Something had to give. So, to address these concerns and challenges, the concept of grid computing began to take shape in the early 2000s. With grid computing, groups of inexpensive networked servers functioned as one large server. This meant that IT departments no longer had to acquire large and expensive servers to meet existing or anticipated workload requirements. Moreover, capacity could be added to existing infrastructure by simply adding new servers and systems. Grid computing also enabled data center consolidation via server clustering. The next logical extension of this technology was cloud computing. (Learn more about how to tell cloud and grid apart in What is the difference between cloud and grid computing?)
Why the Cloud?The basic premise of cloud computing is that users can get access to any IT resource, including storage, CPU resources, memory and software over the Internet whenever they want. They can also pay for their actual use of the resource rather than incurring capital and operational expenditures in order to own and operate the IT infrastructure themselves. This computing scheme closely mimics the way households pay for utilities such as electricity and gas on metered usage. That's part of the reason why cloud computing has revolutionized the way IT infrastructure can be managed and used. It means more effective management of data centers because it puts more emphasis on server virtualization, standardization, automation and self-service provisioning.
In a private cloud, an organization sets up a virtualization environment on its own servers, either in its own data centers or in those of a managed services provider. This structure is useful for companies that either have significant existing IT investments or feel they absolutely must have total control over every aspect of their infrastructure. The key advantage of a private cloud is control. You retain full control over your infrastructure, but you also gain all of the advantages of virtualization. (Learn more about private clouds in Public, Private and Hybrid Clouds: What's the Difference?)
Drivers for Private CloudThe following image shows the technological drivers for building a private cloud for an enterprise. These include the need for rapid scaling of applications and an inability to predict capacity and performance needs. In other words, cloud solutions are more flexible, which can be a real advantage for certain types of business.
Figure 1: Private cloud IT drivers
The adoption of a private cloud may also be driven by business factors. These include the need to reduce the costs of IT ownership and operation, and the need to speed up production. When a cloud infrastructure is able to provide these sorts of benefits for an enterprise, there is often a very strong case for adopting it.
Figure 2: Private cloud business drivers
Cloud Service ModelsCloud computing service models indicate the type of service that is being offered. These include a hardware/software infrastructure; an application development, testing, and deployment platform; or enterprise software ready for use by subscription.
An enterprise can expect to access a cloud under one of the following three service models:
- Software as a Service (SaaS)
Applications are delivered as a service to end users over the Internet. This model is the earliest model of cloud computing in which software companies started to sell their solutions to businesses based on the number of users with a given set of service-level requirements. The major players in this field are Oracle (with its CRM on-demand solution), Salesforce.com, and Google (with its Google Apps).
- Platform as a Service (PaaS)
An application development and deployment platform (made up of application servers, databases, etc.) delivered as a service. Amazon Elastic Compute Cloud (EC2) and Savvis are the prominent providers of this model of cloud service.
- Infrastructure as a Service (IaaS)
Server, storage and network hardware and associated software delivered as a service. Amazon EC2 is the prominent provider of this model of cloud service. Key technologies that have enabled cloud computing in general are virtualization and clustering.
Figure 3: Cloud computing service models
Virtualization Vs. Private CloudMost of the virtualization software that is available today is based on hypervisor technology, which was introduced by IBM in the 1960s with a mainframe-based product called CP/CMS. This eventually evolved into a product known as z/VM. Virtualization in cloud computing typically involves deploying many operating system images (virtual machines (VMs)) on a single server sharing available CPU resources and memory. This also facilitates monitoring of resource consumption by individual VMs for use by charge-back systems later. The image below weighs the pros and cons of virtualization against the use of a private cloud.
Figure 4: Virtualization Vs. private cloud
Building a Private Cloud Step by StepBuilding a private cloud isn't simple, but once it's up and running it can significantly simplify IT. The following lists the sequence of steps essential for building a private cloud.
- Assessment of the existing infrastructure is carried out to understand the application data, workload characteristic and hosting environment.
- Physical infrastructure is assessed to ensure that it can be used for a private cloud solution. Otherwise, it needs to be refreshed as part of the data center transformation.
- A virtualization layer is built and can be based on VMware, Hyper-V or Xen.
- Asset management is deployed to track and update all the converged infrastructures via a discovery tool.
- Virtualization management tools are build over the infra layer.
- Asset management and virtualization management tools are integrated.
- The automation piece and orchestration layer is integrated over the virtualization infrastructure.
- Other tools within the management layer are deployed, such as ITSM, CMDB, and SRM.
- Integration between the automation and orchestration layer to the ITSM, CMDB is built.
- The service catalogs and ITFM are built.
- All the workflows for the orchestrator are built and configured. Creation of workflows and their storage in the orchestration library (provisioning, de-provisioning, remediation and auto ticketing) also occurs at this point.
- The CMDB is integrated with the discovery tool and asset management is completed to capture and perform asset and configuration management.
- A self-service portal for user access and catalog management is deployed.
- A template and images are created or imported from an existing environment.
- Billing and charge-back tools are implemented and integrated with CMDB.
- Once the setup, configuration and integration are completed, VMware and Hyper-V hosts to centralized cloud management are added or migrated.
- Functional/integration/UAT testing is then carried out on the implemented solution.
- Customized reports as per requirements for capacity, usage, billing and charge back information are implemented.
- The production environment is integrated with the deployed cloud management solution.
- The enterprise transitions to ASM for the management of day-to-day activities.
Figure 5: Workload clustering
Benefits of Private CloudA private cloud has some key benefits for enterprise. The image below depicts what it can do.
Figure 6: Benefits of private cloud