The Next Generation Data Center For Big Data Applications With Private Cloud

Cloud computing offers services to users based on on-demand self-service, broad network access, measured service, resource pooling and rapid elasticity; These characteristics promise a faster time for implementation, lower cost, superior scalability and a better end user satisfaction. These services are delivered in models known as Software As A service (SaaS), Platform As A Service (PAAS), and Infrastructure As A Service (IAAS). The first layer which is the Software As A service (SaaS) is the layer in which software applications are delivered to end users. Below is the Platform As A Service (PAAS) layer which offers a platform on which applications can be developed. The lowest layer is the Infrastructure As A Service (IAAS) layer, in this layer the physical servers and network infrastructure is offered as a service. These services can be deployed throughout the internet (Public Cloud Computing), on the intranet infrastructure, (Private Cloud Computing), in a shared community of private networks (Community Cloud Computing), or a hybrid of both (Hybrid Cloud Computing). The service deployment models are [8]:

SDC is a hot topic in the IT world and Stratoscales hyper-convergence (HaaS) is a software only solution that tightly integrates the datacenter siloes of proprietary infrastructure compute, storage, networking and virtualization resources and creates a pool of resources that is managed from a single pane of

The days of data centers with separate racks, management tools for storage, servers and different networking infrastructure may soon be a thing of the

Across Industry verticals there is increasing adoption of Hadoop for Information Management and Analytics. Many have realized that in addition to new business related capabilities Hadoop also offers a host of options for IT Simplification and cost reduction. Initiatives such as Offloads are at the heart of such optimization. That said, capacity planning is the first step that needs to be carried out successfully for either a IT driven use case or a business driven use case. This paper takes a look at why Big Data processing frameworks such as Hadoop clusters require careful capacity planning for the timely launch of Big Data based capabilities. Additionally, it discusses how capacity planning can facilitate appropriate service level agreement (SLA) guarantees and ensure deliveries within defined budgets. These types of guarantees with sets of standard hardware configuration are the key for effective capacity planning. The key constituent of overall capacity management strategy for the Hadoop eco system is Cluster Capacity Planning. It is this part of the strategy that caters to the troublesome and unavoidable

Every year the data transmitted over the internet is growing exponentially. By the end of 2016, Cisco estimates that the annual global data traffic will reach 6.6 zettabytes. The challenge will be not only to “speed up” the internet connections, but also to develop software systems that will be able to handle large data requests in optimal time. For the definition of the Big Data, there are various different

Organizations are beginning to realize that using outdated mainframes is no longer a viable pathway for meeting their data needs. This in turn has given way for the development and use of Cloud Computing. According to Fee (2013), the “history of the cloud dates back as far as the 1950s” with the concept of “timesharing,” in which several computers within an organization would share one giant “mainframe” computer (Fee, 2013, A brief…, para. 1). This eventually led to the creation of “ARPANET (Advanced Research Projects Agency Network)” by “J.C.R. Licklider,” who hoped “that someday everyone would be able to access data and programs from any location” (Fee, 2013, A brief…, para. 2). Suffice to say, Licklider’s dreams are now a reality as

The term “cloud” is not fairly new (Mohamed, 2009). The cloud can be dated back to the sixties. During the sixties, the evolution of cloud computing has continued to progress.

There are four deployment models of cloud computing. Each one has its unique benefits, therefore, the most suitable to a business must be chosen wisely. In the public cloud model, the cloud computing infrastructure is hosted at the vendor’s premises by the cloud vendor. The customer doesn’t know about the structure of the cloud nor has control over the location where computing infrastructure is hosted. In the public cloud, the computing infrastructure is shared among organizations. In Private cloud, the computing infrastructure is for one single organization and not shared with any other entities. Some say that private clouds are not considered a part of cloud computing. In comparison to public clouds, private clouds tend to be more expensive but more secure. There are two types of private clouds: On-premise private clouds and externally hosted private clouds. Externally hosted private clouds are hosted by a third party that specializes in cloud computing

Cloud computing programs, or the ideas of them, have been around since the 1960s, but it was not until the 1990s that the services were finally available due to advancements in technology. But to fully understand the importance of this innovation we must define what cloud computing is. Per the National Institute of Standards and Technology, an agency that creates standards and guidelines for providing information security for all agency operations and assets has defined cloud computing as a model that have easy access to a pool of shared network. Cloud computing programs must have the following five characteristics to be defined as such: on-demand self-service, broad network access, resource pooling, rapid elasticity, and measured service. Once the program satisfies these five elements in can meet one of three service models: Software as a Service, Platform as a service, and Infrastructure as a Service and one of four development models: private cloud, community cloud, public cloud, and hybrid cloud. For the sake of this paper we will focus on Software as a Service (Grance, 2011, 2-3).

Stratoscale is a unique software-only platform that enables enterprises to easily, quickly, efficiently and reliably build a private cloud using existing heterogeneous x86 infrastructure. Stratoscale integrates traditional data center silos into a single pool of IT resources and manages them from a single pane of glass – zero to cloud in minutes.

Cloud computing is a part of internet growth, it’s the next generation of internet. Cloud computing deliver everything –computing resource, infrastructure, application, and business process to personal collaboration – and can be access as service wherever and whenever through various devices. The cloud itself is a set of hardware, networks, storages, services, and interface that enable to delivery of computing as services based on user demand. (Hurwitz, J, 2009)

The computing power of one machine is not sufficient for processing huge data sets. Hadoop makes this possible by distributing the processing load throughout a cluster of nodes, or different machines that send messages to one another.

This study is focused on HBase database which is a column-oriented NoSql database. HBase is Apache’s open source database that is modeled after Google’s BigTable technology. It uses Java as the API and is developed on top of the Hadoop distributed file system (HDFS) to store and process large quantities of data, maintaining reliability and fault tolerance. This database is being used by many big enterprises including Facebook, Twitter and Yahoo to store and process large quantities of data in efficient and cost effective manner.

If the Information Age began in the 1990s with the rise of digital technology, then we’ve now officially entered the Age of Big Data, wherein companies like Google, Facebook, IBM, Teradata, Oracle, and SAS have the capacity to gather a lifetime’s worth of data about customers and their behavior.

However, as the immense cloud relocation changes the data center industry, a smaller, under-rated change has been occurring around the non-cloud applications that have been abandoned. These “edge” applications have remained on premise and, because of the nature of the cloud, the criticality of these applications has expanded altogether.