Nov 4 – 8, 2019
Adelaide Convention Centre
Australia/Adelaide timezone

Managing the ATLAS Grid through Harvester

Nov 5, 2019, 11:45 AM
Riverbank R3 (Adelaide Convention Centre)

Riverbank R3

Adelaide Convention Centre

Oral Track 3 – Middleware and Distributed Computing Track 3 – Middleware and Distributed Computing


Fernando Harald Barreiro Megino (University of Texas at Arlington)


ATLAS Computing Management has identified the migration of all resources to Harvester, PanDA’s new workload submission engine, as a critical milestone for Run 3 and 4. This contribution will focus on the Grid migration to Harvester.
We have built a redundant architecture based on CERN IT’s common offerings (e.g. Openstack Virtual Machines and Database on Demand) to run the necessary Harvester and HTCondor services, capable of sustaining the load of O(1M) workers on the grid per day.
We have reviewed the ATLAS Grid region by region and moved as much possible away from blind worker submission, where multiple queues (e.g. single core, multi core, high memory) compete for resources on a site. Instead we have migrated towards more intelligent models that use information and priorities from the central PanDA workload management system and stream the right number of workers of each category to a unified queue while keeping late binding to the jobs.
We will also describe our enhanced monitoring and analytics framework. Worker and job information is synchronized with minimal delays to a CERN IT provided Elastic Search repository, where we can interact with dashboards to follow submission progress, discover site issues (e.g. broken Compute Elements) or spot empty workers.
The result is a much more efficient usage of the Grid resources with smart, built-in monitoring of resources.

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Primary authors

Fernando Harald Barreiro Megino (University of Texas at Arlington) Aleksandr Alekseev (National Research Tomsk Polytechnic University (RU)) Frank Berghaus (University of Victoria (CA)) David Cameron (University of Oslo (NO)) Andrej Filipcic (Jozef Stefan Institute (SI)) Ivan Glushkov (University of Texas at Arlington (US)) Fa-Hui Lin (Academia Sinica (TW)) Tadashi Maeno (Brookhaven National Laboratory (US)) Nicolo Magini (Iowa State University (US))

Presentation materials