  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
