International Journal of Computer
Trends and Technology

Research Article | Open Access | Download PDF

Volume 58 | Number 1 | Year 2018 | Article Id. IJCTT-V58P111 | DOI : https://doi.org/10.14445/22312803/IJCTT-V58P111

VMWARE Virtualization - Physical to Virtual Migration

Subash Thota

Citation :

Subash Thota, "VMWARE Virtualization - Physical to Virtual Migration," International Journal of Computer Trends and Technology (IJCTT), vol. 58, no. 1, pp. 65-75, 2018. Crossref, https://doi.org/10.14445/22312803/IJCTT-V58P111

Abstract

Resource optimization is one of the key drivers for deploying virtualization technology. Regardless of whethertheresourcesarecurrentlyunder-utilizedorover-utilized,itinfluencestheBusiness.Virtualization offers the potential for a reduction in total server hardware and better management of that hardware, but it is not without its own caveats. There are both advantages and disadvantages to using virtualization in any environment,anditiscriticalthatyouunderstandtherealityofwhatvirtualizationcanofferandreconcilethat with your expectations of how it can be used in yourenvironment.For example, you should not assume that applications are suddenly going to require fewer resources just because they are virtualized. On the contrary, the use of virtualization adds overhead, and virtualized applicationsoftenusemoreresourcesthanbefore.Theactualamountofoverheaddependsonanumberof factors including the type of application, which virtualization engine is being used, what kind of hardware is available, and how it will be used. Before implementing virtualization you need to make sure that you have enough storage bandwidth/space, memory, CPU, network bandwidth and other resources to handle the applicationsANDthevirtualizationoverhead.Whenyouexhaustanysingleresourceonaserverthatisused for virtualization, all guest operating systems may be impacted and seen to wait for that single resource. Thus, low CPU or memory utilization alone is not an indication that additional work can be added - youmust verify that all required resources have availablecapacity.

Keywords

Big Data Analytics, Social Analytics, Storage Analytics, Data Management, Information Quality, Data Mitigation, Metadata, Data Profiling, VMWARE

References

[1]http://pubs.vmware.com/vsphere-55/topic/com.vmware.ICbase/PDF/vsphere-esxi-vcenter-server-551-installation-setup-guide.pdf http://www.vmware.com/in/virtualization/how-it-works
[2] Memory Resource Management in VMware ESX Server http://www.vmware.com/pdf/usenix_resource_mgmt.pdf
[3] vSphere Resource Management Guide http://www.vmware.com/pdf/vsphere4/r40/vsp_40_resource_mgmt.pdf
[4] Performance Tuning Guidelines for Windows Server 2008 R2 http://www.microsoft.com/whdc/system/sysperf/Perf_tun_srv.mspx
[5] Bi Data Analytics with R and Hadoop Vignesh Prajapati, Packt Publishing, 1st edition, 2013.
[6] Thota, S., 2017. Big Data Quality. Encyclopedia of Big Data, pp.1-5. https://link.springer.com/referenceworkentry/10.1007/978-3-319-32001-4_240-1
[7] Machine Learning with R Brett Lantz, Packt Publishing, 1st edition, October 2013.
[8] Hadoop For Dummies Dirk deRoos, Paul C. Zikopoulos, Bruce Brown, Rafael Coss, and Roman B. Melnyk, John Wiley & Sons, Inc., 1st edition 2014.
[9] Hadoop Beginner`s Guide Garry Turkington, PacktPublishing, 2013.
[10] https://cwiki.apache.org/confluence/display/Hive/LanguageManual+ORC
[11] hortonworks.com/blog/announcing-apache-hive-0-12
[12] Subash Thota "Virtual Infrastructure (Journey from Physical Servers to the Cloud)". International Journal of Computer Trends and Technology (IJCTT) V52(1):4-8, October 2017. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.