Running AI MCP Tools on Kubernetes with kagent

Agentic DevOps

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.

🙌 My next course is coming soon! I've opened the waitlist for those wanting to go deep in GitHub Actions for DevOps and AI automation in 2025. I'm so thrilled to announce this course. The waitlist allows you to quickly sign up for some content updates, discounts, and more as I finish building the course.
https://courses.bretfisher.com/waitlist 🍾

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
• (06:13) - Hype vs Reality
• (08:05) - Incident Response and Debugging
• (11:23) - Defining Agents and MCP
• (17:10) - Where Do You Run Agents?
• (20:14) - What Problem does kagent Solve?
• (30:42) - Authentication and Tool Limitations

You can also support my free material by subscribing to my YouTube channel and my weekly newsletter at bret.news!

Grab the best coupons for my Docker and Kubernetes courses.
Join my cloud native DevOps community on Discord.
Grab some merch at Bret's Loot Box
Homepage bretfisher.com

★ Support this podcast on Patreon ★