g between IP and Optical Layers Using ROADMs 16.2.5 Use of Available Spare Capacity to Offer Bandwidth Calendaring Service 16.3 Network Capacity Planning 16.3.1 Current Network Capacity Planning Process 16.3.2 Highlights of Benefits from SDN 16.3.3 Traffic Matrix Data 16.3.4 Traffic Forecast 16.3.5 Wavelength Circuits 16.3.6 Layer 0 and Layer 3 Resources 16.4 SDN Controller Measurement Framework 16.4.1 Objectives for a Measurement Framework 16.4.2 Measurement Framework Overview 16.4.3 Component-Level Measurements 16.4.4 Service and Network Measurements 16.4.5 The Case for Decoupling Service and Network Path Measurements from Network Elements 16.5 AT&T's SDN-Mon Framework 16.5.1 Network Deployment Example for the SDN-Mon Framework 16.6 Telemetry Measurements 16.7 NFV Data and Measurements 16.7.1 NFV Data Model 16.7.2 NFV Infrastructure Telemetry Data Model 16.7.2.1 OpenStack Telemetry Service: Ceilometer 16.7.2.2 OpenStack Telemetry Service: Ceilometer Examples 16.8 NFV Data Measurement Framework 16.8.1 Organic NFV Data Measurement Model 16.8.2 Passive vProbe Measurement Data Model 16.8.3 Active vProbe Measurements Data Model 16.9 VNF Reporting Metrics 16.9.1 VNF Resource Consumption and Operational Metrics 16.9.2 VNF SLAs and KPI 16.9.3 VNF Resiliency Reporting 16.10 VNF Scaling Measurements 16.10.1 NFV Service Auto-Scaling 16.10.2 Scaling Triggers 16.10.3 Scale Out: Illustrative Example Building the Network of the Future 16.11 VNF Efficiency Measurements and KCI Reporting 16.12 VNF Measurements for Optimal Placement and Sizing 16.13 Areas for Further Study Acknowledgments References Software-defined networking (SDN) and NFV present many new challenges to the traditional oper- ator model of operating services. VNFs are instantiated based on resource demands and the SDN- controlled logical connections used to connect services move dynamically based on utilization, policy, and resiliency designs. SDN and NFV data models have to enable measurements that ensure parity with the legacy service data models while adding 