Multi-Agent LLM Orchestration with Docker Compose and MCP
The article discusses a new book on operational AI using Docker, focusing on building and deploying AI applications. It covers the full lifecycle of running local LLMs and integrating them into real applications. The book provides hands-on examples and guidance on using Docker's AI toolkit for various tasks, including building autonomous agents and orchestrating them on Kubernetes.
- ▪The book is titled 'Operational AI with Docker: LLMOps, Agents and Multi-Model Systems with Docker and Kubernetes'.
- ▪It teaches readers how to run and optimize local LLMs, integrate AI applications with external systems, and deploy securely using Docker.
- ▪The content includes practical examples and code for building autonomous AI agents and managing AI workloads with tools like Prometheus and Grafana.
Opening excerpt (first ~120 words) tap to expand
Operational AI with Docker This is the code repository for Operational AI with Docker: LLMOps, Agents and Multi-Model Systems with Docker and Kubernetes, published by Packt. Build, deploy and scale production-ready AI applications using Docker's integrated AI toolkit. What this book is about If you've ever wanted to take an AI app from "works on my laptop" to something you can actually run in production, this book is for you. It walks through the full lifecycle running local LLMs, wiring them into real applications, integrating external tools through MCP, building autonomous agents and finally orchestrating fleets of agents on Kubernetes all using Docker's AI tooling.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.