Use of Docker for deployment and testing of astronomy software

We describe preliminary investigations of using Docker for the deployment and testing of astronomy software. Docker is a relatively new containerisation technology that is developing rapidly and being adopted across a range of domains. It is based upon virtualization at operating system level, which presents many advantages in comparison to the more traditional hardware virtualization that underpins most cloud computing infrastructure today. A particular strength of Docker is its simple format for describing and managing software containers, which has benefits for software developers, system administrators and end users. We report on our experiences from two projects -- a simple activity to demonstrate how Docker works, and a more elaborate set of services that demonstrates more of its capabilities and what they can achieve within an astronomical context -- and include an account of how we solved problems through interaction with Docker's very active open source development community, which is currently the key to the most effective use of this rapidly-changing technology.Comment: 29 pages, 9 figures, accepted for publication in Astronomy and Computing, ref ASCOM19

Evaluation of containers as a virtualisation alternative for HEP workloads

In this paper the emerging technology of Linux containers is examined and evaluated for use in the High Energy Physics (HEP) community. Key technologies required to enable containerisation will be discussed along with emerging technologies used to manage container images. An evaluation of the requirements for containers within HEP will be made and benchmarking will be carried out to asses performance over a range of HEP workflows. The use of containers will be placed in a broader context and recommendations on future work will be given

DALiuGE: A Graph Execution Framework for Harnessing the Astronomical Data Deluge

The Data Activated Liu Graph Engine - DALiuGE - is an execution framework for processing large astronomical datasets at a scale required by the Square Kilometre Array Phase 1 (SKA1). It includes an interface for expressing complex data reduction pipelines consisting of both data sets and algorithmic components and an implementation run-time to execute such pipelines on distributed resources. By mapping the logical view of a pipeline to its physical realisation, DALiuGE separates the concerns of multiple stakeholders, allowing them to collectively optimise large-scale data processing solutions in a coherent manner. The execution in DALiuGE is data-activated, where each individual data item autonomously triggers the processing on itself. Such decentralisation also makes the execution framework very scalable and flexible, supporting pipeline sizes ranging from less than ten tasks running on a laptop to tens of millions of concurrent tasks on the second fastest supercomputer in the world. DALiuGE has been used in production for reducing interferometry data sets from the Karl E. Jansky Very Large Array and the Mingantu Ultrawide Spectral Radioheliograph; and is being developed as the execution framework prototype for the Science Data Processor (SDP) consortium of the Square Kilometre Array (SKA) telescope. This paper presents a technical overview of DALiuGE and discusses case studies from the CHILES and MUSER projects that use DALiuGE to execute production pipelines. In a companion paper, we provide in-depth analysis of DALiuGE's scalability to very large numbers of tasks on two supercomputing facilities.Comment: 31 pages, 12 figures, currently under review by Astronomy and Computin

NEOExchange -- An online portal for NEO and Solar System science

Las Cumbres Observatory (LCO) has deployed a network of ten identical 1-m telescopes to four locations. The global coverage and flexibility of the LCO network makes it ideal for discovery, follow-up, and characterization of all Solar System objects, and especially Near-Earth Objects (NEOs). We describe the "LCO NEO Follow-up Network" which makes use of the LCO network of robotic telescopes and an online, cloud-based web portal, NEOexchange, to perform photometric characterization and spectroscopic classification of NEOs and follow-up astrometry for both confirmed NEOs and unconfirmed NEO candidates. The follow-up astrometric, photometric, and spectroscopic characterization efforts are focused on those NEO targets that are due to be observed by the planetary radar facilities and those on the NHATS lists. Astrometry allows us to improve target orbits, making radar observations possible for objects with a short arc or large orbital uncertainty and also allows for the detection and measurement of the Yarkovsky effect on NEOs. Photometric & spectroscopic data allows us to determine the light curve shape and amplitude, measure rotation periods, determine the taxonomic classification, and improve the overall characterization of these targets. We describe the NEOexchange follow-up portal and the methodology adopted which allows the software to be packaged and deployed anywhere, including in off-site cloud services. This allows professionals, amateurs, and citizen scientists to plan, schedule and analyze NEO imaging and spectroscopy data using the LCO network and acts as a coordination hub for the NEO follow-up efforts. We illustrate these capabilities with examples of first period determinations for radar-targeted NEOs and its use to plan and execute multi-site photometric and spectroscopic observations of (66391) 1999 KW4, the subject of the most recent planetary defense exercise campaign.Comment: 35 pages, 6 figures, accepted by Icarus. Available on the web at https://lco.global/neoexchange/ code available from GitHub at https://github.com/LCOGT/neoexchange

INDIGO-DataCloud: a Platform to Facilitate Seamless Access to E-Infrastructures

[EN] This paper describes the achievements of the H2020 project INDIGO-DataCloud. The project has provided e-infrastructures with tools, applications and cloud framework enhancements to manage the demanding requirements of scientific communities, either locally or through enhanced interfaces. The middleware developed allows to federate hybrid resources, to easily write, port and run scientific applications to the cloud. In particular, we have extended existing PaaS (Platform as a Service) solutions, allowing public and private e-infrastructures, including those provided by EGI, EUDAT, and Helix Nebula, to integrate their existing services and make them available through AAI services compliant with GEANT interfederation policies, thus guaranteeing transparency and trust in the provisioning of such services. Our middleware facilitates the execution of applications using containers on Cloud and Grid based infrastructures, as well as on HPC clusters. 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