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Deploying Agentic AI with Docker: A hands-on guide to building and scaling AI services with Docker and Kubernetes - Couverture souple
Synopsis
Most AI books teach concepts.
Very few teach you how to actually build production AI systems from the ground up.
You can connect a model to an application.
You can even make an AI demo work locally.
But building a real AI service is different.
Real systems crash. Containers fail. Agents loop endlessly. Memory grows uncontrollably. Infrastructure becomes unstable under load. Suddenly, the challenge is no longer the model itself, it is the architecture surrounding it.
This book was written for that reality.
Deploying Agentic AI with Docker is a deeply practical, project-focused guide to building and scaling modern AI systems using Docker and Kubernetes. Instead of isolated snippets and disconnected examples, you will work through complete real-world projects designed to reflect how intelligent services are actually engineered and deployed in production environments.
Throughout this book, you will build:
- Stateful AI agents
- Containerized inference services
- Multi-service AI architectures
- Persistent memory systems
- Tool-using autonomous workflows
- Scalable API layers
- Distributed orchestration pipelines
- Production-ready AI deployments with Docker and Kubernetes
Along the way, you will uncover:
- Why most AI deployments become unstable at scale
- How Docker transforms AI deployment workflows
- How Kubernetes manages orchestration and resilience
- How autonomous agents handle memory, tools, and execution loops
- How production AI systems deal with failures, queues, scaling, and observability
- How real engineering decisions impact long-term system reliability
It is a hands-on engineering guide for developers who want to move beyond experiments and start building AI infrastructure that can survive real-world pressure.
If you are ready to stop building temporary demos and start engineering AI systems that are scalable, resilient, and production-ready, this book will show you how.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
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Deploying Agentic AI with Docker: A hands-on guide to building and scaling AI services with Docker and Kubernetes
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Deploying Agentic AI with Docker
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Deploying Agentic AI with Docker
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Deploying Agentic AI with Docker (Paperback)
impression à la demandeVendeur : CitiRetail, Stevenage, Royaume-Uni
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Paperback. Etat : new. Paperback. Most AI books teach concepts.Very few teach you how to actually build production AI systems from the ground up.You can connect a model to an application.You can even make an AI demo work locally.But building a real AI service is different.Real systems crash. Containers fail. Agents loop endlessly. Memory grows uncontrollably. Infrastructure becomes unstable under load. Suddenly, the challenge is no longer the model itself, it is the architecture surrounding it.This book was written for that reality.Deploying Agentic AI with Docker is a deeply practical, project-focused guide to building and scaling modern AI systems using Docker and Kubernetes. Instead of isolated snippets and disconnected examples, you will work through complete real-world projects designed to reflect how intelligent services are actually engineered and deployed in production environments.Throughout this book, you will build: Stateful AI agentsContainerized inference servicesMulti-service AI architecturesPersistent memory systemsTool-using autonomous workflowsScalable API layersDistributed orchestration pipelinesProduction-ready AI deployments with Docker and KubernetesEach project is designed to teach not only how something works, but why modern AI systems are structured the way they are.Along the way, you will uncover: Why most AI deployments become unstable at scaleHow Docker transforms AI deployment workflowsHow Kubernetes manages orchestration and resilienceHow autonomous agents handle memory, tools, and execution loopsHow production AI systems deal with failures, queues, scaling, and observabilityHow real engineering decisions impact long-term system reliabilityThis is not a book built around theory-heavy explanations or toy chatbot tutorials.It is a hands-on engineering guide for developers who want to move beyond experiments and start building AI infrastructure that can survive real-world pressure.If you are ready to stop building temporary demos and start engineering AI systems that are scalable, resilient, and production-ready, this book will show you how. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9798197107404
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Deploying Agentic AI with Docker : A hands-on guide to building and scaling AI services with Docker and Kubernetes
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Taschenbuch. Etat : Neu. Neuware - Most AI books teach concepts.Very few teach you how to actually build production AI systems from the ground up.You can connect a model to an application.You can even make an AI demo work locally.But building a real AI service is different.Real systems crash. Containers fail. Agents loop endlessly. Memory grows uncontrollably. Infrastructure becomes unstable under load. Suddenly, the challenge is no longer the model itself, it is the architecture surrounding it.This book was written for that reality.Deploying Agentic AI with Docker is a deeply practical, project-focused guide to building and scaling modern AI systems using Docker and Kubernetes. Instead of isolated snippets and disconnected examples, you will work through complete real-world projects designed to reflect how intelligent services are actually engineered and deployed in production environments.Throughout this book, you will build: - Stateful AI agents- Containerized inference services- Multi-service AI architectures- Persistent memory systems- Tool-using autonomous workflows- Scalable API layers- Distributed orchestration pipelines- Production-ready AI deployments with Docker and KubernetesEach project is designed to teach not only how something works, but why modern AI systems are structured the way they are.Along the way, you will uncover: - Why most AI deployments become unstable at scale- How Docker transforms AI deployment workflows- How Kubernetes manages orchestration and resilience- How autonomous agents handle memory, tools, and execution loops- How production AI systems deal with failures, queues, scaling, and observability- How real engineering decisions impact long-term system reliabilityThis is not a book built around theory-heavy explanations or toy chatbot tutorials.It is a hands-on engineering guide for developers who want to move beyond experiments and start building AI infrastructure that can survive real-world pressure.If you are ready to stop building temporary demos and start engineering AI systems that are scalable, resilient, and production-ready, this book will show you how. N° de réf. du vendeur 9798197107404
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EUR 42
Expédition à EUR 63,50
Expédition depuis Allemagne vers Etats-Unis
Expédition depuis Allemagne vers Etats-Unis
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