Evaluation of AI Techniques to Implement Proactive Container Auto-scaling Strategies

Bryan Leonardo Figueredo González, Mariela J. Curiel H

Producción: Capítulo del libro/informe/acta de congresoCapítulo en libro de investigaciónrevisión exhaustiva

Resumen

This paper evaluates techniques for improving the use of cloud computing resources through autoscaling. Autoscaling, also referred to as auto-scaling or automatic scaling, is a cloud computing technique for dynamically allocating computational resources. Autoscaling can be reactive (responding to resource needs as they arise) or proactive (anticipating future demands). Our study proposes the use of AI-based models to predict the creation of new computational entities under varying load conditions. The proposed methodology included data cleaning, correlation analysis to select relevant features, and the evaluation of several supervised and unsupervised machine learning models. The results shown that machine learning techniques can be used to anticipate and optimize the capacity of computing systems.
Idioma originalInglés
Título de la publicación alojadaEvaluation of AI Techniques to Implement Proactive Container Auto-scaling Strategies
Volumen1924
ISBN (versión digital)978-3-031-47372-2
DOI
EstadoPublicada - 14 nov. 2023

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