all services presents several problems. The composition of services on the platform is predefined and consists of required as well as nonessential capabilities. New service rollouts and software upgrades typically require changes to existing network elements. This requires extensive regression testing of the platform and existing services, thereby extending the roll-out period of the new service. Session state is tightly coupled with network elements and is lost if network elements at a site fail. Also, upon element failures, stable sessions are lost and there is a possibility of registration storms, which requires overprovisioning network resources to handle storm scenarios. Network platform rollouts (capacity augmentation or upgrades) also have a very lengthy cycle time as a result of a fixed deployment approach based on geographic regional boundaries. In the current model of introducing new services, especially those that require the deployment of PNFs, it typically takes 12-18 months or more to realize a new service, depending on the complex- ity of the service and the number of network functions involved. Much of that time is spent in build- ing the laboratory, performing laboratory testing, field deployment, and production testing, prior to service turn-up. Many services are deployed as silos requiring dedicated infrastructure resources. Investment in network infrastructure is made at least 6 months before it starts getting utilized for many services. To meet the business continuity needs in cases of network outages, infrastructure is deployed with 1 + 1 redundancy per component at a location and across geographical locations in most cases. In addition, capacity is calculated to accommodate the busy hour of all services and applications, including spikes in traffic for mass event applications (like voting for American Idol), resulting in excess network infrastructure that does not get used at all times. The current architecture is expensive to grow and maintain. Deployment of new network ele- ments and appl