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AI Platform Engineering with MCP Servers: Architect Context-Aware Agent Systems with Observability, Compliance, and Vendor-Neutral Design - Tapa blanda
Sinopsis
AI Platform Engineering with MCP Servers: Architect Context-Aware Agent Systems with Observability, Compliance, and Vendor-Neutral Design
Your AI agents work in staging. They break in production. Context leaks. Costs spike. Logs tell you nothing useful. Compliance teams start asking hard questions. Vendor lock-in quietly tightens its grip.
Modern AI systems are not just prompts and APIs. They are distributed, stateful, compliance-sensitive platforms that must scale under pressure. If you are building LLM-powered tools without platform-grade architecture, you are gambling with reliability, security, and long-term flexibility.
AI Platform Engineering with MCP Servers delivers a practical blueprint for building context-aware agent systems that behave predictably in real-world environments. This book shows how to design MCP server architectures that separate model logic from orchestration, enforce observability from day one, and maintain vendor-neutral portability across model providers and infrastructure stacks.
You will learn how to:
Design context pipelines that prevent drift and control token costs
Implement structured world-state management for deterministic agents
Add production-grade observability, tracing, and performance metrics
Enforce policy, auditability, and compliance boundaries at the platform layer
Avoid vendor lock-in through abstraction and protocol-driven design
Scale multi-agent workflows without losing control of reasoning paths
Why do most AI projects fail after proof-of-concept? Because they treat AI like a feature instead of a platform. This book shows you how to engineer it properly.
If you are an AI platform engineer, enterprise architect, or senior developer responsible for reliability and governance, this is your operational manual.
Build systems that think clearly. Operate transparently. Scale responsibly.
Get your copy today and start engineering AI the way production demands.
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AI Platform Engineering with MCP Servers: Architect Context-Aware Agent Systems with Observability, Compliance, and Vendor-Neutral Design
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AI Platform Engineering with MCP Servers (Paperback)
Impresión bajo demandaLibrería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
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Paperback. Condición: new. Paperback. AI Platform Engineering with MCP Servers: Architect Context-Aware Agent Systems with Observability, Compliance, and Vendor-Neutral DesignYour AI agents work in staging. They break in production. Context leaks. Costs spike. Logs tell you nothing useful. Compliance teams start asking hard questions. Vendor lock-in quietly tightens its grip.Modern AI systems are not just prompts and APIs. They are distributed, stateful, compliance-sensitive platforms that must scale under pressure. If you are building LLM-powered tools without platform-grade architecture, you are gambling with reliability, security, and long-term flexibility.AI Platform Engineering with MCP Servers delivers a practical blueprint for building context-aware agent systems that behave predictably in real-world environments. This book shows how to design MCP server architectures that separate model logic from orchestration, enforce observability from day one, and maintain vendor-neutral portability across model providers and infrastructure stacks.You will learn how to: Design context pipelines that prevent drift and control token costsImplement structured world-state management for deterministic agentsAdd production-grade observability, tracing, and performance metricsEnforce policy, auditability, and compliance boundaries at the platform layerAvoid vendor lock-in through abstraction and protocol-driven designScale multi-agent workflows without losing control of reasoning pathsWhy do most AI projects fail after proof-of-concept? Because they treat AI like a feature instead of a platform. This book shows you how to engineer it properly.If you are an AI platform engineer, enterprise architect, or senior developer responsible for reliability and governance, this is your operational manual.Build systems that think clearly. Operate transparently. Scale responsibly.Get your copy today and start engineering AI the way production demands. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9798250289740
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AI Platform Engineering with MCP Servers (Paperback)
Impresión bajo demandaLibrería: CitiRetail, Stevenage, Reino Unido
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Paperback. Condición: new. Paperback. AI Platform Engineering with MCP Servers: Architect Context-Aware Agent Systems with Observability, Compliance, and Vendor-Neutral DesignYour AI agents work in staging. They break in production. Context leaks. Costs spike. Logs tell you nothing useful. Compliance teams start asking hard questions. Vendor lock-in quietly tightens its grip.Modern AI systems are not just prompts and APIs. They are distributed, stateful, compliance-sensitive platforms that must scale under pressure. If you are building LLM-powered tools without platform-grade architecture, you are gambling with reliability, security, and long-term flexibility.AI Platform Engineering with MCP Servers delivers a practical blueprint for building context-aware agent systems that behave predictably in real-world environments. This book shows how to design MCP server architectures that separate model logic from orchestration, enforce observability from day one, and maintain vendor-neutral portability across model providers and infrastructure stacks.You will learn how to: Design context pipelines that prevent drift and control token costsImplement structured world-state management for deterministic agentsAdd production-grade observability, tracing, and performance metricsEnforce policy, auditability, and compliance boundaries at the platform layerAvoid vendor lock-in through abstraction and protocol-driven designScale multi-agent workflows without losing control of reasoning pathsWhy do most AI projects fail after proof-of-concept? Because they treat AI like a feature instead of a platform. This book shows you how to engineer it properly.If you are an AI platform engineer, enterprise architect, or senior developer responsible for reliability and governance, this is your operational manual.Build systems that think clearly. Operate transparently. Scale responsibly.Get your copy today and start engineering AI the way production demands. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9798250289740
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AI Platform Engineering with MCP Servers
Librería: Rarewaves.com UK, London, Reino Unido
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