| Description |
1 online resource (328 pages) |
| Physical Medium |
polychrome |
| Description |
text file |
| Contents |
Cover; Title Page; Copyright and Credits; About Packt; Contributors; Table of Contents; Preface; Section 1: VMware Approach with ML Technology; Chapter 1: Machine Learning Capabilities with vSphere 6.7; Technical requirements; ML and VMware; ML-based data analysis; Using virtualized GPUs with ML; Modes of GPU usage; Comparing ML workloads to GPU configurations; DirectPath I/O ; Scalability of GPU in a virtual environment; Containerized ML applications inside a VM; vGPU scheduling and vGPU profile selection; Power user and designer profiles ; Knowledge and task user profiles |
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Adding vGPU hosts to a cluster with vGPU ManagerML with NVIDIA GPUs; Pool and farm settings in Horizon; Configuring hardware-accelerated graphics; Virtual shared graphics acceleration; Configuring vSGA settings in a virtual machine; Virtual machine settings for vGPU; GRID vPC and GRID vApps capabilities; GRID vWS to Quadro vDWS; Summary; Further reading; Chapter 2: Proactive Measures with vSAN Advanced Analytics; Technical requirements; Application scalability on vSAN; Storage and network assessment; Storage design policy; VMware best practices recommendations ; Network design policy |
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VMware best practices recommendations VMware's Customer Experience Improvement Program/vSAN ReadyCare; Intelligent monitoring; General monitoring practices; vSAN Health Check plugin; vSAN Observer; vRealize Operations Manager monitoring; Challenges affecting business outcomes; Business benefits; Technical Issues; Technical solution; Log Intelligence advantages; HA configuration in stretched clusters; Two-node clusters; Witness appliance for the vSAN cluster; Configuring the vSAN cluster; vSAN policy design with SPBM; Defining a policy based on business objectives |
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FTT policy with RAID configurationsSummary; Further reading; Chapter 3: Security with Workspace ONE Intelligence; Technical requirements; Workspace ONE Intelligence; Business objectives of Workspace ONE Intelligence; Integrated deep insights; App analytics for smart planning; Intelligent automation driven by decision engines; Design requirements; Conceptual designs; Top ten use cases of Workspace ONE Intelligence; Identifying and mitigating mobile OS vulnerabilities; Insights into Windows 10 OS updates and patches; Predicting Windows 10 Dell battery failures and automating replacement |
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Identifying unsupported OS versions and platformsTracking OS upgrade progress; Monitoring device utilization or usage; Increasing compliance across Windows 10 devices; Comprehensive mobile app deployment visibility; Tracking migration and adoption of productivity applications; Adopting internal mobile applications; Workspace ONE Trust Network; Workspace ONE AirLift; Workspace ONE platform updates; Expanded Win32 app delivery; Simplified macOS adoption; Extended security for Microsoft Office 365 (O365) applications; VMware Boxer with Intelligent Workflows |
| Note |
Extended management for rugged devices |
| Summary |
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. |
| Local Note |
eBooks on EBSCOhost EBSCO eBook Subscription Academic Collection - North America |
| Subject |
VMware.
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VMware. |
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VMware. |
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Virtual computer systems.
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Virtual computer systems. |
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Computer networks.
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Computer networks. |
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Machine learning.
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Machine learning. |
| Genre/Form |
Electronic books.
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| Other Form: |
Print version: Kundan, Ajit Pratap. Intelligent Automation with VMware : Apply Machine Learning Techniques to VMware Virtualization and Networking. Birmingham : Packt Publishing Ltd, ©2019 9781789802160 |
| ISBN |
1789806798 |
|
9781789806793 (electronic book) |
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