Abstract: Making cloud services responsive is critical to providing a compelling user experience. Many largescale sites, including LinkedIn, Digg and Facebook, address this need by deploying pools of servers that operate purely on in-memory state. Unfortunately, current technologies for partitioning requests across these inmemory server pools, such as network load balancers, lead to a frustrating programming model where requests for the same state may arrive at different servers. Leases are a well-known technique that can provide a better programming model by assigning each piece of state to a single server. However, in-memory server pools host an extremely large number of items, and granting a lease per item requires fine-grained leasing that is not supported in prior datacenter lease managers. This paper presents Centrifuge, a datacenter lease manager that solves this problem by integrating partitioning and lease management. Centrifuge consists of a set of libraries linked in by the in-memory servers and a replicated state machine that assigns responsibility for data items (including leases) to these servers. Centrifuge has been implemented and deployed in production as part of Microsoft’s Live Mesh, a large-scale commercial cloud service in continuous operation since April 2008. When cloud services within Mesh were built using Centrifuge, they required fewer lines of code and did not need to introduce their own subtle protocols for distributed consistency. As cloud services become ever more complicated, this kind of reduction in complexity is an increasingly urgent need.