o make decisions, where these decisions will often be conditional upon the current situation. A major example of this approach is the feedback/control loop pattern driven by DCAE. Many specific control loops can be defined. In a particular control loop, each participant (e.g., orchestra- tor, controller, DCAE, VF) will have received policies determining how it should act as part of that loop. All of the policies for that loop will have been previously created together, ensuring proper coordinated closed-loop action. DCAE can receive specific policies for data collection (e.g., what data to collect, how to collect, and how often), data analysis (e.g., what type and depth of analysis to perform), and signature and event publishing (e.g., what analysis results to look for as well as the specifics of the event to be published upon detecting those results). Remaining components of the loop (e.g., orchestrators, controllers, etc.) can receive specific policies determining actions to be taken upon receiving the triggered event from DCAE. Each loop participant could also receive poli- cies determining the specific events to which it subscribes. 7.8 ACTIVE AND AVAILABLE INVENTORY (A&AI) SYSTEM A&AI is the ONAP component that provides real-time views of the network cloud resources, services, products, and customer information virtual network services. Figure 7.13 provides a functional view of A&AI. The views provided by A&AI relate data managed by multiple ONAP, BSS, OSS, and network applications to form a "top to bottom" view, ranging from the products customers buy to the services and resources used to compose the products. A&AI not only forms a registry of products, services, and resources, but also maintains up-to-date views of the rela- tionships between these inventory items across their lifecycles. To deliver the vision of a dynamic, fungible network cloud, A&AI will manage these multidimensional relationships in real time. A&AI maintains real-time inventory and topology data by being continually updated as changes 