ications requires additional hardware, which must be individually architected and planned prior to deployment. This process can take months. Capacity expansion requires deploying additional dedicated compute resources. This takes careful planning and execution, and additional dedicated capital specifically for each application (not sharable) well in advance of demand. The current architecture requires every interface to be defined, with every IP address statically allocated, as a means of implementing access control. Any changes, upgrades, etc. may require reworking the IP allocation and associated security rules, which can be time-consuming, error prone, and costly. Each application is designed for specific equipment types. Equipment end-of-life issues can cause problems for capacity expansion, since the same hardware model as originally designed can no longer be purchased. If a new hardware model is used, the network element/appli- cation infrastructure may need to be redesigned. With dedicated hardware, maintenance can be an issue since applications cannot be moved from the hardware instance. Maintenance will often require service downtime. With the current state of virtualization technology and cloud infrastructures, the signaling plane is well suited for virtualization. Although virtualization adds some processing overhead, the perfor- mance for signaling elements is acceptable. The ability to provide guaranteed network bandwidth on a per-virtual machine (VM) basis is critical to ensure that end-to-end signaling latencies are not impacted. Performance is a key consideration for virtualizing the media plane. The vSwitch in the hypervisor is a bottleneck for i/o processing. Various I/O optimization techniques (SR-IOV [single root input/output virtualization], faster vSwitches, Intel Data Plane Development Kit [DPDK] APIs, CPU pinning, etc.) are being considered to close this gap. Virtualization needs to be cost effective for some media functions such as transcoding for a large number of users to replace the sp