BUSINESS DRIVER
Executive Summary - Data driven placement and monitoring of workloads and infrastructure require AI based big data analytics. To support multiple edges, federated learning, it is required to deploy anlalytics packages at multiple locations. This project intends to simplify deployment and automation of big data framework at multiple locations, thereby reducing the analytics deployment from weeks to hours.
Business Impact - Simplify operations and separate out analytics framework from analytics applications, which allows multiple data scientist organization to deploy training/predictions applications without worrying about on how analytics framework is deployed and managed.
Business Markets - Applicable to physical and virtual network functions deployed in large operational networks - cellular service (4G/5G), cloud service and data center networks.
Funding/Financial Impacts - Potential of significantly reducing the CAPEX
Organization Mgmt, Sales Strategies - There is no additional organizational management or sales strategies for this use case outside of a service providers "normal" ONAP deployment and its attendant organizational resources from a service provider.
DEVELOPMENT IMPACTS
PROJECT | PTL | User Story / Epic | Requirement |
A&AI | |||
AAF | |||
APPC | |||
CLAMP | |||
CC-SDK | |||
DCAE | |||
DMaaP | |||
External API | |||
MODELING | |||
Multi-VIM / Cloud | |||
OOF | |||
POLICY | |||
PORTAL | |||
SDN-C | |||
SDC | |||
SO | |||
VID | |||
VNFRQTS | |||
VNF-SDK | |||
CDS |
List of PTLs:Approved Projects
Technical Debt
Features that would make it in for R4
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