Key technology attributes

The business drivers of e-business on demand must be supported by a well-defined technical infrastructure.

These key technological attributes deliver the flexibility, responsiveness, and efficiency that on demand organizations require:

򐂰 Integration

򐂰 Virtualization

򐂰 Automation

򐂰 Open standards

Figure 2-2 on page 20 provides a high-level overview of the range of each e-business on demand attribute.

Figure 2-2 Four key technology attributes of e-business on demand

In the sections that follow, these four key elements are described as they apply to e-business on demand. They are then expanded to demonstrate the correlation of e-business on demand and the SOA.

Integration

The fundamental component of on demand infrastructure is integration:

In 2002, Sam Palmisano, Chief Executive Officer of IBM, defined on demand in the following way: “An on demand business is an enterprise whose business processes, integrated end-to-end with key partners, suppliers, and customers, can rapidly respond to any customer demand, market opportunity, or external threat.”

Integration can occur at various levels:

򐂰 People

To function at an on demand operating level, human-to-human and human-to-process interaction requires integration throughout the various levels not limited to end users. Business partners, customers, and employees are all important resources to the value chain provided by on demand. For example, integration can occur for developers through open tooling

on demand

Proprietary

Open Standards

Interoperable

Virtualization

Physical

Automation

Manual

Integration

Silos

Grid

Automated

Full Integration

Chapter 2. e-business on demand and service-oriented architecture 21 paradigms based on open standards, for business partners by the creation of horizontal processes and employees through collaboration.

򐂰 Process

Recurring elements (security, service level, monitoring, and so on) can be shared across applications to provide horizontal services to decouple these reusable application components. The use of SOA and Web services to implement these processes, including the emerging Business Process Execution Language for Web Services (BPEL4WS), will facilitate more rapid changes in these processes, enabling the business to respond with agility to changing market conditions.

򐂰 Applications

Organizations have invested enormous resources and capital into custom- designed and off-the shelf applications. The application integration goal is to leverage, rather than replace, these assets by providing ways of connecting, routing, and transforming the data that is stored or shared among them. Applications sit on disparate systems in an enterprise or across many enterprises.

򐂰 Systems

Systems manage, process, and deliver data to the people and applications in the solution environment. An on demand Operating Environment requires the system to be transparent to the elements that interact with it.

򐂰 Data

Data is the primary business element of a system. The data is the source of the information and can more easily be shared through the adoption of standards specifications.

Virtualization

Various areas of technology in our lives exploit virtualization concepts, including cell phones, PDAs, wireless connectivity, printers, and so forth. Aspects of virtualization draw on widely adopted architectural concepts, including object oriented design and development, Web services, and XML.

There is a spectrum of virtualization that begins at independent stand-alone systems on one side (a large mainframe system, perhaps) and grid computing on the other. In the middle are varying degrees of client-server implementations. A grid paradigm, an absolute example of on-demand virtualization, is a collection of distributed computing resources that are available over a local or wide area network and that appear to an end user or application as one large virtual computing system.

The Internet, the most widely recognized example of virtualization, provides a virtual network that supplies access to content and applications.

The vision is to create virtual dynamic organizations through secure, coordinated resource sharing among individuals, institutions, and resources. Grid computing is an approach to distributed computing that spans locations, organizations, machine architectures, and software boundaries.

Figure 2-1 on page 18 depicts virtualization as a set of virtualized resource pools based on:

򐂰 Servers

This could include partioning, hypervisors, VM OS, emulators, I/O virtualization, virtual Ethernet, and so forth.

򐂰 Storage

Here, the focus is on the addition of intelligence and value in the network.

򐂰 Distributed systems

This includes Web services, scheduling, provisioning, workload management, billing/metering, and transaction management.

The goal of grid computing, and thus on demand virtualization, is to provide unlimited power, collaboration, and information access to everyone connected to a grid.

Automation

Autonomic computing addresses an organization’s need to limit the amount of time and cost that occurs as a result of:

򐂰 Overprovisioning

򐂰 High cost of new applications and highly skilled labor

򐂰 Amount of time spent on disparate technology platforms even within one organization

򐂰 IT budget spent on maintenance, not problem resolution

򐂰 Complexities in operating heterogeneous systems

Note: Open Grid Services Architecture (OGSA) is an important starting point for grid enablement. For more information about OGSA, refer to the article at:

Chapter 2. e-business on demand and service-oriented architecture 23 So how can organizations begin to address these common concerns using an on demand Operating Environment? This is where autonomic computing comes in. Autonomic computing can be summarized using the four key components:

򐂰 Self-healing

A system’s ability to keep functioning. In order to achieve this, the system must detect, prevent, and recover from disruptions with minimal or no human intervention. This requirement is directly proportional to increased business dependence on technical infrastructures. The need for self-healing is directly proportional to the organization’s availability requirement.

򐂰 Self-configuring

The ability to adapt dynamically to changing environments, add and remove components to and from the systems, and change the environment to adapt to variable workloads.

򐂰 Self-optimization

Configuration that maximizes operational efficiency including resource tuning and workload management. This alleviates the constant drain on resources to perform routine tasks. The goal is to tune systems to respond to the workload changes. Systems have to monitor and self-tune continuously, adapting and learning from the environment around them.

򐂰 Self-protecting

Security is one of the inhibitors of the adoption of SOAs as organizations prepare themselves to share data externally. Self-protection requires the system to provide safe alternatives to secure information and data.

Self-protecting automation works by anticipating, detecting, identifying, and protecting systems from external or internal threats.

Open standards

While described as an attribute on its own, open standards affects the on demand Operating Environment across the previously defined levels including automation, integration, and virtualization. Each of these elements leverage open standards specifications in order to achieve their objectives. Open standards are the key element of flexibility and interoperability across heterogeneous systems. The global adoption of a standard specification enables the disparate systems to interact with each other. The underlying platforms may be completely different and independent but open standards enable processes to be built despite (or because of) these differences.

Open standards provide the e-business on demand Operating Environment with a standard, open mechanism to invoke system services.

Shortly, we will discuss the open standards that are involved in providing the level of interoperability that is required to create an SOA.