An architecture for model-based and intelligent automation in DevOps

The increasing complexity of modern systems poses numerous challenges at all stages of system development and operation. Continuous software and system engineering processes, e.g., DevOps, are increasingly adopted and spread across organizations. In parallel, many leading companies have begun to app...

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Detalhes bibliográficos
Autores: Eramo, Romina, Said, Bilal, Oriol Hilari, Marc|||0000-0003-1928-7024, Brunelière, Hugo, Morales, Sergio
Formato: artículo
Fecha de publicación:2024
País:España
Recursos:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/417177
Acesso em linha:https://hdl.handle.net/2117/417177
https://dx.doi.org/10.1016/j.jss.2024.112180
Access Level:acceso abierto
Palavra-chave:Software architecture
DevOps
Continuous software engineering
Artificial intelligence
Mode-driven engineering
Àrees temàtiques de la UPC::Informàtica::Enginyeria del software
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial
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repository_id_str
spelling An architecture for model-based and intelligent automation in DevOpsEramo, RominaSaid, BilalOriol Hilari, Marc|||0000-0003-1928-7024Brunelière, HugoMorales, SergioSoftware architectureDevOpsContinuous software engineeringArtificial intelligenceMode-driven engineeringÀrees temàtiques de la UPC::Informàtica::Enginyeria del softwareÀrees temàtiques de la UPC::Informàtica::Intel·ligència artificialThe increasing complexity of modern systems poses numerous challenges at all stages of system development and operation. Continuous software and system engineering processes, e.g., DevOps, are increasingly adopted and spread across organizations. In parallel, many leading companies have begun to apply artificial intelligence (AI) principles and techniques, including Machine Learning (ML), to improve their products. However, there is no holistic approach that can support and enhance the growing challenges of DevOps. In this paper, we propose a software architecture that provides the foundations of a model-based framework for the development of AI-augmented solutions incorporating methods and tools for continuous software and system engineering and validation. The key characteristic of the proposed architecture is that it allows leveraging the advantages of both AI/ML and Model Driven Engineering (MDE) approaches and techniques in a DevOps context. This architecture has been designed, developed and applied in the context of the European large collaborative project named AIDOaRt. In this paper, we also report on the practical evaluation of this architecture. This evaluation is based on a significant set of technical solutions implemented and applied in the context of different real industrial case studies coming from the AIDOaRt project. Moreover, we analyze the collected results and discuss them according to both architectural and technical challenges we intend to tackle with the proposed architecture.The work presented in this paper is funded by the ECSEL Joint Undertaking (JU)under grant agreement No. 101007350 (AIDOaRt project). The JU receives support from the European Union’s Horizon 2020 research and innovation programme and Sweden, Austria, Czech Republic, Finland, France, Italy, Spain.Peer Reviewed20242024-11-0120242024-11-07journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/417177https://dx.doi.org/10.1016/j.jss.2024.112180reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/4171772026-05-27T15:37:01Z
dc.title.none.fl_str_mv An architecture for model-based and intelligent automation in DevOps
title An architecture for model-based and intelligent automation in DevOps
spellingShingle An architecture for model-based and intelligent automation in DevOps
Eramo, Romina
Software architecture
DevOps
Continuous software engineering
Artificial intelligence
Mode-driven engineering
Àrees temàtiques de la UPC::Informàtica::Enginyeria del software
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial
title_short An architecture for model-based and intelligent automation in DevOps
title_full An architecture for model-based and intelligent automation in DevOps
title_fullStr An architecture for model-based and intelligent automation in DevOps
title_full_unstemmed An architecture for model-based and intelligent automation in DevOps
title_sort An architecture for model-based and intelligent automation in DevOps
dc.creator.none.fl_str_mv Eramo, Romina
Said, Bilal
Oriol Hilari, Marc|||0000-0003-1928-7024
Brunelière, Hugo
Morales, Sergio
author Eramo, Romina
author_facet Eramo, Romina
Said, Bilal
Oriol Hilari, Marc|||0000-0003-1928-7024
Brunelière, Hugo
Morales, Sergio
author_role author
author2 Said, Bilal
Oriol Hilari, Marc|||0000-0003-1928-7024
Brunelière, Hugo
Morales, Sergio
author2_role author
author
author
author
dc.subject.none.fl_str_mv Software architecture
DevOps
Continuous software engineering
Artificial intelligence
Mode-driven engineering
Àrees temàtiques de la UPC::Informàtica::Enginyeria del software
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial
topic Software architecture
DevOps
Continuous software engineering
Artificial intelligence
Mode-driven engineering
Àrees temàtiques de la UPC::Informàtica::Enginyeria del software
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial
description The increasing complexity of modern systems poses numerous challenges at all stages of system development and operation. Continuous software and system engineering processes, e.g., DevOps, are increasingly adopted and spread across organizations. In parallel, many leading companies have begun to apply artificial intelligence (AI) principles and techniques, including Machine Learning (ML), to improve their products. However, there is no holistic approach that can support and enhance the growing challenges of DevOps. In this paper, we propose a software architecture that provides the foundations of a model-based framework for the development of AI-augmented solutions incorporating methods and tools for continuous software and system engineering and validation. The key characteristic of the proposed architecture is that it allows leveraging the advantages of both AI/ML and Model Driven Engineering (MDE) approaches and techniques in a DevOps context. This architecture has been designed, developed and applied in the context of the European large collaborative project named AIDOaRt. In this paper, we also report on the practical evaluation of this architecture. This evaluation is based on a significant set of technical solutions implemented and applied in the context of different real industrial case studies coming from the AIDOaRt project. Moreover, we analyze the collected results and discuss them according to both architectural and technical challenges we intend to tackle with the proposed architecture.
publishDate 2024
dc.date.none.fl_str_mv 2024
2024-11-01
2024
2024-11-07
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/417177
https://dx.doi.org/10.1016/j.jss.2024.112180
url https://hdl.handle.net/2117/417177
https://dx.doi.org/10.1016/j.jss.2024.112180
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.812429

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