Setup and Implementation

//Setup and Implementation

Cloud services are being implemented by ever more businesses. However, in fact, only very few prepare their steps in a long-term way or even ask themselves basic questions: what does the cloud mean for the company in the short, medium and long term? How can IT leverage the cloud’s benefits and integrate them in an orderly fashion into existing infrastructure?

It takes a certain amount of effort to include cloud-based software, but this does not need to cause big problems or even chaos to break out. This technology can be integrated into the IT infrastructure in such a way that it can be strategically monitored and handled. Most businesses have not taken this into account enough in the past and are therefore referring to the confusion caused by this as “virtual sprawl.” Companies must adopt a clearly defined policy on the use and management of the cloud to leverage the obvious benefits it offers. These have been developed on the basis of the many different projects which have already been carried out and which apply to large and small companies as well as to companies which embrace technology or are more practical.

Here are a few steps describing how the implementation process of our cloud computing solution works:
  • First step: Virtual Infrastructure

    Hardware becomes software: Physical infrastructures are replaced by virtual infrastructure during the first phase of introducing the cloud. In this case a hardware virtual instance is created by a software layer. The program has a benefit, that it is easier to replace and easier to monitor than the hardware. However, virtualization technology isn’t new. Starting in the 1970s, for example, IBM started selling virtual machine hypervisors as part of its portfolio. Today, virtualization or cloud goods are sold by all major IT manufacturers.

    The most common use of virtualization is the installation of a server consolidation program that reduces the number of physical machines. Virtualization is then gradually extended to generate private clouds that provide virtual capabilities and applications on request to internal users. Cloud computing is a virtualization extension to include the public network. This includes the use of cloud capabilities to provide a basic computing process network, and different types of scalable software such as databases. This form of cloud usage is commonly referred to as a service (IaaS) infrastructure. The key benefit of these offers lies in the quick delivery of capacities and applications in minutes, not weeks or months. Besides they can be automatically deployed can programming interfaces (APIs). They are flexibly scalable, and only incur costs when used. The cloud’s characteristics have already resulted in two common usage scenarios: self-service environment creation for research, development, training, and demonstration, as well as quick processing of high-performance workloads, and load testing for applications using ad-hoc virtual machines. However, simple cloud use also poses challenges. It is sometimes used simply to avoid having to work with the IT department within. This approach seems to provide a quicker way to implement processes, but only until the professional management of created IT assets is important. The technologies and applications that arise can either get out of reach or remain unused. And if they are poorly handled, they may also pose a danger to health. Too then they aren’t even shielded from errors.

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  • Second Step: Dynamic Applications

    Cloud applications start tracking their use automatically during the second process. For rising data volumes, cloud APIs are being used to replicate their content and spread processes through the extended network. One popular approach here is to enable the automatic generation of scripts by virtual machines through run book automation. We install and trigger appropriate software for development. The combination of monitoring within the application and scripting outside allows for expanding and dynamically reducing the computing power.

    The economic benefits of this strategy are paramount. After all, it costs a lot of money to set up large data processing centers that are prepared to handle high volumes of data. However this is not possible by using a dynamic application architecture. When performance is achieved and therefore the data traffic increases, businesses can deploy higher computing power when required. Then, they just have to compensate for this for a short period and can lower the capacities again when the amount of data decreases. Scalability for large projects will range from several hundred to several thousand servers-and then be drawn down again.

  • Third Step: Flexible Data Processing Center

    Only businesses that put the highest possible demands on their server environments understand the third level of cloud implementation. These are primarily companies with workloads in the fields of financial services, electricity, and online advertising, which rise and fall very rapidly and must be handled immediately. High scalability applies here not only to the applications but also to the entire data processing center and all its components, including servers, memory, databases, applications, and the network.

    A daunting challenge is the construction of a versatile data processing center. It can be achieved using virtualized infrastructures. In the most scalable data processing centers virtual capacities are implemented internally. This will most likely be done more often in the future though the public cloud. Monitor workloads from various sources to be performed and then scale the data processing center as well as all applications involved in processing processes.