How do I enable AI operations using the TM Forum Framework across production and deployment?

Understand how you can exploit the full potential of AI using the TM Forum AIOps Service Management Framework

The TM Forum work stream “AIOps – Redesigning Operations Processes” has been set up to explore the challenge of redesigning and re-engineering the CSPs operations management processes to support and govern massive deployment of AI.

In this report, a summary of the best practice’s contribution from CSPs, Network Equipment Vendors, IT Vendors, and Consulting & Systems Integrators is key to identify the components required for CLA in the Service and Resource domains of eTOM.

In AIOps, the existing practices are challenged as AI models may evolve and change autonomously and unpredictably when they are in Production bypassing the change controls that have been put in place for traditional software.

In AIOps, in addition to the traditional process above, which is still valid and applicable to changes flowing from Development to Production, we also have the reverse scenario, as AI online components may autonomously change their state in Production and those changes may generate diffuse impacts that need to be managed retrospectively.

Focus on the tests performed at the Deployment stage where we usually go through a final set of tests in order to verify and approve the readiness and acceptance of the new software for the final delivery and roll-out into the Production environment.

The deployment of AI models in Production challenges the existing Knowledge Management practices as the AI models themselves may be new active players in the Knowledge Management process, becoming producers and consumers of knowledge.

Implement an automatic early detection and resolution of incidents, filter and correlate events and ensure the integration with other service management processes and trigger the responses to related event.

With the AIOPs Incident Management processes to restore the service to end users/customers and recover to normal service operations as quickly as possible and in line with agreed SLAs

Address the challenges of large-scale AI software in Production

Automatically detect and resolove of incidents, filter and correlate events and ensure the integration with other service management processes and trigger the responses to related event.

Understand how to deploy, monitor, maintain and eventually decommission (retire) data and the corresponding data flows in Production