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

Summary


The vSAN performance and health service helps with updated health checks for known issues and provides visibility to the end user. It will not help users collect the logs from a customer's site and send them in for support so that the development team will get the incident after the end user has logged a support ticket with issues. Instead, it helps with data that assists the engineering team in enhancing VMware products and related services, resolving issues, and recommend best practices to follow while implementing VMware solutions.

In the next chapter, Chapter 3Security with Workspace One Intelligence, we will learn about how customers are becoming increasingly pressured to provide more intelligent insights about their organizations and user behavior to deliver the best IT service possible. Having different tools and systems that house this insightful data across mobile device management (MDM), PC, and other third-party systems causes fragmentation of this data and inconsistency...