abstract

PIACERE project: description and prototype for optimizing infrastructure as code deployment configurations

Authors:

Eneko Osaba,

Josu Diaz-de-Arcaya,

Leire Orue-Echevarria,

Juncal Alonso,

Jesus L. Lobo,

Gorka Benguria,

Iñaki EtxanizAuthors Info & Claims

GECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference Companion

Pages 71 - 72

https://doi.org/10.1145/3520304.3533938

Published: 19 July 2022 Publication History

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Abstract

PIACERE is an European project supported by the Union's Horizon 2020 research and innovation programme, whose objective is to enhance the productivity of DevOps teams in the operation of Infrastructure as Code (IaC) by offering an integrated DevSec-Ops framework. Thus, DevOps practitioners can develop IaC as if they were programming a common software application. In order to achieve this challenging task, one of the core technologies considered within PIACERE will be the design and development of optimization metaheuristics, in a module coined as IaC Optimizer Platform (IOP). The main objective of the IOP is to provide DevSecOps teams with the most appropriate deployment configurations that best fit a set of defined constraints. The goal of this technical paper is to describe the preliminary approach followed in PIACERE for carrying out this optimization, and how the IOP fits into the whole PIACERE ecosystem. Additionally, results obtained in a preliminary experimentation are detailed in this study.

References

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Juncal Alonso, Leire Orue-Echevarria, Eneko Osaba, Jesús López Lobo, Iñigo Martinez, Josu Diaz de Arcaya, and Iñaki Etxaniz. 2021. Optimization and Prediction Techniques for Self-Healing and Self-Learning Applications in a Trustworthy Cloud Continuum. Information 12, 8 (2021), 308.

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Cited By

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Casalicchio ECotumaccio A(2024)AI-CRAS: AI-driven Cloud Service Requirement Analysis and Specification2024 IEEE International Conference on Cloud Engineering (IC2E)10.1109/IC2E61754.2024.00009(11-21)Online publication date: 24-Sep-2024
https://doi.org/10.1109/IC2E61754.2024.00009
Osaba EDiaz-De-Arcaya JAlonso JLobo JBenguria GEtxaniz I(2023)Multiobjective Optimization Analysis for Finding Infrastructure-as-Code Deployment ConfigurationsProceedings of the 2023 11th International Conference on Computer and Communications Management10.1145/3617733.3617777(26-31)Online publication date: 4-Aug-2023
https://dl.acm.org/doi/10.1145/3617733.3617777
Osaba EDiaz-de-Arcaya JAlonso JLobo JBenguria GEtxaniz I(2023)An Evolutionary Computation-Based Platform for Optimizing Infrastructure-as-Code Deployment ConfigurationsProceedings of Eighth International Congress on Information and Communication Technology10.1007/978-981-99-3043-2_25(321-330)Online publication date: 1-Sep-2023
https://doi.org/10.1007/978-981-99-3043-2_25

Index Terms

PIACERE project: description and prototype for optimizing infrastructure as code deployment configurations
1. Computing methodologies
  1. Artificial intelligence
    1. Search methodologies
2. Mathematics of computing
  1. Discrete mathematics
    1. Combinatorics
      1. Combinatorial optimization

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Information

Published In

GECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference Companion

July 2022

2395 pages

ISBN:9781450392686

DOI:10.1145/3520304

Editor:
Jonathan E. Fieldsend
University of Exeter
,
General Chair:
Markus Wagner
The University of Adelaide

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 July 2022

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Horizon 2020 Framework Programme

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GECCO '22

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SIGEVO

GECCO '22: Genetic and Evolutionary Computation Conference

July 9 - 13, 2022

Massachusetts, Boston

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Casalicchio ECotumaccio A(2024)AI-CRAS: AI-driven Cloud Service Requirement Analysis and Specification2024 IEEE International Conference on Cloud Engineering (IC2E)10.1109/IC2E61754.2024.00009(11-21)Online publication date: 24-Sep-2024
https://doi.org/10.1109/IC2E61754.2024.00009
Osaba EDiaz-De-Arcaya JAlonso JLobo JBenguria GEtxaniz I(2023)Multiobjective Optimization Analysis for Finding Infrastructure-as-Code Deployment ConfigurationsProceedings of the 2023 11th International Conference on Computer and Communications Management10.1145/3617733.3617777(26-31)Online publication date: 4-Aug-2023
https://dl.acm.org/doi/10.1145/3617733.3617777
Osaba EDiaz-de-Arcaya JAlonso JLobo JBenguria GEtxaniz I(2023)An Evolutionary Computation-Based Platform for Optimizing Infrastructure-as-Code Deployment ConfigurationsProceedings of Eighth International Congress on Information and Communication Technology10.1007/978-981-99-3043-2_25(321-330)Online publication date: 1-Sep-2023
https://doi.org/10.1007/978-981-99-3043-2_25

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