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From ESBs to API Portals, an Evolutionary Journey | Part 1

The state of the art today is epitomized by cloud computing under the service paradigm

A number of analysts are beginning to suggest 2013 will likely signal the awakening of a long night in the IT industry that started with the beginning of the third millennium with the Internet crash. And just as recovery was around the corner, the financial crisis of 2008 dried the IT well once more. Both crises can be characterized as crises of demand. Just past 2000, the Y2K pipeline ran dry. Some argue that the problem was overstated, whereas others argue that the problem was solved just in time. In either case this event triggered a significant pullback in IT spending.

Faced with an existential threat after Y2K, the IT industry did not sit still. The main outcome from these lean years has been a significant increase in efficiency where the role of IT in companies with most advanced practices shifted from being a cost center to an active participant in the execution of corporate business strategy. Capabilities evolved from no accountability on resource utilization to efficient use of capital to nimble participant in a broad range of organizations and initiatives.  The second crisis reaffirmed the continuing need to do more in the face of shrinking budgets and very likely provided the impetus for the widespread adoption of cloud technology.

The state of the art today is epitomized by cloud computing under the service paradigm. From a historical perspective the current state of development for services is in its third iteration.

The early attempts came in various forms from different angles and as many vendors. The most prominent examples of this era came from application server and connectivity ISVs (independent software vendors) and from operating system vendors: Microsoft, IBM, TIBCO and various Unix vendors of that era. The main characteristic of this era that went roughly from 1995 to 2005 was single-vendor frameworks with vendors attempting to build ecosystems around their particular framework. This approach did not take off, partly because concerns in IT organizations about vendor lock-in and because the licensing costs for these solutions were quite high.

The second era was the era of SOA that lasted roughly from 2000 to 2010. The focus was to re-architect legacy IT applications from silo implementations to collections of service components working together. Most of the service components were internally sourced, resulting perhaps from the breaking former monoliths, and combined with a few non-core third party services. Vendors evolved their offerings so they would work well in this new environment. The technology transformation costs were still significant as well as the demand on practitioners’ skills.  Transformation projects required a serious corporate commitment in terms of deferrals to accommodate process reenginering, licensing fees and consulting costs. As a result, the benefits of SOA were available only to large companies. Small and medium businesses (SMBs) and individual consumers were left out of the equation.

Cloud technology drives the current incarnation for IT services following the crisis of 2008. Clouds notwithstanding, if we look at the physical infrastructure for data centers, it is not radically different from what it was five years ago, and there are plenty of data centers five years ago or older still in operation. However, the way these assets are organized and deployed is changing. Much in the same way credit or other people’s money drives advanced economies, with the cloud other people’s systems are driving the new IT economy.

Scaling a business often involves OPM (other people’s money), through partnerships or issuing of stock through IPOs (initial public offerings). These relationships are carried out within a legal framework that took hundreds of years to develop.

In the real world, scaling a computing system follows a similar approach, in the form of resource outsourcing, such as using other people’s systems or OPS. The use of OPS has a strong economic incentive: it does not make sense to spend millions of dollars in a large system for occasional use only.

Large scale projects, for instance a marketing campaign that requires significant amounts of computing power are peaky in the usage of infrastructure assets, usually start with small trial or development runs, with large runs far and few between. A large system that lies idle during development would be a waste of capital.

Infrastructure sharing across a pool of users increases the duty cycle of infrastructure assets through the sharing of these assets with multiple users.  Cloud service providers define the sandbox whereby a number of corporate or individual users have access to this infrastructure. Cloud computing increases the efficiency of capital use through resource pooling delivered through a service model.

The first step in the infrastructure transformation came in the form of server consolidation and virtualization technology. After consolidation became a mainstream IT practice, the trend has been toward the support of more dynamic behaviors. IaaS allows the sharing of physical assets not just within the corporate walls, but across multiple corporate customers. A cloud service provider takes a data center, namely $200 million asset and rents individual servers or virtual machines running inside them by the hour, much in the same way a jet leasing companies takes a $200 million asset, namely an airliner and leases it to an air carrier which otherwise would not be able to come up with the upfront capital expense. The air carrier turns around and sells seats to individual passengers, which is essentially renting a seat for the duration of one flight.

In other words, the evolution we are observing in the delivery of IT services is no different than the evolution that took place in other, more mature industries. The processes that we are observing with cloud computing and associated service delivery model is no different than the evolution of the transportation industry, to give one example.

As we will see in the next few articles, the changes brought by the cloud are actually less about technology and more about the democratization of the technology: the quantum for delivery used to be so large that only the largest companies could afford IT. Over the past few years IT became accessible to small and medium businesses and even individual consumers and developers: businesses can purchase email accounts by the mailbox with a monthly fee, and deployment models allow individual consumers to sign up for email accounts at no out of pocket cost. We will look at the evolution of the service model from a corporate privilege to mass availability. From a practical, execution perspective, products like the Intel® Expressway Service Gateway and Intel® API Manager were developed to support the life cycle of cloud enabled applications, and I’ll be pointing to aspects of these products to provide specific examples of the concepts discussed.

In the next article we’ll discuss the “big guns” services represented by the SOA movement in the first decade of the millennium.

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