An Evolutionary Computation-Based Platform for Optimizing Infrastructure-as-Code Deployment Configurations

Eneko Osaba; Josu Diaz-de-Arcaya; Juncal Alonso; Jesus L. Lobo; Gorka Benguria; Iñaki Etxaniz

doi:10.1007/978-981-99-3043-2_25

An Evolutionary Computation-Based Platform for Optimizing Infrastructure-as-Code Deployment Configurations

Eneko Osaba, Josu Diaz-de-Arcaya, Juncal Alonso, Jesus L. Lobo, Gorka Benguria, Iñaki Etxaniz

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

PIACERE is an H2020 European project which objective is to implement a solution involving the development, deployment, and operation of Infrastructure-as-Code of applications running on cloud continuum. This technical paper is focused on describing a specific module of the whole PIACERE ecosystem: the IaC Optimizer Platform. The main objective of this component is to provide the user with optimized Infrastructure-as-Code configurations deployed on the most appropriate infrastructural elements that best meet the predefined requirements. For properly dealing with this problem, the IaC Optimizer Platform is based on Evolutionary Computation metaheuristics. More specifically, it resorts to NSGA-II and NSGA-III algorithms, depending on user needs. Additionally, we not only describe the IaC Optimizer Platform component in this paper, but we also show how it helps the user to find the most adequate Infrastructure-as-Code configurations.

Original language	English
Title of host publication	Proceedings of 8th International Congress on Information and Communication Technology - ICICT 2023
Editors	Xin-She Yang, R. Simon Sherratt, Nilanjan Dey, Amit Joshi
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	321-330
Number of pages	10
ISBN (Print)	9789819930425
DOIs	https://doi.org/10.1007/978-981-99-3043-2_25
Publication status	Published - 2024
Event	8th International Congress on Information and Communication Technology, ICICT 2023 - London, United Kingdom Duration: 20 Feb 2023 → 23 Feb 2023

Publication series

Name	Lecture Notes in Networks and Systems
Volume	695 LNNS
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	8th International Congress on Information and Communication Technology, ICICT 2023
Country/Territory	United Kingdom
City	London
Period	20/02/23 → 23/02/23

Keywords

Cloud computing
Infrastructure-as-Code
Non-dominated sorting genetic algorithm II
Optimization

Access to Document

10.1007/978-981-99-3043-2_25

Cite this

Osaba, E., Diaz-de-Arcaya, J., Alonso, J., Lobo, J. L., Benguria, G., & Etxaniz, I. (2024). An Evolutionary Computation-Based Platform for Optimizing Infrastructure-as-Code Deployment Configurations. In X.-S. Yang, R. S. Sherratt, N. Dey, & A. Joshi (Eds.), Proceedings of 8th International Congress on Information and Communication Technology - ICICT 2023 (pp. 321-330). (Lecture Notes in Networks and Systems; Vol. 695 LNNS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-99-3043-2_25

Osaba, Eneko ; Diaz-de-Arcaya, Josu ; Alonso, Juncal et al. / An Evolutionary Computation-Based Platform for Optimizing Infrastructure-as-Code Deployment Configurations. Proceedings of 8th International Congress on Information and Communication Technology - ICICT 2023. editor / Xin-She Yang ; R. Simon Sherratt ; Nilanjan Dey ; Amit Joshi. Springer Science and Business Media Deutschland GmbH, 2024. pp. 321-330 (Lecture Notes in Networks and Systems).

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abstract = "PIACERE is an H2020 European project which objective is to implement a solution involving the development, deployment, and operation of Infrastructure-as-Code of applications running on cloud continuum. This technical paper is focused on describing a specific module of the whole PIACERE ecosystem: the IaC Optimizer Platform. The main objective of this component is to provide the user with optimized Infrastructure-as-Code configurations deployed on the most appropriate infrastructural elements that best meet the predefined requirements. For properly dealing with this problem, the IaC Optimizer Platform is based on Evolutionary Computation metaheuristics. More specifically, it resorts to NSGA-II and NSGA-III algorithms, depending on user needs. Additionally, we not only describe the IaC Optimizer Platform component in this paper, but we also show how it helps the user to find the most adequate Infrastructure-as-Code configurations.",

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author = "Eneko Osaba and Josu Diaz-de-Arcaya and Juncal Alonso and Lobo, {Jesus L.} and Gorka Benguria and I{\~n}aki Etxaniz",

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Osaba, E , Diaz-de-Arcaya, J , Alonso, J , Lobo, JL , Benguria, G & Etxaniz, I 2024, An Evolutionary Computation-Based Platform for Optimizing Infrastructure-as-Code Deployment Configurations. in X-S Yang, RS Sherratt, N Dey & A Joshi (eds), Proceedings of 8th International Congress on Information and Communication Technology - ICICT 2023. Lecture Notes in Networks and Systems, vol. 695 LNNS, Springer Science and Business Media Deutschland GmbH, pp. 321-330, 8th International Congress on Information and Communication Technology, ICICT 2023, London, United Kingdom, 20/02/23. https://doi.org/10.1007/978-981-99-3043-2_25

An Evolutionary Computation-Based Platform for Optimizing Infrastructure-as-Code Deployment Configurations. / Osaba, Eneko ; Diaz-de-Arcaya, Josu ; Alonso, Juncal et al.
Proceedings of 8th International Congress on Information and Communication Technology - ICICT 2023. ed. / Xin-She Yang; R. Simon Sherratt; Nilanjan Dey; Amit Joshi. Springer Science and Business Media Deutschland GmbH, 2024. p. 321-330 (Lecture Notes in Networks and Systems; Vol. 695 LNNS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Osaba E , Diaz-de-Arcaya J , Alonso J , Lobo JL , Benguria G , Etxaniz I. An Evolutionary Computation-Based Platform for Optimizing Infrastructure-as-Code Deployment Configurations. In Yang XS, Sherratt RS, Dey N, Joshi A, editors, Proceedings of 8th International Congress on Information and Communication Technology - ICICT 2023. Springer Science and Business Media Deutschland GmbH. 2024. p. 321-330. (Lecture Notes in Networks and Systems). doi: 10.1007/978-981-99-3043-2_25