Enhancing Network Automation with Generative AI
Generative AI has many new capabilities, but few engineers have integrated those features into existing network automation solutions. This course will teach you how to do exactly that using a realistic use-case.
What you'll learn
This course cuts through today's hype surrounding generative AI by tying the output from the large language models (LLMs) into a complex network automation workflow. In this course, Enhancing Network Automation with Generative AI, you’ll learn to make intelligent requests of your generative AI model, then receive precise and accurate answers. First, you'll discover how to ask generative AI to convert network device configurations across vendors. Next, you’ll explore the power of post-AI/pre-deployment validation by combining off-line tools like pytest and batfish to catch obvious mistakes made by generative AI before deployment. Finally, you'll learn how to programmatically deploy network topologies and subsequently test them using an innovative combination of Python, GNS3, scrapli, textFSM, and asyncio. When you’re finished with this course, you’ll have the skills and knowledge of automation-oriented generative AI needed to solve specific business problems relating to network configuration, troubleshooting, deployment, and validation.
Table of contents
- What Is LLM Fine-tuning? 3m
- Demo: Training a Finely-tuned LLM 6m
- Demo: Method #4 Using Model Fine-tuning 4m
- Measuring Text Relatedness with Embeddings 2m
- Demo: Generating Embeddings for CLI Commands 7m
- Demo: Mapping Related CLI Commands 4m
- Demo: Method #5 Using Embedding-based Context 4m
- Module Review 1m
- Validating Offline Topologies with Batfish 2m
- Demo: Installing Docker and Deploying Batfish 3m
- Demo: Batfish API Reference and Basic Tests 8m
- Demo: Validating Interface Descriptions and OSPF Cost Values 6m
- Demo: Testing for the Presence or Absence of OSPF Routes 8m
- Demo: Simulating Unidirectional Traceroute Probes 5m
- Demo: Serializing the Network Topology into JSON 7m
- Module Review 1m
- Modeling Virtual Topologies with GNS3 3m
- Demo: GNS3 User Interface and API Reference 4m
- Demo: Loading and Refining the JSON Topology 4m
- Demo: Mapping the Device-specific Templates 3m
- Demo: Creating Projects and Nodes 6m
- Demo: Linking the Nodes via the JSON Topology 3m
- Demo: Starting the Nodes 5m
- Module Review 1m
About the author
Nicholas (Nick) Russo, CCDE #20160041 and CCIE #42518, is an internationally recognized expert in IP/MPLS networking and design. To grow his skillset, Nick has been focused advancing Network DevOps via automation for his clients. Recently, Nick has been sharing his knowledge through online video training and speaking at industry conferences. Nick also holds a Bachelor's of Science in Computer Science from the Rochester Institute of Technology (RIT). Nick lives in Maryland, USA with his wife, Car... more