Why Computer Systems Fail PODS

The last years have seen dramatic changes in the way the world st es, manages, and uses its data. Whereas the end of the previous millennium saw an emphasis on decentr alized, desktop-based storage and manipulation of data, we are now seeing information technology returning in reat part to a model of centralized, professionallymanaged computation and data delivery services, using incr easingly more ubiquitous networks. This is however not a return to the era of mainframes, but rather a segregatio n of the IT world into small, end-consumer devices on one hand, and the infrastructures to support and interconne t th se devices on the other. One might argue this is a more natural division of functionality. This model of infrastructure-provided compute services ha s enabled a rich landscape of technological enhancements to our daily lives, ranging from e-mail, SMS, to e-bank ing, e-government, and e-voting. At the same time, the new usage models have encouraged outsourcing, have brou ght about large clusters of commodity hardware, and generally have pushed the providers to optimize for cost and peak performance, while initially ignoring traditional mainframe virtues like reliability and manageabili ty. In such a service-oriented world, dependable computing inf rastructures become indispensable. For example, organizations rely increasingly more on e-mail and instant messaging for communicating and making decisions on business-critical matters; Osterman [2001] found that los s of e-mail access (whether due to downtime, viruses, or other reasons) can result in up to a 35% decrease in worker pro ductivity. Infrastructures are critical to the viability of many sectors of the economy; according to Patterson [2002 ], service outages can cost tens of thousands to millions of dollars per hour, with collateral damage rangin g from loss of customers to drops in market valuation, as described by Fox and Patterson [2002]. As witnessed just a few years ago (Poulsen [2004]), the risks of failure