Packt.Publishing.-.Building.AI.Agents.For.Network.Operations.2026.RETAIL.EPUB.eBook-CTO

Section
eBooks/Audiobooks
Group
CTO
Size
25,74 MB
Files
5
Date
2026-08-09

NFO

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                                Packt Publishing
                                   Sif Baksh
                   Building AI Agents For Network Operations
                                      N/A
                                      2026
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      Publisher > Packt Publishing
      Author    > Sif Baksh
      Title     > Building AI Agents For Network Operations
      Issue     > N/A
      Year      > 2026
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      ISBN      > 9781808346835
      Pages     > 235
      Genre     > Nonfiction Computers
      Language  > English
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      Type      > RETAIL
      Media     > TECH
      Format    > .epub
      Section   > eBook
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      Published > 2026-07
      Release   > 2026-08-09
      Disks     > 03 x 10 MB
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                 -  - --   [ D E S C R I P T I O N ]   -- -  -
   Build AI-assisted network troubleshooting workflows that parse CLI output,  
     call approved tools, use MCP, and keep evidence visible for review Key    
    Features Build local LLM workflows for NetOps using Python, Ollama, and    
   validated CLI data Create troubleshooting agents that use memory, approved  
   tools, and clear evidence Package reusable network tools with MCP and plan  
    controlled read-only pilots Book Description 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. What you will learn Run local LLM workflows with   
    Ollama and Python Shape reliable NetOps prompts using RACE Parse CLI and   
          BGP output into structured JSON Build chatbots that remember         
   troubleshooting context Connect AI agents to approved network tools Create  
  evidence-based troubleshooting loops Expose reusable network tools with MCP  
   Plan read-only pilots with safety controls Who this book is for This book   
    is for network engineers, NetOps engineers, NOC engineers, SREs, DevOps    
    engineers, and network automation professionals who want to apply AI to    
        troubleshooting without losing control. Basic networking and CLI       
    familiarity will help, beginner Python knowledge is useful for following   
                                   the labs.                                   
                  -  - --   [ R E T A I L   U R L ]   -- -  -                  
   https://www.kobo.com/us/en/ebook/building-ai-agents-for-network-operations  
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