Build Intelligent Networks with AI

Ready to supercharge your networking career with AI?

Step into the future of network engineering in this hands-on workshop where artificial intelligence meets automation, observability, and real-world infrastructure. In just four hours, you’ll learn how to turn AI from a buzzword into a practical tool that accelerates your workflows, improves troubleshooting, and boosts efficiency.

With live instruction and guided labs using Arista cEOS, Containerlab, and open-source AI tools, you’ll gain practical experience building intelligent systems that help you automate, analyze, and operate smarter. This is not theory; it’s real, applied learning designed for network engineers who want to see instant results.

Whether you are building AI-assisted playbooks, connecting LLMs to your network with the Model Context Protocol (MCP), or deploying AI-powered monitoring systems, this session gives you the knowledge and hands-on practice to bring AI into your daily operations.

Transform the way you build, monitor, and manage networks with the power of AI.

Who Is This Workshop For

This workshop is designed for network professionals who want to bring the power of AI into their daily workflows. It’s perfect for those ready to move beyond theory and apply AI to real-world network operations using open-source tools and live lab environments.

Who Should Attend

• Network Engineers and Architects with 3 to 10 years of experience who want to modernize their approach to automation and observability.

• Automation and DevOps Engineers familiar with CLI, Ansible, or Git who are ready to experiment with AI copilots for faster, smarter development.

• Operations and Platform Teams seeking to deploy AI-powered monitoring, alert summarization, and troubleshooting solutions.

• Technical Leads and Infrastructure Managers guiding network or automation projects who want to understand the capabilities and limitations of AI-driven operations.

After This Workshop, You Will Have

• The ability to design, deploy, and validate automation playbooks up to five times faster using AI copilots while maintaining accuracy and version control.

• A working Model Context Protocol (MCP) server that connects LLMs to network devices, enabling intelligent, context-aware automation.

• Hands-on experience building AI-powered observability systems that summarize alerts, analyze logs, and suggest remediation actions.

• The skills to troubleshoot, test, and validate AI-generated configurations in real lab environments using Arista cEOS and Containerlab.

• A deep understanding of when to use AI and when to rely on traditional automation, helping you make confident, production-ready decisions.

• Practical exposure to open-source tools like Ansible, Python, Prometheus, Grafana, and Sherlog for end-to-end network automation.

• A repeatable, real-world workflow for integrating AI copilots and LLM-driven agents into your daily network engineering tasks.

What You Will Learn

• Understand LLM fundamentals through network-based analogies.

• Use AI tools such as ChatGPT, Claude, and GitHub Copilot to create and validate automation playbooks.

• Build a custom Model Context Protocol (MCP) server to connect AI models securely with network devices.

• Design an AI-powered monitoring stack with Prometheus, Grafana, and Sherlog for smarter alerting and analysis.

• Implement agentic AI workflows for multi-step network automation.