing and capacity planning, has two components: 1 The chance of queuing increases exponentially as you near the capacity of the resource 2 The response time is equal to the sum of the service time plus the queue time The rest of this chapter will use these concepts to explain capacity planning and sizing..

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