ead to resource scaling, configuration changes, other activities, as well as faults and performance degradations that require healing. The collected data and computed analytics are stored for persistence as well as use by other applications for business and operations (e.g., billing and ticketing). More importantly, DCAE has to perform a lot of these functions in real time. One of the key design patterns expected of this component is to realize the following: "Collect Data Analyze and Correlate Detect Anomalies Publish need for Action" This pattern will take various forms and be realized at multiple layers (e.g., infrastructure, net- work, and service). The data are collected once and made available to multiple applications (net- work operators, vendors, partners, and others) for consumption. Applications supporting various operational and business functions are key consumers of the data and events made available by DCAE. DCAE is an open analytic framework, allowing network operators to be able to extend and enhance their capabilities, alter behavior and modify scale, supporting the evolution of the various network functions that are virtualized over time. 7.6.1 DCAE's FOUR MAJOR COMPONENTS Analytics framework-a data development and processing platform with a catalog of micro-services-stand-alone policy-enabled, elementary analytics functions that support structured and unstructured data processing. 2. Collection framework-a set of streaming and batch collectors that support virtualized network, device, and infrastructure data. 3. Data distribution bus-It enables different components within DCAE and ONAP to pub- lish and subscribe to data as well as move data from the edge of the network downstream for processing. 4. Persistence storage framework-a data-storage platform for short- and long-term consumption. Besides these four components, DCAE includes an orchestrator and a set of controllers that man- age the data bus and micro-services and interprets different service designs and workflows. DCAE, commonly referr