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Building AI Agents for Network Operations. Design LLM-powered NetOps workflows with Python, Ollama, MCP, and tool calling Sif Baksh

Książka w języku angielskim angielski
Building AI Agents for Network Operations. Design LLM-powered NetOps workflows with Python, Ollama, MCP, and tool calling Sif Baksh - okladka książki

Building AI Agents for Network Operations. Design LLM-powered NetOps workflows with Python, Ollama, MCP, and tool calling Sif Baksh - okladka książki

Building AI Agents for Network Operations. Design LLM-powered NetOps workflows with Python, Ollama, MCP, and tool calling Sif Baksh - audiobook MP3

Building AI Agents for Network Operations. Design LLM-powered NetOps workflows with Python, Ollama, MCP, and tool calling Sif Baksh - audiobook CD

Autor:
Sif Baksh
Wydawnictwo:
Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
226
Dostępne formaty:
     PDF
     ePub

Ebook
116,10 zł 129,00 zł (-10%)
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Do przechowalni

Network troubleshooting is full of clues, but they are often buried in noisy alerts, long CLI output, missing topology context, and incomplete handoffs. Building AI Agents for Network Operations shows how to use AI agents, LLMs, and network automation in a controlled way, so engineers can get clearer evidence without giving up validation or operational control.
You will start with local LLM workflows using Ollama and Python, then use a simple RACE prompt structure to make repeatable NetOps tasks clearer, safer, and easier to review. You will parse interface and BGP output into structured data, build a chatbot that keeps troubleshooting context, and connect the model to approved tools for device status, interfaces, reachability, topology, and BGP health. You will then build an agentic troubleshooting loop, package reusable network tools with MCP, and learn how to evaluate these workflows against logging, approvals, observability, runbooks, feature flags, and read-only pilot readiness.
By the end of this book, you will have a practical path for turning AI ideas into NetOps workflows that can be tested in a lab, reviewed by your team, and adapted toward real-world network operations with the right controls.

O autorze książki

Sif Baksh is a network automation architect, solutions engineer, and technical educator with more than 15 years of experience across networking, security, infrastructure, and automation. His work focuses on helping engineering teams build governed workflows that connect network data, infrastructure APIs, operational tools, and human approvals into systems that are practical, observable, and safe to operate.
His technical background includes DNS/DHCP/IPAM automation, network and security operations, threat intelligence enrichment, compliance workflows, incident response, and tool integration. He has worked with teams to replace manual, ticket-driven processes with repeatable automation patterns designed for production environments.
His current work explores how AI agents, local LLMs, prompt design, tool calling, MCP servers, and agentic troubleshooting loops can be applied to network operations without losing validation or control. Through his writing, workshops, videos, and community projects, he teaches engineers how to turn AI ideas into NetOps workflows that can be tested, reviewed, and trusted.

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