DC: Small: Collaborative Research: DARE: Declarative and Scalable Recovery

当今大规模计算系统的一个主要特征是大型存储集群的流行。成百上千台商用机器规模的存储集群正在被越来越多地部署。在亚马逊、谷歌、雅虎和其他公司，数千个节点被作为一个系统进行管理。由于大型集群带来了许多好处，它们也带来了新的挑战：必须管理的故障数量和频率不断增加。位、扇区、磁盘、机器、机架和许多其他组件出现故障。拥有数百万台服务器和数百个数据中心，这些组件有数百万次失败的机会。不处理故障将直接影响数据和作业的可靠性和可用性。不幸的是，即使在最近，我们仍然听到数据丢失的故事。例如，2009年3月，Facebook因同时发生的磁盘故障而丢失了数百万张照片，而这在同一时间是很少发生的(但它发生了)；2009年7月，一家大型银行在丢失了数千名客户的数据后，被罚款总计300万英镑；更近的是，在2009年10月，使用微软云服务的T-Mobile SideKey也丢失了客户数据。为了应对大规模恢复的挑战，该项目的目标是：(1)在当今可扩展的计算世界中寻找恢复的根本问题，(2)提高现有大规模恢复的可靠性、性能和可扩展性，以及(3)探索正式的基础语言，以赋予恢复属性和行为的严格规范。我们的愿景是建立“敢于失败”的系统：故意自我故障的系统，定期进行恢复，并使新的恢复策略能够轻松而正确地部署。有关更多信息，请访问以下网站：http://boom.cs.berkeley.edu/dare/

One dominant characteristic of today's large-scale computing systemsis the prevalence of large storage clusters. Storage clusters at thescale of hundreds or thousands of commodity machines areincreasingly being deployed. At companies like Amazon, Google, Yahoo,and others, thousands of nodes are managed as a single system.As large clusters have brought many benefits, they also bring a newchallenge: a growing number and frequency of failures that must bemanaged. Bits, sectors, disks, machines, racks, and many othercomponents fail. With millions of servers and hundreds of datacenters, there are millions of opportunities for these components tofail. Failing to deal with failures will directly impact thereliability and availability of data and jobs.Unfortunately, we still hear data-loss stories even recently. Forexample, in March 2009, Facebook lost millions of photos due tosimultaneous disk failures that "should" rarely happen at the sametime (but it happened); in July 2009, a large bank was fined a recordtotal of 3 millions pounds after losing data on thousands of itscustomers; more recently, in October 2009, T-Mobile Sidekick, whichuses Microsoft's cloud service, also lost its customer data. Theseincidents have shown that existing large-scale storage systems arestill fragile to failures.To address the challenges of large-scale recovery, the goal of thisproject is to: (1) seek the fundamental problems of recovery intoday's scalable world of computing, (2) improve the reliability,performance, and scalability of existing large-scale recovery, and (3)explore formally grounded languages to empower rigorous specificationof recovery properties and behaviors. Our vision is to build systemsthat "DARE to fail": systems that deliberately fail themselves,exercise recovery routinely, and enable easy and correct deployment ofnew recovery policies.For more information, please visit this website:http://boom.cs.berkeley.edu/dare/