Software Defined Networking (SDN) is an active area for network research, with many organizations exploring the opportunities provided by the decoupling of network control from packet forwarding. However, questions remain over the operation of such systems in production. In order to build operational confidence, we built Cardigan -a distributed router using OpenFlowand deployed it at a public Internet exchange. Cardigan applies a routing as a service abstraction to a RouteFlow controlled IP network in an effort to reduce operational complexity. The implementation and deployment efforts provide insights into the challenges involved with using these technologies, and suggests the viability of mixed device environments despite the limitations of early OpenFlow implementations.

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Hybrid Software-Defined Networking (SDN) systems are an active area for network research, with many organisations exploring the opportunities unlocked by the de-coupling of network control from packet forwarding. Previous work has suggested that a hybrid networking model will pave the way for migration towards SDN, through interoperability with legacy devices. However, questions remain over the operation of such systems in production environments. In order to explore the challenges of hybrid SDN systems and build operational confidence, we built a simple distributed router using OpenFlow and deployed it at a public Internet exchange. This implementation provides insights into the challenges involved with using these technologies, and suggests the viability of mixed device environments despite the limitations of early OpenFlow implementations.

End-to-end latency is becoming an important metric for many emerging applications (e.g., 5G low-latency services) over the Internet. To better understand end-to-end latency, we present Ruru 1 , a DPDK-based pipeline that exploits recent advances in high-speed packet processing and visualization. We present an operational deployment of Ruru over an international high-speed link running between Auckland and Los Angeles, and show how Ruru can be used for latency anomaly detection and network planning.

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