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Agentic AI for Platform Engineering: Rethinking developer platforms with agentic AI, RAG, MCP, and governed autonomous operations
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Agentic AI for Platform Engineering: Rethinking developer platforms with agentic AI, RAG, MCP, and governed autonomous operations
Agentic AI for Platform Engineering: Rethinking developer platforms with agentic AI, RAG, MCP, and governed autonomous operations
제품번호 #: 269853853

Agentic AI for Platform Engineering: Rethinking developer platforms with agentic AI, RAG, MCP, and governed autonomous operations

제품번호 #: 269853853

KRW 84449

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Shop Agentic AI for Platform Engineering: Rethinking developer platforms with agentic AI, RAG, MCP, and governed autonomous operations online at a best price in South Korea. 1806386658
  • Build AI-driven platforms with RAG, MCP, governed agents, and observability, while seeing how Claude Code, Kiro, and Codex CLI fit into the shift from personal coding agents to governed platform agentsKey FeaturesEnd-to-end coverage from AI-enhanced developer portals to governed agentic operationsApply agentic AI patterns for governed remediation, observability, and human-in-the-loop controlGenerate infrastructure-as-code and CI/CD artifacts through conversational AI interfacesBook DescriptionPlatform engineers today face a growing challenge: developer platforms must scale faster than teams can maintain them. This book shows how to embed GenAI, RAG, MCP, and governed agents into developer platforms while preserving delivery and governance practices.The book moves from platform engineering and AIOps foundations to organizational knowledge, conversational interfaces, and agentic operations. Along the way, it places Claude Code, Kiro, and Codex CLI within this evolution, showing how these tools connect to the shift toward governed agents across platforms and organizations. You will build RAG pipelines, connect platform capabilities through MCP, and explore natural-language generation of Terraform and Kubernetes artifacts alongside CI/CD use cases. Hands-on chapters use Backstage, GitOps, Argo CD, Strands, and Langfuse to demonstrate assistants, governed pull-request changes, observability, audit trails, and operational agents.You will also learn when single- or multi-agent designs are appropriate, evaluate build-versus-buy choices, and address prompt injection, memory poisoning, identity abuse, and compliance. By the end, you will be able to design AI-enhanced developer platforms that improve self-service while keeping high-impact actions observable, auditable, and subject to human approval where risk demands it.What you will learnBuild RAG systems grounded in organizational knowledgeBuild governed agents that propose changes through pull requestsConnect conversational workflows to platform tools with MCPExplore where Claude Code and Kiro fit in agentic platform workflowsTrace agent activity and maintain auditable operational recordsSecure agent workflows with guardrails, identity, and compliance controlsCompare personal and production agents with governed tool accessEvaluate build-versus-buy choices for AI platform capabilitiesWho this book is forThis book is for platform engineers, SREs, DevOps professionals, and cloud architects who want to integrate GenAI and agentic AI into internal developer platforms. If you are responsible for building or maintaining internal platforms and want to improve developer self-service, operational intelligence, and governed automation, this book is for you. Technical leaders driving AI adoption within engineering teams will also find valuable strategic guidance. Basic familiarity with cloud computing, infrastructure as code, Kubernetes, CI/CD, and DevOps practices is assumed.Table of ContentsPlatform Engineering and Developer ExperienceAIOps: A Pre- and Post-Platform Engineering PerspectiveFoundation of Generative AI for Platform TeamsDriving Platform Intelligence with Organizational KnowledgeConversational InterfacesAgentic AI and Autonomous BehaviorOperational Agents in ProductionSecurity, Compliance, and GovernanceFuture Directions
Publisher Packt Publishing
Publication date September 30, 2026
Edition 1st
Language English
Print length 268 pages
ISBN-10 1806386658
ISBN-13 978-1806386659
Item Weight 1.03 pounds (470 grams)
Dimensions 7.5 x 0.61 x 9.25 inches (19.1 x 1.5 x 23.5 cm)

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