IG1219A AI Closed Loop Automation Management v1.1.0

In this project asset, the information blueprint for Closed Loop Automation (section 6) extends similar implementation of ONAP CLAMP with the inclusion of Intelligence Management across Engagement, Party, Production and Core Commerce management Function blocks of the Open Digital Architecture (ODA). This is based on Closed Loop Anomaly Detection and Resolution Automation (CLADRA) logical architecture and the Autonomous Network business architecture. Application of the information model and architecture blueprint cuts across all verticals of the Business Process Framework (aka eTOM), with existing use cases contributed focusing on realized solution in the Assurance vertical of eTOM.

AI Closed Loop Automation Management (AI-CLAM) in section 8.1.2 is a blueprint that presents the components, defined from the capabilities in section 7 for a solution architect to automate intelligently. With AI, Closed Loop Automation (CLA) ensures that solutions like autonomic systems (AS), autonomous networks (AN), self-driving cars etc., can interact with their environments based on well established requirements and goals. This is important to realize higher benefits of automation with paired with user, business and operational performance targets.

Occurrences such as faults, congestion, human error, waste etc. can be effectively mitigated with AI and CLAM. Closed loops can provide needed data or events to enable design, develop and operate “automated solutions” so that can adjust and optimize their performance towards meeting user and business expectations (through a model that facilitates well-defined requirements and metrics – refer to Intent in Autonomous Networks.

With next generation data centers and platforms anticipating explosion in connected experiences, digital services, new platforms and new networks (5G, Wi-Fi 6 etc.), service providers require new capabilities to manage digital at speed and scale. This need must factor in more importantly, the ‘unknown unknowns’ which are presented by automated systems interacting with the environment. AI capabilities will be required to enable learn, capture feedback and manage CLA solutions using a model like observe, orient, decide and act (section 5.2.1) in order to effectively manage “normal” and “abnormal” patterns.

AI Closed Loop Automation Management Platform (AI-CLAMP) thus provides the solution framework (in section 8.1.1) that realizes user-centricity and business outcomes. It provides the ability to choreograph components and the activities they support, component interaction through interfaces, and managing intelligence that brings all these together in a continuum.