Monitoring of large-scale federated data storage: XRootD and beyond

The computing models of the LHC experiments are gradually moving from hierarchical data models with centrally managed data pre-placement towards federated storage which provides seamless access to data files independently of their location and dramatically improve recovery due to fail-over mechanisms. Construction of the data federations and understanding the impact of the new approach to data management on user analysis requires complete and detailed monitoring. Monitoring functionality should cover the status of all components of the federated storage, measuring data traffic and data access performance, as well as being able to detect any kind of inefficiencies and to provide hints for resource optimization and effective data distribution policy. Data mining of the collected monitoring data provides a deep insight into new usage patterns. In the WLCG context, there are several federations currently based on the XRootD technology. This paper will focus on monitoring for the ATLAS and CMS XRootD federations implemented in the Experiment Dashboard monitoring framework. Both federations consist of many dozens of sites accessed by many hundreds of clients and they continue to grow in size. Handling of the monitoring flow generated by these systems has to be well optimized in order to achieve the required performance. Furthermore, this paper demonstrates the XRootD monitoring architecture is sufficiently generic to be easily adapted for other technologies, such as HTTP/WebDAV dynamic federations.