Build AI Agents in Kubernetes
Learn how to design and deploy AI agents directly in Kubernetes in this live, hands-on workshop with Lin Sun and Christian Posta. You'll work through the foundational building blocks of agentic systems—agents, tool integrations (MCP), and gateways—while gaining a practical understanding of how these components fit together in real environments. This session focuses on getting you hands-on with the core primitives so you can confidently start building and iterating on your own agent-based systems.
In this workshop, you will:
- Deploy and explore AI agents in Kubernetes using kagent
- Inspect and understand agent configuration, including models, YAML, and tool connections
- Learn the challenges of running MCP services in Kubernetes and simplify them with kmcp
- Install and configure agentgateway to expose and route agent traffic
- Work across both local and Kubernetes environments using real configurations
- Build and run a functional agent setup that forms the foundation for more advanced systems
By the end, you'll have a working foundation for running AI agents in Kubernetes—and a clear path to expanding it into more complete, production-ready systems.
Learn how to design and deploy AI agents directly in Kubernetes in this live, hands-on workshop with Lin Sun and Christian Posta. You'll work through the foundational building blocks of agentic systems—agents, tool integrations (MCP), and gateways—while gaining a practical understanding of how these components fit together in real environments. This session focuses on getting you hands-on with the core primitives so you can confidently start building and iterating on your own agent-based systems.
In this workshop, you will:
- Deploy and explore AI agents in Kubernetes using kagent
- Inspect and understand agent configuration, including models, YAML, and tool connections
- Learn the challenges of running MCP services in Kubernetes and simplify them with kmcp
- Install and configure agentgateway to expose and route agent traffic
- Work across both local and Kubernetes environments using real configurations
- Build and run a functional agent setup that forms the foundation for more advanced systems
By the end, you'll have a working foundation for running AI agents in Kubernetes—and a clear path to expanding it into more complete, production-ready systems.


