Purpose and Working of Data Centers

The hypervisor could be defined a technique based on virtualization of hardware that would allow several guest operating systems (OS) to run together within a single host based system at the same point of time. The OS of the guest would be able to share the hardware situated within the host computer as the OS would have their own processors, hardware resources and memory. The hypervisor is also called as the Virtual Machine manager (VMM). A Data Center could be defined as a facility that would comprise of networked based storage and computers, which would be used for organizing, storing and processing of larger amounts of data [1]. Container based virtualization could be defined as a form of virtualization based on operating system. This method of virtualization would run within the layer of virtualization based on the operating system. This report would focus on defining the various forms of aspects based on the three technologies and would thus provide a conclusion from the derived understandings of the research. 

Purpose – The primary purpose of a data center is based on the running of the applications of IT systems that would be able to handle the core operations of the business and data operations within the organization. The common form of components within the data center are file servers, databases, middleware and application servers [2].

Working – The data center would include the processes of computing and non-computing based within the data center environment. The working of data centers is based on the operations within the infrastructural processes such as installation of systems, maintenance, monitoring and evaluating of the services offered, providing patches and updating of the servers.

Scalability – The operators within the data center helps in accommodating scaling by providing sufficient form of infrastructure in order to facilitate much of the requirements needed by IT. The environment of data center would be helpful for scaling the level of infrastructure for supporting the increasing demands for data.

Features and Weaknesses – The features provided by data centers would include various benefits for cost and time. These data centers would be able to offer wide range of technical and cutting-edge tools. They also provide the capability to adapt to the various kinds of situations within the business, which would lead to improved form of flexibility within the operations [4].

The weaknesses of data centers is that they only provide the reduction of single mode of communication with the clients. There are various kinds of security issues that would be based within the data center service providers. There are also numerous challenges related to natural or man-made disasters [5].  

Scalability and Features of Data Centers

Socio-Technical Aspects – The social aspects in relation with the data centers would include the factors of consumerization within the IT processes, which has helped in empowering the consumers and have thus raised the level of their expectations that have been driven by social and mobile based businesses. The technical aspects within data centers would include the needs of maintenance of the data centers.

Some of the data centers based in Australia are Equinix, NextDC, Colocation Australia and many others.

Purpose – The hypervisor based virtualization technology is a form of function that would be able to abstract and isolate the operating systems and various applications that form the underlying base of computer hardware. The process of abstraction would allow the hardware of the host machine for operating independently based on more than one virtual machines as guest users [6].

Working – The hypervisor is a form of program that would enable the hosting of different form of virtual machines on a single form of hardware. The servers within the virtualization technology would be able to execute the performance of the hypervisor. The hypervisor would then load the client based operating systems within the virtual machines. The hypervisor would then allocate the proper form of resources to the CPU, bandwidth, memory and the disk storage space within each of the virtual machines.

Scalability – Whenever an application would demand more access to resources from virtual machines, they would give more resources in order to be handled within itself. The private clouds would allow the enterprises for making the resources to be available based on demands. The scaling up of resources would be available [7].

Features and Weaknesses – The primary features that are provided by hypervisors are that they are able to provide numerous benefits to the data centers of the enterprise. These would include the facilities provided by virtual server, which would be simplified and would save the space within the devices. This technology also makes use of the full capability of the provided applications.

The weakness of hypervisor is that they have a problem based on the difficulty within the access to hardware devices such as specific forms of USB devices or specific forms of cards. These hypervisors make use of RAM. Each of the virtual machines would be able to occupy a separate area of space.

Socio-Technical Aspects – The hypervisor based virtualization technology provides and thus supports the user for working together in an efficient manner. They would be able to share the resources and thus be able to perform the work of other users. As the hypervisor virtualization technique is capable of running on a huge number of container based systems, they would be greatly helped for allowance for use as the technology would be provided with tools [8].

Weaknesses and Socio-Technical Aspects of Data Centers

The technical aspects of hypervisor architecture is that the virtual machines would be managed by the software layer that would be installed on the bare metal. The x86 architecture of machines was not designed for the purpose of virtualization. Higher level of performance based on virtualization would be difficult to be achieved. The technical aspects of virtualization would include memory management, I/O and higher performance of CPU. This would ultimately help in providing the best level of performance, compatibility and reliability to the end users.

Two examples of virtualization technology are VMware and VirtualBox. The VMware virtualization tool would allow the desktop tool for Linux and Windows. VirtualBox is an example of Oracle’s host-based virtualization. The workstation of VMWare helps in providing a vast number of features for the purpose of desktop virtualization. They would be able to run the multiple VMs at the same point of time, create the encrypted VMs or would share VMs as server based systems.

Purpose – The container based virtualization is known as application and containerization. It is a form of reliable solution for the purpose of execution while movement within the computing environment. This process could be imagined as a form of transformation within the machine of the developer. The purpose of containers based technology is able to solve the problem for helping the software to run properly from one of the computing environment to another form of computing environment [9].

Working – The containers within the host operating system make use of the operating system of the host as their base without making use of the hypervisor. The containers would be able to virtualize the OS rather than virtualizing of the hardware. They also share the host OS kernel with both of the host and other form of containers. The containers also helps in providing the bare essentials that would be required for the running of any kind of applications on the host OS.

Scalability – The container engine would be able to perform within a manageable environment for the purpose of deploying various kinds of containerized applications. The engine within the container helps in allocating cores to the technology. They also helps in providing the scalability for enabling for the addition of the containers [10].

Features and Weaknesses – The features of containers are that the containers would be able to enable for the easy allocation of resources for the running of several processes in order to run various applications within various environments.

Purpose and Working of Hypervisor Based Virtualization

The container based technology would help in less form of flexibility within the operating systems. There are also various forms of challenges related with networking [11].

Socio-Technical Aspects – The social aspects within container based technologies is that they help in the security of the underlying technologies such that the information within the systems is not hampered. The technical aspects would include that the containers would be helpful in ensuring about the deployment of applications in a quick, reliable and consistent manner.   

Two container based virtualization technologies are Docker and Rocket. Docker is an open-source platform project that would be easily created based on lightweight, portable and self-sufficient containers based on any form of applications. On the other hand, Rocket is a platform for App Containers. The primary aim of rocket is to ensure fast form of secure and fast medium of performing functions. The limitations of Docker is that the newer released versions could be broken easily. The documentation made within Docker is not always synced and it also has an unreliable form of networking [12].  

Conclusion 

Based on the above discussion from the report, it could be discussed that these form of technologies are helping in the improvement within various forms of sectors. These technologies have helped for the management of various forms of applications, components of the software, maintain and run them on various platforms. They are also meant to upgrade the current environments and thus be able to match with the increasing growth of the technical platforms. This report has also focused on the different aspects of these technologies, which would be helpful for maintaining the applications.

References 

[1] Beloglazov, Anton, and Rajkumar Buyya. “Managing overloaded hosts for dynamic consolidation of virtual machines in cloud data centers under quality of service constraints.” IEEE Transactions on Parallel and Distributed Systems 24, no. 7 (2013): 1366-1379.

[2] Sun, Gang, Vishal Anand, Dan Liao, Chuan Lu, Xiaoning Zhang, and Ning-Hai Bao. “Power-efficient provisioning for online virtual network requests in cloud-based data centers.” IEEE Systems Journal 9, no. 2 (2015): 427-441.

[3] Dong, Jiankang, Xing Jin, Hongbo Wang, Yangyang Li, Peng Zhang, and Shiduan Cheng. “Energy-saving virtual machine placement in cloud data centers.” In Cluster, Cloud and Grid Computing (CCGrid), 2013 13th IEEE/ACM International Symposium on, pp. 618-624. IEEE, 2013.

[4] Ahmad, Raja Wasim, Abdullah Gani, Siti Hafizah Ab Hamid, Muhammad Shiraz, Abdullah Yousafzai, and Feng Xia. “A survey on virtual machine migration and server consolidation frameworks for cloud data centers.” Journal of Network and Computer Applications 52 (2015): 11-25.

[5] Sharma, Bikash, Timothy Wood, and Chita R. Das. “Hybridmr: A hierarchical mapreduce scheduler for hybrid data centers.” In Distributed Computing Systems (ICDCS), 2013 IEEE 33rd International Conference on, pp. 102-111. IEEE, 2013.

[6] Xavier, Miguel G., Marcelo V. Neves, Fabio D. Rossi, Tiago C. Ferreto, Timoteo Lange, and Cesar AF De Rose. “Performance evaluation of container-based virtualization for high performance computing environments.” In Parallel, Distributed and Network-Based Processing (PDP), 2013 21st Euromicro International Conference on, pp. 233-240. IEEE, 2013.

[7] Morabito, Roberto, Jimmy Kjällman, and Miika Komu. “Hypervisors vs. lightweight virtualization: a performance comparison.” In Cloud Engineering (IC2E), 2015 IEEE International Conference on, pp. 386-393. IEEE, 2015.

[8] Andrikos, Christos, Georgios Rassias, Panayiotis Tsanakas, and Ilias G. Maglogiannis. “An enhanced device-transparent real-time teleconsultation environment for radiologists.” IEEE Journal of Biomedical and Health Informatics (2018).

[9] Kozhirbayev, Zhanibek, and Richard O. Sinnott. “A performance comparison of container-based technologies for the cloud.” Future Generation Computer Systems 68 (2017): 175-182.

[10] Drutskoy, Dmitry, Eric Keller, and Jennifer Rexford. “Scalable network virtualization in software-defined networks.” IEEE Internet Computing 17, no. 2 (2013): 20-27.

[11] Li, Wubin, and Ali Kanso. “Comparing containers versus virtual machines for achieving high availability.” In Cloud Engineering (IC2E), 2015 IEEE International Conference on, pp. 353-358. IEEE, 2015.

[12] Baig, Roger, Jim Dowling, Pau Escrich, Felix Freitag, Roc Meseguer, Agusti Moll, Leandro Navarro et al. “Deploying clouds in the Guifi community network.” In Integrated Network Management (IM), 2015 IFIP/IEEE International Symposium on, pp. 1020-1025. IEEE, 2015.