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As raw system and network performance continues to improve at exponential rates, the utility of many services is increasingly limited by availability rather than performance. A key approach to improving availability involves replicating the service across multiple, wide-area sites. However, replication introduces well-known tradeoffs between service consistency and availability. Thus, this paper explores the benefits of dynamically trading consistency for availability using a continuous consistency model. In this model, applications specify a maximum deviation from strong consistency on a per-replica basis. In this paper, we: i) evaluate availability of a prototype replication system running across the Internet as a function of consistency level, consistency protocol, and failure characteristics, ii) demonstrate that simple optimizations to existing consistency protocols result in significant availability improvements (more than an order of magnitude in some scenarios), iii) use our experience with these optimizations to prove tight upper bounds on the availability of services, and iv) show that maximizing availability typically entails remaining as close to strong consistency as possible during times of good connectivity, resulting in a communication versus availability trade-off.