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Platform Engineering for Artificial Intelligence: Mastering Kubernetes Orchestration for Natural Language Processing with LLM
Paperback
General ComputersOperating SystemsSystem Administration
Publisher: Independently Published
Published: Sep 4 2026
Pages: 190
Weight: 0.75
Height: 0.40 Width: 7.00 Depth: 10.00
Language: English
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.
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.
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