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Service Virtualization - Completing the Cloud Story

Organizations that have applications in production are required to have atleast 4-5 different sets of pre-production environments like System Testing, Performance Testing, User Acceptance Testing, Automated Regression Testing environments, to ensure 100% validation of the different set of requirements associated with an application. This in all probability increases the CAPEX budget for the organization. Organizations typically consolidate, virtualize and share these infrastructures for validating applications across different Lines of Business (LoBs). But this exercise is also bound to have significant OPEX associated with it due to the costs incurred in terms of having dedicated teams/personnel to manage the environments, rental costs and infrastructure costs. Also, even in these setups testing teams are constrained with situations like waiting for access to expensive test tool licenses/legacy systems, external/dependent systems, etc. In order to overcome these issues in testing traditional environments, it is but natural for us to look at the need to virtualize external/dependent systems using techniques like Service Virtualization.

Let us consider a scenario, where we have a Payments Processing Engine (PPE) which is currently undergoing changes and is hosted in a traditional QA environment. This PPE systems needs to talk to two major external systems, Legacy and Data warehouse, which are not currently available and are out of scope for testing. If the organization is to test the PPE system end-to-end, then they will need to acquire access to the external systems. Further, not being available on the virtualized environment is not the only constraint that this situation has to offer. Access to legacy system is expensive and it's made available in a 2 hour time window only. Also, the Data warehouse system is not available in the pre-production environment. When there are such constraints/dependencies on external systems, delays in time-to-market and increase CAPEX requirements are bound to bring down the overall testing efficiency. The way out for Organizations faced with such situations is to adopt Service Virtualization or virtualize services for all external/dependent systems, like the Legacy and Data warehouse systems in this particular example.

Today's market dynamics forces business to be more cost effective, agile and scalable to service ever changing market demands. The advent of cloud computing has made it possible for organizations to achieve the above mentioned points, in addition to helping organizations move from a CAPEX to OPEX business model. Though this movement to the cloud brings sizable benefits and cost savings, it doesn't however answer the question of dependencies on external systems. Organizations will need to spend huge amounts on setting up cloud images for these large external systems, making the entire process unfeasible. So, how can organizations do away with the issue of external system dependences in a cloud environment? This is where Service Virtualization comes in. With Service Virtualization, organizations can create virtual models of external dependent systems and bring them to the cloud as Virtual Services (VSE), with 24/7 availability and low cost.

Let us consider a scenario to understand the applicability of Service Virtualization in a Cloud environment.  Currently, we have an Order Management System (OMS), hosted in a cloud based environment, undergoing changes. This OMS system in turn needs to talk to 3 major external systems - Mainframe, ERP and Databases - that are not on the cloud and are out of scope for testing. If the organization is to test the OMS along with 3 external systems, then they will need to spend huge amounts in setting up the external systems - Mainframe, ERP and Database, in the cloud. This will result in higher CAPEX for the organization, which could very well blunt the cloud benefits of Cost Saving and Optimized IT spending. With Service Virtualization, the organization can host the OMS application in a virtual machine in the cloud, while the external/dependent systems - Mainframe, ERP and Databases, can be modeled and used as Virtual Services (VSE) implementations in the cloud. Thus by applying Service Virtualization all the external/dependent systems are provisioned at a fraction of the overall external system setup costs. With Service Virtualization, Organizations can achieve goals of elastic capacity consumption. Organizations can also cut down significant wait times associated with effort of infrastructure acquisition, installation and setup, and with accessing of external /dependent systems from months/weeks to a few minutes.

Thus with Service Virtualization, Organizations can achieve their overall goal/ objective of moving to the cloud and being responsive and relevant to the ever changing market dynamics and demands.

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