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The collection layer supports both real-time streaming and batch collection.
Data Movement
This component facilitates the movement of messages and data between various publishers and interested subscribers. While a key component within DCAE, this is also the component that enables data movement between various OpenECOMP components.
Edge and Central Lake
DCAE supports a variety of applications and use cases. These range from real-time applications that have stringent latency requirements to other analytic applications that have a need to process a range of unstructured and structured data. The DCAE storage lake supports these needs and is scalable so that new storage technologies can be incorporated as they become available. The storage lake uses big-data storage technologies such as in-memory repositories and support for raw, structured, unstructured and semi-structured data to accommodate a broad scope of requirements such as large volume, velocity, and variety.
While there may be detailed data retained at the DCAE edge layer for detailed analysis and trouble-shooting, applications should optimize the use of bandwidth and storage resources by propagating only the required data (for example, reduced, transformed, or aggregated) to the core data lake for other analyses.
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Analytic Framework
Analytics and related applications run in the Analytic Framework of DCAE. The Analytic Framework enables agile development of analytic applications. This framework supports creation of applications that process data from multiple streams and sources. Applications can be real-time – for example, analytics, anomaly detection, capacity monitoring, congestion monitoring, or alarm correlation – or non-real time, such as applications that perform analytics on previously collected data or forward synthesized, aggregated or transformed data to big data stores and other applications. The framework can process both real-time streams of data and data collected through traditional batch methods. Analytic applications are managed by the DCAE controller.
Analytic Applications
The following list provides examples of types of applications that can be built on top of DCAE:
Analytics These will be the most commonapplications that are processing collected data and deriving interesting metrics or analytics for use by other applications. These analytics applications range from very simple ones (from a single source of data) that compute usage, utilization, latency, and similar metrics to very complex ones that detect specific conditions based on data collected from various sources. The analytics could be capacity indicators used to adjust resources or could be performance indicators pointing to anomalous conditions requiring response.
Fault / event correlation: This is a key application type that processes events and thresholds published by managed resources or other applications that detect specific conditions. Based on defined rules, policies, known signatures and other knowledge about the network or service behavior, an application of this kind would determine root cause for various conditions and notify other interested applications.
Performance surveillance and visualization: Thisclass of application provides a window to an operations organization notifying them of network and service conditions. The notifications could include outages and impacted services or customers based on various dimensions of interest. They provide visual aids ranging from geographic dashboards to virtual information model browsers to detailed drilldown to specific service or customer impacts.
Capacity planning: This class of application providesplanners and engineers the ability to adjust forecasts based on observed demands as well as plan specific capacity augments at various levels, e.g., NFVI level (technical plant, racks, clusters, etc.), Network level (bandwidth, circuits, etc.), Service or Customer levels.
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