Machine learning for cloud resources management -- An overview

TL;DR

This paper reviews how machine learning techniques are applied to cloud resource management, analyzing their effectiveness, available data, challenges, and proposing suitable models for different management tasks.

Contribution

It provides a comprehensive overview of ML applications in cloud resource management, including comparisons and recommendations for suitable models in various fields.

Findings

ML techniques show promising results in cloud resource management

Different ML models are suitable for specific management tasks

Open challenges include data availability and model selection

Abstract

Nowadays, an important topic that is considered a lot is how to integrate Machine Learning(ML) to cloud resources management. In this study, our goal is to explore the most important cloud resources management issues that have been combined with ML and which present many promising results. To accomplish this, we used chronological charts based on some keywords that we considered important and tried to answer the question: is ML suitable for resources management problems in the cloud? Furthermore, a short discussion takes place on the data that are available and the open challenges on it. A big collection of researches is used to make sensible comparisons between the ML techniques that are used in the different kinds of cloud resources management fields and we propose the most suitable ML model for each field. 1