From Reliable to Self-Optimizing: An AIOps Roadmap for Data Center Networking
The Nokia data center network migration is done; the opportunity starts now. Building on the Futurum Research and Nokia Bell Labs’ model this webinar outlines a pragmatic AIOps journey for data center networking and operations. Using Nokia’s own data transformation project as our model, we’ll discuss how next-gen infrastructure integrates with existing tooling to create measurable outcomes With these experiences, and insights from a panel of experts, our focus will be on the data center networking for the future, grounded in the real experiences of today.
With Nokia’s migration complete—achieving five-nines availability, an ~80% incident reduction, and projecting multi-million dollar OPEX reductions—the focus now shifts from stabilization to acceleration. The automation fabric gives the Nokia IT team a launching pad for more autonomous operations: digital twins that validate every intent before deployment, event-driven automation that executes 90% of changes without human intervention, and AI-assisted telemetry that reduces MTTR by correlating logs, metrics, and alarms into actionable “event stories.”
This webinar looks forward to what comes next: How enterprises can evolve toward self-optimizing networks, adopt closed-loop AIOps, converge ITSM + NetOps pipelines, and define the feature requirements that will shape the next generation of enterprise-scale data center operations.
Key Takeaways:
An actionable AIOps roadmap: How to move from “post-migration steady state” to a self-optimizing network.
Digital twin as the new change gate: A concrete pattern for using twins so more changes are safe, smaller, and faster without expanding maintenance windows.
Day-2+ operations that measure themselves: Practical KPIs and how modern infrastructure integrations with existing ITSM and NetOps tools make those metrics visible and continuously improving.
The “what’s next” feature asks for enterprise scale. Topics include: richer app/service context, policy-driven SLO guardrails, multi-site service intent, and AI recommendations that help engineers move from hunting to deciding.
