Gemini Schema-Enforced K8s Generation

This demo is a technical deep dive into an AI assistant that generates production-grade Kubernetes and Sveltos configurations from natural language. I’ll show how I built it to tackle the complexity of Kubernetes schemas and answer advanced technical questions about Sveltos, a multi-cluster management platform that extends Kubernetes with advanced GitOps capabilities.

The core technical challenge is that Kubernetes and Sveltos schemas are massive and complex, requiring large context windows and strict structural enforcement to generate valid YAML. I’ll walk through the code and demonstrate how I use a multi-stage agentic workflow with Gemini 2.5 Flash. The system first classifies user intent (Q&A, new config, modification, or out-of-topic) and then routes to a specialized agent.

The key innovation I’ll showcase is the use of Gemini’s function calling capabilities to enforce the complex, nested schemas required for valid Kubernetes resources. This unique approach, combined with Gemini’s large context window, makes it possible to reliably generate intricate K8s or Sveltos configurations directly from a simple prompt. For the Q&A portion, the assistant uses a RAG pipeline with Google’s embedding models and Google Search Grounding to provide accurate, cited answers from technical documentation.