Abstract
The PanDA (Production and Distributed Analysis) system has been developed to meet ATLAS production and analysis requirements for a data-driven workload management system capable of operating at LHC data processing scale. PanDA has performed well with high reliability and robustness during the two years of LHC data-taking, while being actively evolved to meet the rapidly changing requirements for analysis use cases. We will present an overview of system evolution including automatic rebrokerage and reattempt for analysis jobs, adaptation for the CernVM File System, support for the multi-cloud model through which Tier-2 sites act as members of multiple clouds, pledged resource management and preferential brokerage, and monitoring improvements. We will also describe results from the analysis of two years of PanDA usage statistics, current issues, and plans for the future.
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