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The DCAE Platform consists of several components: Common Collection Framework, Data Movement, Edge and Central Lake, Analytic Framework, and Analytic Applications.
Common Collection Framework
The collection layer provides the various data collectors that are needed to collect the instrumentation that is available from the cloud infrastructure. Included are both physical and virtual elements. For example, collection of the following types of data is supported:
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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.
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:
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