Scientific innovation produced by Virtual Organizations (VOs) such as the LHC, demands high capacity and highly available network technologies to link remote data creation, storage, and processing facilities. Research and Education (R&E) networks are a vital cog in this supply chain, and offer advanced capabilities to this distributed scientific project. Network operations staff spend countless hours monitoring and assuring internal performance and traffic management needs, all to benefit local user communities. Often the "big picture" of end-to-end performance is forgotten, or cast aside, due to the relative complexity of multi-domain operational scenarios and the lack of human and technological resources.
Software deigned to monitor and share network information between domains, developed by the perfSONAR-PS project, is available to help with end-to-end performance concerns. This framework, in use within the USATLAS project since 2007, and emerging on other collaborations including the Italian and Canadian ATLAS clouds, has been beneficial in identifying complex network faults while imposing minimal operational overhead on local administrators.