Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research
Adaptation and Deployment of PanDA Task Management System for a Private Cloud Infrastructure. / Iakushkin, Oleg; Malevanniy, Daniil; Bogdanov, Alexander; Sedova, Olga.
Computational Science and Its Applications – ICCSA 2017: 17th International Conference, Trieste, Italy, July 3-6, 2017, Proceedings, Part V. Springer Nature, 2017. p. 438-447 (Lecture Notes in Computer Science; Vol. 10408).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research
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TY - GEN
T1 - Adaptation and Deployment of PanDA Task Management System for a Private Cloud Infrastructure
AU - Iakushkin, Oleg
AU - Malevanniy, Daniil
AU - Bogdanov, Alexander
AU - Sedova, Olga
N1 - Conference code: 17
PY - 2017
Y1 - 2017
N2 - Management of computational infrastructure is a complicated task which, often employs user workloads delivery across multiple clusters. Criteria for such tasks distribution may vary: priority, transport costs, utilization of data, node capabilities, etc.Such process happens to tasks devoted to the simulation and analysis of the results of high-energy physics experiments at CERN. For task distribution on massive data streams obtained during ATLAS experiment, “Production ANd Distributed Analysis system” (PanDA) was developed. It performs management of workloads delivery and execution in a geographically distributed cluster environment. This paper is devoted to the deployment of PanDA server in a private cluster setting.This paper presents architecture and its implementation that allows, to run and embed PanDA system into existing computational solutions. It consists of a container, that isolates PanDA server its dependencies and environment from other system processes and an embedded Web interface which simplifies task management for end-users. In other words, our approach is focused on PanDA system deployment speed up by means of security layer simplification, containerization and stateless client web service implementation. System was tested on a heterogeneous geographically distributed Azure cloud nodes.
AB - Management of computational infrastructure is a complicated task which, often employs user workloads delivery across multiple clusters. Criteria for such tasks distribution may vary: priority, transport costs, utilization of data, node capabilities, etc.Such process happens to tasks devoted to the simulation and analysis of the results of high-energy physics experiments at CERN. For task distribution on massive data streams obtained during ATLAS experiment, “Production ANd Distributed Analysis system” (PanDA) was developed. It performs management of workloads delivery and execution in a geographically distributed cluster environment. This paper is devoted to the deployment of PanDA server in a private cluster setting.This paper presents architecture and its implementation that allows, to run and embed PanDA system into existing computational solutions. It consists of a container, that isolates PanDA server its dependencies and environment from other system processes and an embedded Web interface which simplifies task management for end-users. In other words, our approach is focused on PanDA system deployment speed up by means of security layer simplification, containerization and stateless client web service implementation. System was tested on a heterogeneous geographically distributed Azure cloud nodes.
KW - Grid computing User interface API Virtualization Deploying
M3 - Conference contribution
SN - 978-3-319-62403-7
T3 - Lecture Notes in Computer Science
SP - 438
EP - 447
BT - Computational Science and Its Applications – ICCSA 2017
PB - Springer Nature
T2 - 17th International Conference on Computational Science and Its Applications, ICCSA 2017
Y2 - 2 July 2017 through 5 July 2017
ER -
ID: 71327259