Use self-driven data centers to reduce management complexity by deploying Infrastructure as Code to gain value from investments.
Key Features
Add smart capabilities in VMware Workspace ONE to deliver customer insights and improve overall security
Optimize your HPC and big data infrastructure with the help of machine learning
Automate your VMware data center operations with machine learning
Book DescriptionThis 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.
What you will learn
Orchestrate on-demand deployments based on defined policies
Automate away common problems and make life easier by reducing errors
Deliver services to end users rather than to virtual machines
Reduce rework in a multi-layered scalable manner in any cloud
Explore the centralized life cycle management of hybrid clouds
Use common code so you can run it across any cloud
Who this book is forThis book is intended for those planning, designing, and implementing the virtualization/cloud components of the Software-Defined Data Center foundational infrastructure. It helps users to put intelligence in their automation tasks to get self driving data center. It is assumed that the reader has knowledge of, and some familiarity with, virtualization concepts and related topics, including storage, security, and networking.
Key Features
Add smart capabilities in VMware Workspace ONE to deliver customer insights and improve overall security
Optimize your HPC and big data infrastructure with the help of machine learning
Automate your VMware data center operations with machine learning
Book DescriptionThis 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.
What you will learn
Orchestrate on-demand deployments based on defined policies
Automate away common problems and make life easier by reducing errors
Deliver services to end users rather than to virtual machines
Reduce rework in a multi-layered scalable manner in any cloud
Explore the centralized life cycle management of hybrid clouds
Use common code so you can run it across any cloud
Who this book is forThis book is intended for those planning, designing, and implementing the virtualization/cloud components of the Software-Defined Data Center foundational infrastructure. It helps users to put intelligence in their automation tasks to get self driving data center. It is assumed that the reader has knowledge of, and some familiarity with, virtualization concepts and related topics, including storage, security, and networking.
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