Operational AI with Docker

Building an AI service and running it reliably in production at scale are two very different challenges, and Operational AI with Docker is concerned entirely with the second one. Ajeet Singh Raina and Harsh Manvar bring container and orchestration expertise to the specific challenges of deploying and operating agentic AI services — the kinds of systems that take autonomous actions, manage state across multiple steps, and need to scale up and down reliably under real-world load. The book covers the full operational stack: containerizing AI services with Docker, orchestrating them with Kubernetes, managing the infrastructure dependencies that agentic AI systems introduce compared to simpler model serving, and building the monitoring and reliability practices needed to keep these systems functioning under production conditions. That operational focus distinguishes it from AI development books that stop at getting a working prototype and from general Kubernetes resources that don’t account for the specific patterns and requirements of AI workloads. At 390 pages, the coverage is thorough enough to serve as a genuine operational reference rather than a surface introduction, suited to DevOps engineers, platform engineers, and AI infrastructure teams who need to run agentic systems reliably rather than just build them. For the engineers responsible for keeping AI services actually working in production, this addresses a gap that most AI-focused books leave largely untouched.

Author:
Ajeet Singh Raina, Harsh Manvar