- • NGI(s) proposed for contributing and their share of the effort • NGI(s) proposed for contributing and their share of the effort
- • of SLA/SLD if applicable • of SLA/SLD if applicable
- • HUC(s): HEP(WLCG) and others • HUC(s): HEP(WLCG) and others

In order to perform production and analysis tasks across a highly distributed system crossing multiple management domains powerful and flexible monitoring systems are clearly needed. To respond to the LHC experiments’ requirements in this area, the experiment Dashboard monitoring system was originally developed in the context of the EGEE NA4/HEP activity. This framework, not only supports multiple grids / middleware stacks, including glite, OSG and ARC (NDGF), but is also sufficiently generic as to address the needs of multiple other communities including but not limited to HUCs. Furthermore, it covers the full range of the experiments’ computing activities: job monitoring, data transfer (see FTS and VO services above) as well as site commissioning. It also addresses the needs of different categories of users, including:

- • teams of the LHC VOs; • teams of the LHC VOs;
- • and WLCG management; • and WLCG management;
- • administrators and VO support at the sites; • administrators and VO support at the sites;
- • running their computational tasks on the grid infrastructure. • running their computational tasks on the grid infrastructure.

Future Evolution: The future evolution of the project is driven by the requirements of the LHC community which is preparing for LHC data taking at the end of 2009. The main strategy is to concentrate effort on common applications which are shared by multiple LHC VOs but can also be used outside the LHC and HEP scope. Examples of such applications are: generic job monitoring application and user task monitoring, FTS monitoring, site status board, VO-specific site availability based on the results of tests submitted via Site Availability Monitor (SAM). Impact: Reliable monitoring is a necessary condition for establishing and maintaining production quality of the distributed infrastructure. Monitoring of the computing activities of the main communities using this infrastructure in addition provides the best estimation of its reliability and performance. The importance of flexible monitoring tools focusing on the applications has been demonstrated to be essential not only for “power-users” but also for single users. For the power users (such as managers of key activities like large simulation campaigns in HEP or drug searches in BioMed) a very important feature is to be able to monitor the resource behaviour to detect the origin of failures and optimise their system. They also benefit from the possibility to “measure” efficiency and evaluate the quality of service provided by the infrastructure. Single users are typically scientists using the Grid for analysis data, verifying hypotheses on data sets they could not have available on other computing platforms. In this case the monitoring / dashboard is a guide to understand the progress of their activity, identify and solve problems connected to their application. This is essential to allow efficient user support by “empowering the users” in such a way that only non-trivial issues are escalated to support teams (for example, jobs on hold due to scheduled site maintenance can be identified as such and the user can decide to wait or to resubmit). Effort: 4 FTEs, 50% co-funded through CERN / WLCG. Ganga is an easy-to-use frontend for job definition and management, implemented in Python. It has been developed to meet the needs of the ATLAS and LHCb for a Grid user interface, and includes built-in support for configuring and running applications based on the Gaudi / Athena framework

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