Clustering, Resource Management, and Replication Support for Scalable Network Services Kai Shen Department of Computer Science University of California at Santa Barbara With the increasing demand of providing highly scalable, available and easy-to-manage services, the deployment of large-scale complex server clusters has been rapidly emerging in which service components are usually partitioned, replicated, and aggregated. This dissertation investigates techniques in building a middleware system, called Neptune, that provides clustering support for scalable network services. In particular, Neptune addresses three specific aspects in support of network service clustering: 1) the development of a flexible and scalable clustering architecture with efficient load balancing support for fine-grain services; 2) the design and implementation of an integrated resource management framework that combines the "response time"- aware service quality, overall resource utilization efficiency, and service differentiation support; and 3) the design and implementation of a service replication framework focusing on providing flexible replica consistency, performance scalability, and failure recovery support. Neptune has been implemented on Linux and Solaris clusters and a number of applications have been successfully deployed on Neptune platforms, including a large-scale document search engine.