Struggling With Network Automation? Here’s Your Roadmap

AIOps, or Artificial Intelligence for IT Operations, is an appealing concept where AI agents autonomously manage and optimize network operations, yet its practical implementation faces significant challenges. Current AI agents often malfunction unless tasked with highly specific duties, causing skepticism and reluctance to deploy them in production environments. This mirrors past experiences with network automation, where rushed implementations led to fragmented solutions due to poor foundational planning. A successful approach involves modeling intent, structuring data, and prioritizing automation only after establishing a robust foundation. The Network Automation Framework (NAF) offers a blueprint for scalable, reliable network automation, emphasizing six foundational elements: intent, executor, observability, collector, orchestrator, and presentation. These elements support a structured, tool-agnostic, and continuously updated framework that is accessible to various stakeholders, not just network engineers. The NAF Framework provides a systematic approach to network automation, enabling seamless integration of AI while ensuring reliability and scalability through thorough planning and execution.