bution bus-this is the blood stream of the platform. It enables components within and outside the platform to publish and subscribe to data as well as to move data from the edge of the network downstream for processing. 4. Persistence storage and compute framework-a multitiered data-storage platform for short- and long-term consumption, as well as a distributed computing environment for supporting streaming and batch analytics. Besides these four components, the platform would need to have a controller system to auto- mate many of the operational and services configurations of the MSs and platform resources. More details on this platform are covered in Chapter 7. 8.3.1 DATA COLLECTION, ANALYTICS, AND EVENTS Figure 8.10 depicts a high-level conceptual view of data collection, analytics, and events (DCAE)-a big data platform within ONAP (see Chapter 7). DCAE, which is commonly referred to as "Open DCAE," adopts an open source philosophy. It fosters a data marketplace and micro-services of collectors and analytics functions. With this approach, we can create a secure ecosystem where developers, third-party providers, data scientists, and engineers can contribute to the platform. The Building the Network of the Future Edge Processing Central Processing Core Processing Analytics Analytics Analytics Collectors Collectors Collectors Policy Policy Policy Storage Storage Storage Compute Compute Compute FIGURE 8.10 A platform approach to analytics applications in the Network Cloud. platform also supports analytics, collections, policy enablement, compute and storage at the edge (local cloud zones distributed across the country), central (limited large-scale regional cloud zones), and core (core data lakes enabling batch-mode processing) of the network. Given this distributed design, we can optimize compute, data distribution, and storage resources to achieve desirable scale, performance, reliability, and cost efficiencies. Open DCAE enables intelligent services to be dynamically instantiated or updated automati- cally. By 