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systems sold by Tandem (ironically, in 1997 Tandem was also acquired by Compaq), DEC began to introduce their VMScluster in 1980 and continued enhancing it well into the 1990s VMScluster was a distributed computer system, made up of multiple, thenstandard VAX CPUs and storage controllers, connected by a high-speed serial bus, which supported simultaneous connections to as many as 16 nodes VMS was extended to permit each major system facility to run on each CPU in the cluster; the CPUs communicated with each other on the serial bus Two key pieces of software were developed: a distributed lock manager to manage multiple CPUs trying to write to the same disks and a connection manager that determined which CPUs were active at any particular time and coordinated their efforts The result was a single distributed operating system that ran across multiple CPUs.



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Services were delivered continuously as long as a majority of the CPUs and their OSs were operating Functionally, VMScluster delivered nearly continuous operations, with little or no interruption when a CPU or OS failed In 1991, a Wall Street financial firm was concerned because their trading systems, which ran Sybase s RDBMS on SunOS, were having failures The failures interrupted the firm s ability to trade and cost them a lot of money They contracted with Fusion Systems, a small New York City consulting company, for Fusion to produce software that allow a system that had failed to automatically migrate its services to a dedicated standby system that would take over and continue running the services Although the firm did not deploy the product, Fusion turned this project s output into the first commercially available failover software for SunOS, called High Availability for Sun.

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It was a very limited product; early releases only supported failing over to a dedicated standby system (this configuration is called asymmetric or active-passive failover) in two node clusters Around the same time, Hewlett-Packard released SwitchOverUX, their first entry into the clustering space In 1992, IBM acquired their first clustering software, HA/CMP, from a small company called CLaM Associates (now called Availant), making it available for AIX After a few years, HA/CMP became the first clustering software that supported as many as 16 nodes in a cluster It was designed specifically for NFS and could not be used with other applications Later, in 1992, a group of former Sun SEs in Silicon Valley decided that they could write a better failover product They formed their own company, called Tidalwave Technologies, and wrote a product called FirstWatch.

where pij is the steady-state probability, that is, pij m Gji pij P i i ; k pk m Gk 17:32

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It was better able to support symmetric or active-active failover in two node configurations (for more on clustering configurations, see 17) FirstWatch was also easier to install and configure than the Fusion product Tidalwave had entered into an agreement for Qualix, a California reseller, to exclusively sell FirstWatch, which is why many people at the time believed that FirstWatch was a Qualix product..

with pi the steady-state vector of the Markov chain Pi pi pi Pi and m Gji the mean of Gji for Gj in Eq. (17.8), for all sources i. With the steady-state mean, there is no conditioning. Section 17.2 gives the formula for conditioning on both level and age. Now we give the formulas conditioning only on the level; that is, we condition on the level, assuming that we are in the steady state. We omit the i superscript. Then the age in level j has the stationary-excess cdf Gje t 1 m Gj t

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Adam Greco is director of Web Analytics at Salesforce.com, which makes him responsible for measuring everything online right up until people log into salesforce.com as a customer. Salesforce.com is now in the listening stage monitoring how often they are talked about in various channels. We re trying to nd out who s talking about us, who s talking about our competitors and gure out what they re saying. We re doing out bound as well we have a whole YouTube channel and a Facebook channel with one or two people who just focus on getting our message out, but I m analyzing what people are saying about us. Adam integrated Omniture s SiteCatalyst with Twitter, creating a list of three types of keywords. First is their branded keywords that mention their company. The second group is competitor keywords. The third group is general, industry keywords they care about. So for example in our case, cloud computing or CRM. Using the Twitter API, we go out to Twitter and pull any tweets that mention those phrases on an hourly basis. So, we now have charts and graphs to monitor over time and we can be alerted through the e-mail or a cell phone device if there s a spike. Managing by alarm is a time-honored tradition. There is a certain background noise level to be calibrated. A certain number of mentions is normal traf c. Should the general tweeting public stop talking about the company altogether, then the PR and marketing departments need

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