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@InProceedings{woods:icalepcs2019-mopha160,
author = {K. Woods and F. Barnsely and R.J. Clegg and N.S. Cook and C. Jones and R. Millward},
title = {{Enabling Data Analytics as a Service for Large Scale Facilities}},
booktitle = {Proc. ICALEPCS'19},
pages = {614--616},
paper = {MOPHA160},
language = {english},
keywords = {simulation, data-analysis, distributed, software, experiment},
venue = {New York, NY, USA},
series = {International Conference on Accelerator and Large Experimental Physics Control Systems},
number = {17},
publisher = {JACoW Publishing, Geneva, Switzerland},
month = {08},
year = {2020},
issn = {2226-0358},
isbn = {978-3-95450-209-7},
doi = {10.18429/JACoW-ICALEPCS2019-MOPHA160},
url = {https://jacow.org/icalepcs2019/papers/mopha160.pdf},
note = {https://doi.org/10.18429/JACoW-ICALEPCS2019-MOPHA160},
abstract = {The Ada Lovelace Centre (ALC) at STFC is an integrated, cross-disciplinary data intensive science centre, for better exploitation of research carried out at large scale UK Facilities including the Diamond Light Source, the ISIS Neutron and Muon Facility, the Central Laser Facility and the Culham Centre for Fusion Energy. ALC will provide on-demand, data analysis, interpretation and analytics services to worldwide users of these research facilities. Using open-source components, ALC and Tessella have together created a software infrastructure to support the delivery of that vision. The infrastructure comprises a Virtual Machine Manager, for managing pools of VMs across distributed compute clusters; components for automated provisioning of data analytics environments across heterogeneous clouds; a Data Movement System, to efficiently transfer large datasets; a Kubernetes cluster to manage on demand submission of Spark jobs. In this paper, we discuss the challenges of creating an infrastructure to meet the differing analytics needs of multiple facilities and report the architecture and design of the infrastructure that enables Data Analytics as a Service.},
}