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

ML and VMware


VMware is extensively leveraging AI and ML techniques in most of its products. We can see this with the new version of vSphere 6.7 features and also with products such as AppDefense and Workspace. This is one intelligence that will help in achieving the future vision of self-driving data centers. VMware has already done the performance benchmarking regarding how it can help its customers to run their own ML workloads on vSphere with improved support from NVIDIA GPUs.

ML is important for VMware mixed cloud vision, as ML has the ability to absorb a huge amount of datato utilize it for precise learning and with end users.

ML-based data analysis

ML is helping customers to fetch better granular-level information from large datasets. This will give a huge competitive advantage in business, as the customer is able to integrate their data from different sources, which will help the management to take major decisions ahead of their competitors. As we get this result with the relevant reasons behind it, we can help customers with accurate and productive data. The potential of AI in our daily life is immense.

We have a new development in ML every day, and ML will be extended even further. All the biggest public cloud vendors use ML-based techniques in their daily operations. Apple, GE, and Bosch are also gathering massive amounts of data and applying machine learning techniques to filter out only useful data. GE is accumulating data analytics through its industrial internet, and Apple has a huge amount of consumer and health data from its millions of end users, which helps them to emerge as major players in AI. 

Embedding AI within present cloud technologies is helping businesses and consumers to grow and also creating new opportunities with all the relevant information to plan for the future. We are moving toward intelligent infrastructure where AI uses machines to adopt human intelligence. AI is based on rules-based logic, decision trees, and methodology to enable it to behave like a human. ML analyzes data and enhances the performance of repetitive tasks. DL will help machines learn by locating and checking various options against one another in order to get the best result or solution.

Customers have adopted the cloud and are now embedding ML techniques and its capabilities to extend its dynamics and delivering values to customers. Customers get a safe and secure environment with the scale up and out capabilities. The cloud provider receives loyal long-term customers in return. Every cloud provider is better than others in specific fields, from a business and an AI perspective. This will give customers diverse offerings with specialized intelligence for their unique requirements.

VMware will help customers with intelligent infrastructure that can deliver a comparable and secure solution across mixed clouds to choose the right cloud provider for their unique business requirements, such as security, backup, disaster recovery, networking, storage, graphics, and management with basic compute resources. 

A good example of intelligent technology is Google Maps. When we leave our office for a meeting, with Google Map's guidance, we are able to identify alternative routes via AI, saving us valuable time.

Using virtualized GPUs with ML

ML is being extensively used in research and development these days, and the computing power enhancement of accelerators such as GPUs has enabled a rapid adoption of ML applications.

Designers, engineers, and architects are the extensive end users who frequently use 3D graphics for a wide-range of use cases and expect their IT teams to assist them in this. They use high-end graphics workstations handling 3D models of automobiles, manufacturing components, and buildings in real time. They are part of manufacturing, architecture, engineering and construction, higher education, public sector, oil and gas, and so on. They have to view and control this rich, visual 2D and 3D data in real time. Power-user groups such as clinicians, engineers, and office professionals represent millions of users who rely on rich 2D and 3D graphics for their deliverables.

Organizations are evolving today as their footprint increasing with the global workforce who are geographically distributed teams using virtual desktop with graphics from anywhere, anytime and on any workstation. As these power users are working in the field and need application access from anywhere using their end-point devices such as laptops, tablets, and mobile devices, they need to collaborate with their team members in real time without the risk of data loss and with full compliance. We have to redefine the workflow for designers and engineers with a Virtual Desktop Infrastructure (VDI) solution:

 VMware Horizon VDI with NVIDIA GPU

A VMware VDI solution is certified with all leading 3D apps workstations—world-class graphics from endpoint to data center are accessible on any device while lowering the operating expenses. VMware Horizon with protocol Blast ensures a tremendous user experience based on NVIDIA GRID vGPU technology by providing secure, native, 3D graphics from the cloud and delivered across any endpoint devices and from any locations with lower OpEx. Graphics commands executed on each virtual machine are directly passed to the physical GPU without any overheads at the hypervisor layer with NVIDIA GRID vGPU technology.

It helps with application compatibility as the applications have access to the same graphics card as earlier on their workstations. NVIDIA GRID vGPU makes it possible for the GPU hardware to be time-sliced to provide the best in shared virtualized graphics performance.

VMware, vSphere, and VMware Horizon ensure power users, designers, and engineers can get a fabulous graphics experience that is equivalent to native hardware and certified by NVIDIA and VMware for most of the important business applications.