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Bockelman, B. P.

Publications and source records attributed to Bockelman, B. P..

Effective HTCondor-based monitoring system for CMS

The CMS experiment at the LHC relies on HTCondor and glideinWMS as its primary batch and pilot-based Grid provisioning systems, respectively. Given the scale of the global queue in CMS, the operators found it increasingly difficult to monitor the pool to find problems and fix them. The operators had to rely on several different web pages, with several different levels of information, and sift tirelessly through log files in order to monitor the pool completely. Therefore, coming up with a suitable monitoring system was one of the crucial items before the beginning of the LHC Run 2 in order to ensure early detection of issues and to give a good overview of the whole pool. Our new monitoring page utilizes the HTCondor ClassAd information to provide a complete picture of the whole submission infrastructure in CMS. The monitoring page includes useful information from HTCondor schedulers, central managers, the glideinWMS frontend, and factories. It also incorporates information about users and tasks making it easy for operators to provide support and debug issues.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

CMS distributed data analysis with CRAB3

The CMS Remote Analysis Builder (CRAB) is a distributed workflow management tool which facilitates analysis tasks by isolating users from the technical details of the Grid infrastructure. Throughout LHC Run 1, CRAB has been successfully employed by an average of 350 distinct users each week executing about 200,000 jobs per day.CRAB has been significantly upgraded in order to face the new challenges posed by LHC Run 2. Components of the new system include 1) a lightweight client, 2) a central primary server which communicates with the clients through a REST interface, 3) secondary servers which manage user analysis tasks and submit jobs to the CMS resource provisioning system, and 4) a central service to asynchronously move user data from temporary storage in the execution site to the desired storage location. Furthermore, the new system improves the robustness, scalability and sustainability of the service.Here we provide an overview of the new system, operation, and user support, report on its current status, and identify lessons learned from the commissioning phase and production roll-out.

97 MATHEMATICS AND COMPUTING↗