duced, transformed, aggregated, etc.) to the core data lake for other analyses. Open DCAE is configured by the controller SO that software- defined storage can be instantiated at different AIC cloud zones on an as-needed basis. 8.3.2.4 Analytics Framework The analytics framework is an open ecosystem that is capable of onboarding MSs that are developed by analytics developers, data scientists, VNF analytics solution engineers, and business analysts. This concept is key for driving wide adoption of analytics in the Network Cloud, addressing trouble- shooting, service quality management, and DevOps. The open ecosystem would need to support a full spectrum of analytics capabilities: Descriptive analytics (what is happening) Diagnostic analytics (why did it happen) Predictive analytics (what is likely to happen) Prescriptive analytics (what should I do about it) Exploratory analytics (what can I learn from the data and how do I use it to drive value to the business) The analytics framework provides access to production data sources and enables automatic test- ing and certification of MSs. The framework includes APIs to Expose a catalog of analytics MSs and/or applications to SDC Support publishing and dynamic instantiation of those MSs and/or applications Support interfaces with the base DCAE analytics framework (runtime, service based, pluggable) Allow publishing and maintenance of the DCAE data catalog A runtime DCAE analytics platform for building, testing, and deploying batch and real- time streaming data solutions on Hadoop. In addition, the following key enablers will be addressed: Building the Network of the Future An initial set of core MSs to jumpstart developers in using the framework Adaptors or modules (or flowlets in the Cask Data Application Platform [CDAP] parlance [CDAP16]) for common functions (e.g., reading records from the DCAE RDBMS) Criteria for defining the minimal set of interface (aka API) parameters necessary to enable orchestration A specification of what requirements a developer must meet to