Platform Engineering for Artificial Intelligence : Mastering Kubernetes Orchestration for Natural Language Processing with LLM
Language: English
Published by Amazon Digital Services LLC - Kdp Sep 2026, 2026
Series: Book 2 of 4 - The Cloud-Native AI Orchestration Series
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 27.07
Quantity: 2 available
Add to basketItem description from seller
Neuware - What happens when AI experimentation needs to become reliable enterprise infrastructure Building an LLM application is one challenge. Building the platform that allows AI teams to deploy, scale, secure, observe, and continuously improve those applications is another.Platform Engineering for Artificial Intelligence: Mastering Kubernetes Orchestration for Natural Language Processing with LLM explores the architecture behind modern enterprise AI platforms, bringing together Kubernetes, large language models, RAG, vector databases, GPUs, agentic workflows, and LLMOps.Designed for engineers and architects working at the intersection of cloud infrastructure and AI, this book explores how to create standardized, scalable foundations for production LLM workloads.Inside, you'll explore: - Designing internal AI platforms and developer-friendly 'golden paths'- Deploying and serving LLMs with vLLM and TGI on Kubernetes- Scaling vector databases and persistent embedding infrastructure- Building and operating RAG pipelines with event-driven workloads- Orchestrating MCP gateways, tools, and multi-agent systems- Running LoRA, QLoRA, and distributed fine-tuning workflows- Managing LLM gateways, token budgets, caching, and model routing- Implementing security, guardrails, RBAC, PII protection, and compliance- Establishing observability and LLMOps across the model lifecycleIf you're ready to move beyond isolated AI prototypes and understand the infrastructure required to support scalable, governed, production-ready enterprise AI, this book provides a practical architectural foundation for the journey.Build the platform your AI teams can depend on. …
Seller Inventory # 9798171899660
- Title
- Platform Engineering for Artificial Intelligence : Mastering Kubernetes Orchestration for Natural Language Processing with LLM
- Author
- Erik Stormveld
- Publisher
- Amazon Digital Services LLC - Kdp Sep 2026
- Publication year
- 2026
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 13
- 9798171899660
- Item weight
- 340 grams
- Dimensions
- 254x178x10 mm
- Series
- Book 2 of 4: The Cloud-Native AI Orchestration Series
Building an LLM application is one challenge. Building the platform that allows AI teams to deploy, scale, secure, observe, and continuously improve those applications is another.
Platform Engineering for Artificial Intelligence: Mastering Kubernetes Orchestration for Natural Language Processing with LLM explores the architecture behind modern enterprise AI platforms, bringing together Kubernetes, large language models, RAG, vector databases, GPUs, agentic workflows, and LLMOps.
Designed for engineers and architects working at the intersection of cloud infrastructure and AI, this book explores how to create standardized, scalable foundations for production LLM workloads.
Inside, you'll explore:
- Designing internal AI platforms and developer-friendly “golden paths”
- Deploying and serving LLMs with vLLM and TGI on Kubernetes
- Scaling vector databases and persistent embedding infrastructure
- Building and operating RAG pipelines with event-driven workloads
- Orchestrating MCP gateways, tools, and multi-agent systems
- Running LoRA, QLoRA, and distributed fine-tuning workflows
- Managing LLM gateways, token budgets, caching, and model routing
- Implementing security, guardrails, RBAC, PII protection, and compliance
- Establishing observability and LLMOps across the model lifecycle
Build the platform your AI teams can depend on.
"Synopsis" may belong to another edition of this title.
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