A Self-Adapting Cloud Architecture
By Charlie Dai, Principal Consultant for Enterprise Architecture, Forrester Research
Business has become increasingly customer-centric as mobile, digital, and social networking tools have put more power in consumers’ hands. Forrester Research believes that successful enterprises are those able to reshape themselves based upon a systematic understanding of tech-savvy customers and the ability to cater to those customers’ service needs. One of the critical supporting factors behind a successful transformation for these enterprises is the use of a self-adapting, smart computing platform based on hybrid clouds. Hybrid clouds are designed to provide an elastic and agile platform for implementing smart services that adjust rapidly to meet customer needs. The success of these adaptable and smart services will highlight the business value of hybrid clouds.
Support for Hybrid Clouds
Forrester Research believes the trend in integration of infrastructures, platforms, and software for cloud computing solutions is able to meet the growing service needs of customers. Take Platform-as-a-Service (PaaS) and Infrastructure-as-a-Service (IaaS) as examples. These two services intersect in areas such as application containers, platform services, application life-cycle management, and development tools. The two services overlap in areas such as in-depth customization, system integration, and Application Programming Interfaces (APIs). As part of the trend to leverage PaaS and IaaS, the smooth evolution of legacy enterprise systems requires deployment of enterprise-level cloud computing platforms that support hybrid clouds.
Viewed from an implementation perspective, support for hybrid clouds means support for public clouds, hosted private clouds, or other types of private clouds. Forrester Research’s “Forrsights Services Survey Q2, 2012” predicted that about 85 percent of global enterprises would come out with their own cloud computing strategies by the end of 2013, and these enterprises would determine their approaches concerning public, private, and hybrid clouds based on deployment scale, development strategies, and technology management architectures, among others.
Similar to traditional business intelligence software that focused on mining internal enterprise data, some early Big Data applications implement unidirectional and parallel processing of structured and non-structured data based on open-source architectures such as Hadoop and Storm. Although such approaches may prove effective for a particular purpose or application, they add to IT costs and risks. Another issue with such approaches is that unidirectional processing of data is based on the conventional thinking of the businesses involved, which could be limiting. For example, enterprise perceptions of customer or partner behavior patterns can be way off the mark. This type of assumption inevitably limits the depth and breadth of business insight, and the limitation can only be avoided by adopting unconventional approaches such as adaptable intelligence.
Forrester Research defines self-adaptable intelligence as a real-time and multi-channel data-sharing mechanism that maximizes business value by delivering authoritative knowledge able to suit the context and intended use of the information being analyzed. Unlike conventional unidirectional data transmission or bidirectional data exchange mechanisms, self-adaptable intelligence stresses the importance of maximizing the utilization of applications intended for internal enterprise data mining. This approach lays the foundation for multi-directional and real-time data exchange within the ecosystem of an enterprise, based on the elasticity of hybrid cloud platforms and the workload response capabilities of inter-system and inter-organization architectures.
The ability to obtain penetrating customer insight in real time and to deliver the right products and services with agility is crucial for next-generation enterprises. To implement this capability, enterprises need to review their technology management approaches, work out an evolution roadmap that suits their business strategies and employee capabilities, and build self-adaptable, smart hybrid cloud-computing platforms that support the necessary tools and services.