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Automated CI/CD testing, installation and deployment of Dataverse infrastructure on a Cloud

Authors: Slava Tykhonov;

Automated CI/CD testing, installation and deployment of Dataverse infrastructure on a Cloud

Abstract

Dataverse Community Meeting 2021, Harvard University, 14 June 2021. Over the last several years, the Dataverse Project has increased in maturity and has moved forward with CI/CD as a pipeline concept. In addition to the traditional topics around DevOps, Installation Deployments with Vagrant, Ansible, Jenkins, and Automated Testing, attendees will discuss how the Dataverse Community currently uses Cloud technologies such as Docker and Kubernetes to help with the development process and running Dataverse in both production and non-production environments. Serverless computing has also increased in importance recently, to allow for the deployment of shared services as a part of the common data infrastructure. You will learn more about the Cloud related features available in the pyDataverse module, which is widely used by the Dataverse Community for various tasks. We are going to show some practical use cases with the Selenium framework used for automation testing for Jenkins integration. You will also learn about the Software Quality as a Service (SQAaaS) framework that was developed in EOSC Synergy project in the context of the European Open Science Cloud, which covers the following topics: Promoting adoption of software best practices Automatically validating software and services quality of both: thematic services and generic services Promoting the adoption of FAIR data principles Leveraging actionable features on data repositories to analyse and validate FAIR compliance The further automation of all processes allows the community to increase the Dataverse Software ecosystem capabilities and build maintainable and sustainable services integrated with the data repository. Recording is available online.

Keywords

ci/cd, continuous integration, dataverse, testing, cloud infrastructure

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
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