Book Image

Intelligent Automation with VMware

By : Ajit Pratap Kundan
Book Image

Intelligent Automation with VMware

By: Ajit Pratap Kundan

Overview of this book

This book presents an introductory perspective on how machine learning plays an important role in a VMware environment. It offers a basic understanding of how to leverage machine learning primitives, along with a deeper look into integration with the VMware tools used for automation today. This book begins by highlighting how VMware addresses business issues related to its workforce, customers, and partners with emerging technologies such as machine learning to create new, intelligence-driven, end user experiences. You will learn how to apply machine learning techniques incorporated in VMware solutions for data center operations. You will go through management toolsets with a focus on machine learning techniques. At the end of the book, you will learn how the new vSphere Scale-Out edition can be used to ensure that HPC, big data performance, and other requirements can be met (either through development or by fine-tuning guidelines) with mainstream products.
Table of Contents (20 chapters)
Title Page
About Packt
Contributors
Preface
Index

Virtual data centers


There will be four virtual data centers per vCenter Server that relate to the various networking zones. The virtual data center construct is an administrative boundary, but it is not necessary to create multiple instances whereby there isn't a requirement to completely segregate the various vCenter constructs from a privileges perspective. Four virtual data centers are used solely for the purpose of placing the vSphere Distributed Switches (VDS). ESXi hosts and networks would need to be recreated in a new single virtual data center. This activity should only be undertaken with extensive research and planning.

The following are the configuration recommendations for virtual resources:

  • VM density per host: The operation team ensures that they run all required VMs on different clusters and that the RAM will not be overcommitted. It can also decide to use up to 90% available RAM capacity of each host. They use the concept of resource units while scaling their VMs, and each...