Chapter 3. Business objectives
3.2 Cloud computing
Before transforming your IT capabilities to effectively provide business
intelligence and analytics services, it is important to think about what it might look like. Instead of reinventing the wheel, you might model an IT service based on successful existing service models, such as water or electricity utilities. Public utilities can service many consumers while standardizing and centralizing delivery. They use economies of scale to provide competitive pricing and additional value. After some further consideration, you might consider these operational requirements: scalable, resilient, elastic, automated, and
standardized. You can also envision an environment where the end users have a simple method to request services and that there are easy processes for adding, maintaining, and sun-setting services.
With so many different aspects, where do we start when developing a business intelligence and analytics service? First, let us consider the operational parts of a service and determine if they, like a public utility, are good candidates for
centralization.
The four key operational parts of a service are:
Hardware
Software
Data
Business applications
Hardware infrastructure can be managed centrally by an organization or locally by lines of business. The local management approach resulted in a proliferation
of server farms, which has reversed because organizations are leveraging virtualization and want to benefit from economies of scale.
Business Intelligence software and middleware can either be purchased on a department-based level or on an enterprise level. Over time, departments might develop different preferences and skill sets, but such preferences are often outweighed by savings that can be achieved when negotiating for either a larger number of licenses for one product or a smaller set of enterprise-wide software. Further costs reductions are seen in administration and maintenance costs too. Centralization of data, however, receives strong objections by departments. Responsibility for data is a sensitive topic. Lines of business must be in control of the information that is important for the business that they are responsible for and therefore want to manage data themselves, which leaves them enough flexibility to react to changes in the market.
Business applications provide strategic value to each line of business. While the underlying software and middleware can be centralized, it does not make sense to use the same approach for the value differentiating end-user application. Of the operational components, the hardware and software infrastructure components lend themselves to a centralized approach. Centralization and standardization of that infrastructure is known as cloud computing. While cloud computing signals a shift from a distributed to a centralized mindset, there is real value in such a change. Lines of business can focus on what they feel is more important, their data and business applications, and can obtain the reliable infrastructure from the specialized cloud provider.
The term cloud computing is used in different ways. Its usage, however, does have common themes. On one hand, cloud computing is an infrastructure and services methodology. On the other hand, it is also a user experience and business model.
Cloud Computing is:
An infrastructure management and services delivery methodology: Cloud computing is a way to manage large numbers of highly virtualized resources such that, from a management perspective, they resemble a single large resource, which can then be used to deliver services with elastic scaling.
A user experience and a business model: Cloud computing is an emerging style of IT delivery in which applications, data, and IT resources are rapidly provisioned and provided as standardized offerings to users over the Internet in a flexible pricing model.
The cloud meets key requirements, which are:
Scalability: Can increase capacity without impacting functionality.
Resiliency: Allows applications to continue functioning even when underlying components fail.
Elasticity: Can add or change functionality without changing or disturbing existing functionality.
Automation, standardization: Adding resources in a standardized way and, wherever possible, in an automated way.
Service life cycle support: Setting up new infrastructure and software, maintaining it, and sunsetting it.
Self Service: Provides an easy-to-use interface that allows end users, who might not have deep technical skills, to request new resources.
Cloud computing is not just an improvement in data center infrastructure, but it is also a user experience and business model. In a cloud deployment, the end user sees standard offerings of services that are easily accessed and rapidly
provisioned. Figure 3-1 depicts a cloud and its basic components.
Figure 3-1 Components of a cloud
IT Cloud Monitor & Manage Services & Resources
Data Center Hardware & Software Service Catalog, Component Library Service Consumers
Publish & Update Components, Service Templates Access Services Cloud Administrator Cloud User Cloud Application Manager Component Vendors/ Software Publishers
The basic internal components of a cloud are data center infrastructure, a service catalog, and a component library. Data center infrastructure includes hardware, such as a System z, software such as IBM Cognos 8 BI, and middleware like DB2. The component library encompasses the hardware, software, and service components that are required to deliver services. The software catalog lists the services that are provided to the customers, for example, the service catalog can include installation of a Linux guest, licenses for Cognos, or even a complete Smart Analytics Cloud service.
The key roles in the cloud are service consumers, administrators, software publishers, and component vendors. Service consumers make requests through access services that have a standard user interface. Cloud administrators monitor and manage the services and resources that are delivered. Software publishers might be internal departments that develop customized services. Component vendors, such as IBM, can also offer services, such as the Smart Analytics Cloud.
In discussing cloud computing, it is also important to distinguish between types of clouds. While there is variation in the naming, there exist predominantly to classifications, public and private1.
A
public cloud
is owned and managed by a service provider and access is through subscription. It offers a set of standardized business processes, application, and infrastructure services on a price-per-use basis. Advantages of a public cloud include standardization, capital preservation, flexibility, and a shorter time to deploy applications. A
private cloud
is accessible only through your company and your partner network. It provides more ability to customize, drives efficiency, and retains the ability to standardize and implement best practices. Other advantages are that the levels of availability, resiliency, security, and privacy are determined on an enterprise level independently from an external provider.For many organizations, public clouds are not secure or reliable enough. Private clouds provide increased flexibility and are used for enterprise class solutions.