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Most systems are connected to many more physical disks than they are to any other component. If your system has 100 disks in it, each with an MTBF of 200,000 hours (almost 23 years), that doesn t mean that you ll be error-free for two decades and then, on one really bad day, all 100 disks will fail at once. Each disk has the same probability of errors, but as the number of disks increases, the probability that no disk will have an error goes down exponentially. The actual MTBF for a system with that many disks can be calcuated by combining the probability distributions and determining the new mean and standard deviation for the system with 100 interrelated components in it. This approach is beyond the scope of this and, thankfully, most other books.



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Remember 1: Getting Focused Identifying Goals The Big Three Goals are very important, but it s time to get just a little more granular. The bottom line is great for the quarterly report, but it s not so good for navigation, which requires constant sightings and adjustments. The old saw about keeping an eye out the windshield instead of only on the rearview mirror is applicable. Business outcomes are the results that help improve the bottom line. They are the indicators that provide feedback on whether you are likely to meet your goals or not. You can t have pro ts without income. You can t have income without customers. You can t have customers without prospective customers. You can t have prospects without suspects. You can t have suspects without awareness.





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Instead we propose a very rough, and very conservative, rule of thumb: Divide the MTBF for a specific component by the number of those components in the system, and you have something of a worst-case time to your first failures. With a 200,000-hour MTBF, you should expect a 50 percent chance of failure per disk in the first 200,000 hours, but over 90 percent of those failures fall within one standard deviation of the mean. With 100 disks, our simple math works out to 200,000/100, or about 83 days for a 50/50 chance of at least one disk failing. With MTBFs in the 30,000 hour range,1 power supplies tend to have the worst MTBF figures for any component in the system. But since you only have a few of them, the overall frequency of failures will be lower than for disks. Your system may only have six power supplies, giving you a good shot at a failure in just over 200 days, using the same voodoo math approximation we used for disks.

9:40

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There are several OCR ( Optical Character Recognition ) software solutions available to convert scanned images to text, Word, Excel, HTML or searchable PDF. The differences between them can often be obscure, leaving many to wonder why some OCR software cost about $100 while others cost $500 or more.

My introduction to reliable systems began nearly 10 years ago, when I worked with the Foxboro Company to port their real-time, industrial control system from proprietary hardware to the Sun platform You never really consider the impact of a hung device driver or failed disk drive until the device driver is holding a valve open on a huge paint mixing drum, or the disk drive is located along the Alaskan oil pipeline under several feet of snow As the Internet has exploded in popularity, reliability and uptime engineering are becoming staples of our diet, because web surfers have caused us to treat most problems as real-time systems As system administrators we have to decide just how much money to pour into reliability engineering, striving for four-nines (9999 percent) or five-nines (99999 percent) uptime while management remarks on how cheap hardware has become.

upon invoking Eq. (9.36) and the lower bound (9.34) (with G I; y ). This is essentially Theorem 2.1 of Duf eld and O'Connell [10] and shows the local nature of the lower bound. As the best lower bound is the largest, we can immediately sharpen (9.40) into the lower bound (9.4) with g given by (9.37). j The existence of (9.34) (and for that matter, of (9.35)) is typically validated through the Gartner Ellis theorem [9, Theorem 2.3.6, p. 45]. In that context, for each t 1; 2; . . ., we de ne 1 yvt Lt y ln E exp S ; vt t t and it is required that for each y in R, the limit L y lim Lt y

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