How do I enable AI operations using the TM Forum Framework across production and deployment?
Understand AIOPs, your readiness and requirements for redesigning processes for automating management within a large scale AI environment whilst maintaining and eventually retiring existing production flows
Watch the AIOPs Masterclass
Understand how you can exploit the full potential of AI using the TM Forum AIOps Service Management Framework
Enabling AIOps to deliver true operational transformation and new services
Redesign the complex service management operations
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.
IG1190 AIOps Service Management v5.4.0
Redesign and re-engineer your AIOps Configuration Management
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.
IG1190A AIOps Configuration Management
Update your Change Management Processes to ensure they support AI
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.
IG1190B AIOps Change Management
From Development to Production establish how to integrate new and updated AI-driven component
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.
IG1190C AIOps Release Management v2.0.0
Approve the readiness and acceptance of the new software for the final delivery and roll-out into the Production environment
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.
IG1190D AIOps Acceptance Testing v2.0.0
Update your Knowledge Management Processes to enable AI models to be new active players in the Knowledge Management Process
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.
IG1190E AIOps Knowledge Management v1.0.1
Redesign your Monitoring and Event Management Processes
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.
IG1190F AIOps Monitoring and Event Management v1.0.1
Automatically and Proactively manage your Incidents
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
IG1190G AIOps Incident Management v2.0.0
Deploy the AIOps Problem Management processes
Address the challenges of large-scale AI software in Production
IG1190H AIOps Problem Management v2.0.0
Implement the AIOps Application Maintenance Processes
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.
IG1190I AIOps Application Maintenance v2.0.0
Data management for AI components deployed at a significant scale (AIDataOps).
Understand how to deploy, monitor, maintain and eventually decommission (retire) data and the corresponding data flows in Production
IG1190J AI DataOps Management v3.0.0
Objectives and approaches to achieving the Autonomous Network with 5G network assurance, improved customer experience and sustainability
The progressive evolution of CSPs to the digital operators of the future. From simple automation to self governing autonomous networks
How the Automated, Actively Assured Service Lifecycle will be extremely important to Assuring Service Quality in Cloud and 5G Era