In this paper, we study replication techniques for scaling and continuous operation for a dynamic content server. Our focus is on supporting transparent and fast reconfiguration of its database tier in case of overload or failures. We show that the data persistence aspects can be decoupled from reconfiguration of the database CPU. A lightweight in-memory middleware tier captures the typically heavyweight read-only requests to ensure fle xible database CPU scaling and fail-over. At the same time, updates are handled by an on-disk database back-end that is in charge of making them persistent.

Our measurements show instantaneous, seamless reconfiguration in the case of single node failures within the fle xible in-memory tier for a web site running the most common, shopping, workload mix of the industry-standard ecommerce TPC-W benchmark. At the same time, a 9-node in-memory tier improves performance during normal operation over a stand-alone InnoDB on-disk database backend. Throughput scales by factors of 14.6, 17.6 and 6.5 for the browsing, shopping and ordering mixes of the TPC-W benchmark, respectively.