Bret and Nirmal explore AI agents in Kubernetes with Eitan Yarmush, Senior Architect at Solo.io. Eitan explains how AI agents work through three simple components (system prompts, LLMs, and tools), and demonstrates the kagent project, which provides a Kubernetes-native way to deploy and manage AI workflows.

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Also in this episode, we cover the Model Context Protocol (MCP), which standardizes how agents communicate with external tools, along with practical use cases like incident response, debugging workflows, and CI/CD integration. Eitan shows how to create an agent through a web interface.

We also address the challenges including security concerns (MCP lacks built-in security standards), cost considerations, and technical limitations like context window constraints.

Check out the video podcast version here: https://youtu.be/JTTqG5SOpWY

Creators & Guests

Bret Fisher - Host
Beth Fisher - Producer
Cristi Cotovan - Editor
Nirmal Mehta - Host
Eitan Yarmush - Guest

(00:00) - Intro
(06:53) - Hype vs Reality
(08:45) - Incident Response and Debugging
(12:03) - Defining Agents and MCP
(17:50) - Where Do You Run Agents?
(20:54) - What Problem does kagent Solve?
(31:22) - Authentication and Tool Limitations

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Running AI MCP Tools on Kubernetes with kagent