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Kubernetes for Generative AI Solutions
Kubernetes for Generative AI Solutions

Kubernetes for Generative AI Solutions: A complete guide to designing, optimizing, and deploying Generative AI workloads on Kubernetes

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Profile Icon Ashok Srirama Profile Icon Sukirti Gupta
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$12.99 per month
Paperback Jun 2025 334 pages 1st Edition
eBook
$39.99
Paperback
$49.99
Subscription
Free Trial
Renews at $12.99p/m
Arrow left icon
Profile Icon Ashok Srirama Profile Icon Sukirti Gupta
Arrow right icon
$12.99 per month
Paperback Jun 2025 334 pages 1st Edition
eBook
$39.99
Paperback
$49.99
Subscription
Free Trial
Renews at $12.99p/m
eBook
$39.99
Paperback
$49.99
Subscription
Free Trial
Renews at $12.99p/m

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Key benefits

  • Build and deploy your first Generative AI workload on Kubernetes with confidence
  • Learn to optimize costly resources such as GPUs using fractional allocation, Spot Instances, and automation
  • Gain hands-on insights into observability, infrastructure automation, and scaling Generative AI workloads
  • Purchase of the print or Kindle book includes a free PDF eBook

Description

Generative AI (GenAI) is revolutionizing industries, from chatbots to recommendation engines to content creation, but deploying these systems at scale poses significant challenges in infrastructure, scalability, security, and cost management. This book is your practical guide to designing, optimizing, and deploying GenAI workloads with Kubernetes (K8s) the leading container orchestration platform trusted by AI pioneers. Whether you're working with large language models, transformer systems, or other GenAI applications, this book helps you confidently take projects from concept to production. You’ll get to grips with foundational concepts in machine learning and GenAI, understanding how to align projects with business goals and KPIs. From there, you'll set up Kubernetes clusters in the cloud, deploy your first workload, and build a solid infrastructure. But your learning doesn't stop at deployment. The chapters highlight essential strategies for scaling GenAI workloads in production, covering model optimization, workflow automation, scaling, GPU efficiency, observability, security, and resilience. By the end of this book, you’ll be fully equipped to confidently design and deploy scalable, secure, resilient, and cost-effective GenAI solutions on Kubernetes.

Who is this book for?

This book is for solutions architects, product managers, engineering leads, DevOps teams, GenAI developers, and AI engineers. It's also suitable for students and academics learning about GenAI, Kubernetes, and cloud-native technologies. A basic understanding of cloud computing and AI concepts is needed, but no prior knowledge of Kubernetes is required.

What you will learn

  • Explore GenAI deployment stack, agents, RAG, and model fine-tuning
  • Implement HPA, VPA, and Karpenter for efficient autoscaling
  • Optimize GPU usage with fractional allocation, MIG, and MPS setups
  • Reduce cloud costs and monitor spending with Kubecost tools
  • Secure GenAI workloads with RBAC, encryption, and service meshes
  • Monitor system health and performance using Prometheus and Grafana
  • Ensure high availability and disaster recovery for GenAI systems
  • Automate GenAI pipelines for continuous integration and delivery

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jun 06, 2025
Length: 334 pages
Edition : 1st
Language : English
ISBN-13 : 9781836209935
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Product feature icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Product feature icon Thousands of reference materials covering every tech concept you need to stay up to date.
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Product Details

Publication date : Jun 06, 2025
Length: 334 pages
Edition : 1st
Language : English
ISBN-13 : 9781836209935
Tools :

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