Nokia's Steven Butler joins Heavy Networking to discuss how their event-driven automation (EDA) platform supports AI Ops by focusing on multi-vendor abstractions, consistent data models, extensibility, and digital twin capabilities. A key element of EDA is its abstraction layer, which normalizes configuration and state across different network operating systems, providing AI tools with the necessary context to understand network health. The discussion highlights the importance of well-defined and extensible schemas for AI to effectively interpret data and utilize various network tools. EDA's architecture allows users to create custom apps and workflows, enhancing AI's ability to troubleshoot and manage networks, and the platform's digital twin feature enables validation of AI-driven configuration changes before deployment.
Part 1: Introduction, Multi-Vendor Strategy
Part 2: Data Models, Schemas, AI Integration
Part 3: Architecture, Modularity, Extensibility
Part 4: Ecosystem, Digital Twins, Conclusion
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