AI Networking Cookbook
by Eric Chou;
English | 2025 | ISBN: 1805807994 | 346 pages | True EPUB | 7.57 MB
Transform your network operations with AI-powered automation, and learn code generation, prompt engineering, and practical recipes for building custom network tools using AI assistants and Python
Key Features
Leverage AI assistants like OpenAI and Claude to build network automation solutions
Use prompt engineering and AI tools to automate network setup, monitoring, and threat detection
Build AI-assisted network configuration, monitoring, and management workflows with multi-vendor APIs
Purchase of the print or Kindle book includes a free PDF eBook
Book Description
Transform your approach to network automation with the power of AI LLM assistants guided by hands-on recipes for building custom automation solutions quickly using artificial intelligence.
You'll learn tools and techniques such as Vibe coding for conversational development, OpenAI API scripts, prompt engineering for better outputs, local LLM fine-tuning, combining models with LangChain, and Streamlit-based frontends development. The book progresses from simple Python scripts to advanced AI-assisted automation techniques, including multi-vendor API integration, showing you how AI can enhance network configuration, monitoring, security, and troubleshooting.
Each recipe presents realistic mock data, complete code examples, and step-by-step guidance, creating a safe environment for experimentation while building a solid foundation for future production use. Whether you want to automate routine configuration, implement AI-driven troubleshooting, or build compliance monitoring systems, this cookbook helps you connect your networking expertise with the capabilities of modern AI.
What you will learn
Understand the AI LLM landscape and key parameters for networking tasks
Create OpenAI-enabled scripts for daily network engineering workflows
Master prompt engineering techniques for improved AI outputs
Build local LLMs using Ollama for network applications
Chain language models with LangChain for complex network solutions
Develop AI application frontends using the Streamlit framework
Design robust backends for network AI applications
Build an end-to-end network copilot by integrating all the techniques you've learned
Who this book is for
The AI for Networking Cookbook is for experienced network engineers, network architects, and DevOps professionals who want to enhance their network automation capabilities using AI and LLM technologies. It is especially invaluable for networking professionals looking to integrate conversational AI development, prompt engineering, and modern AI tools like OpenAI APIs, LangChain, and local LLM models into their workflows.
Familiarity with basic networking concepts, configurations, and Python is helpful, but no prior AI or advanced programming experience is required.
Table of Contents
The AI LLM Landscape and Key Parameters
OpenAI Recipes for Network Engineers
Prompt Engineering for Reliable Outputs
Local AI LLM Playground in Network Engineering
LangChain for Networking Tasks
Building an AI LLM Network Application Frontend with Streamlit
Building AI LLM Application Backends
Building a Network Co-Pilot
Network Monitoring and Performance Use Cases with MCP
Network Security through Vibe Coding
Links are Interchangeable - Single Extraction
