AI is moving beyond chatbots toward agents that can reason, use tools, call APIs, and execute multi-step tasks. In this session, we’ll build an AI agent using Google’s open-source Agent Development Kit (ADK), containerize it with Docker, and deploy it on Kubernetes.
Through a practical open-source demo, we’ll explore the journey from a locally running agent to a scalable, cloud-native agentic application.
What You’ll Learn:
How AI agents differ from traditional chatbots and LLM applications
How to build an agent using Google’s open-source ADK
How to containerize AI agents with Docker
How to deploy and manage agents on Kubernetes
How agents connect to LLMs, tools, APIs, and other agents
How to use Kubernetes Services, ConfigMaps, Secrets, and health checks for agent workloads
How to scale and observe AI agents in production
How to get started with the open-source demo and extend it for your own use cases

Through a practical open-source demo, we’ll follow an agent from local development to a Kubernetes deployment and explore how agents connect with LLMs, tools, APIs, and other agents.

Attendees will leave with a practical architecture and an open-source example they can use to start running AI agents on Kubernetes.