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Padolski, Siarhei

Publications and source records attributed to Padolski, Siarhei.

An intelligent Data Delivery Service for and beyond the ATLAS experiment

The intelligent Data Delivery Service (iDDS) has been developed to cope with the huge increase of computing and storage resource usage in the coming LHC data taking. iDDS has been designed to intelligently orchestrate workflow and data management systems, decoupling data pre-processing, delivery, and main processing in various workflows. It is an experiment-agnostic service around a workflow-oriented structure to work with existing and emerging use cases in ATLAS and other experiments. Here we will present the motivation for iDDS, its design schema and architecture, use cases and current status, and plans for the future.

97 MATHEMATICS AND COMPUTING↗

Distributed data management on Belle II

The Belle II experiment started taking physics data in April 2018 with an estimated total volume of all files including raw events, Monte-Carlo and skim statistics of 340 petabytes expected by the end of operations in the late-2020s. Originally designed as a fully integrated component of the BelleDIRAC production system, the Belle II distributed data management (DDM) software needs to manage data across about 29 storage elements worldwide for a collaboration of nearly 1000 physicists. By late 2018, this software required significant performance improvements to meet the requirements of physics data taking and was seriously lacking in automation. Rucio, the DDM solution created by ATLAS, was an obvious alternative but required tight integration with BelleDIRAC and a seamless yet non-trivial migration. This contribution describes the work done on both DDM options, the current status of the software running successfully in production and the problems associated with trying to balance long-term operations cost against short term risk. .

97 MATHEMATICS AND COMPUTING↗

ATLAS BigPanDA monitoring

BigPanDA monitoring is a web application that provides various processing and representation of the Production and Distributed Analysis (PanDA) system objects states. Analysing hundreds of millions of computation entities, such as an event or a job, BigPanDA monitoring builds different scales and levels of abstraction reports in real time mode. Provided information allows users to drill down into the reason of a concrete event failure or observe the broad picture such as tracking the computation nucleus and satellites performance or the progress of a whole production campaign. PanDA system was originally developed for the ATLAS experiment. Currently, it manages execution of more than 2 million jobs distributed over 170 computing centers worldwide on daily basis. BigPanDA is its core component commissioned in the middle of 2014 and now is the primary source of information for ATLAS users about the state of their computations and the source of decision support information for shifters, operators and managers. In this work, we describe the evolution of the architecture, current status and plans for the development of the BigPanDA monitoring.

47 OTHER INSTRUMENTATION↗