nt implementations. A common challenge that is consistently faced has been the inability to decouple such measure- ment functionality from the network elements. However, we do see several merits to decoupling these measurement functions from network elements, including the ability to build once and apply everywhere across the myriad of products that comprise the network. With the introduction of Network Measurements virtualization technologies across the network, we now have the ability to decouple such measure- ment functions in a cost-effective manner, and distribute them across the network as needed. However, the transition to a more decoupled measurement design ought to be done carefully. The following criteria tests whether it makes sense to decouple a measurement function: 1. Is measurement functionality enhanced? 2. Is cycle time for network feature development improved? 3. Is cost of the network element and measurement function development reduced? 4. Does it offer an opportunity to optimize the measurement functions? 5. Does it provide an opportunity to normalize measurement data to construct a common over- view of the network? 6. Does it have a minimal operational impact? In general, measurement functions that perform the service or network monitoring role more often meet the criteria for decoupling while component measurements targeted for decoupling, need to be evaluated more carefully. We refer to native or embedded measurement functions (e.g., error counts, collection of compo- nent level statistics such as CPU and memory utilization) as organic functions to indicate the inherent coupling to the network element. The functions that do not belong to this class, termed inorganic or synthetic, can be decoupled from the network element and bundled into a separate VM, which we will call SDN-Mon. Examples would include the service and operational measurement instrumenta- tion such as TWAMP [13], CFM [14], and control plane measurements, as shown in Figure 16.9. A sampling of candidates for decoupling, whic