Scalable near real-time failure localization of data center networks
Herodotos Herodotou, Bolin Ding, Shobana Balakrishnan, Geoff Outhred, Percy Fitter · 2014
Large-scale data center networks are complex---comprising several thousand network devices and several hundred thousand links---and form the critical infrastructure upon which all higher-level services depend on. Despite the built-in redundancy in data center networks, performance issues and device or link failures in the network can lead to user-perceived service interruptions. Therefore, determining and localizing user-impacting availability and performance issues in the network in near real time is crucial. Traditionally, both passive and active monitoring approaches have been used for failure localization. However, data from passive monitoring is often too noisy and does not effectively capture silent or gray failures, whereas active monitoring is potent in detecting faults but limited in its ability to isolate the exact fault location depending on its scale and granularity.