About This Architecture

DevOps Autopilot is a multi-agent AI system orchestrating infrastructure automation across GitHub, Terraform, Kubernetes, and Prometheus using LangGraph, Groq Llama 3.3, and local Qwen models. Natural language requests flow through a Chainlit chat interface into a FastAPI gateway with secret scanning and CVE detection, then route to specialized agents for pipeline generation, IaC validation, Kubernetes deployments, monitoring, diagnostics, and cost estimation. A human-in-the-loop protocol gates risk levels—low-risk tasks execute autonomously while medium and high-risk changes require human confirmation. The system persists state in PostgreSQL and Redis, maintains a RAG knowledge base in ChromaDB, and logs all tool calls for audit and observability via Langfuse.

People also ask

How can I build a multi-agent AI system that automates DevOps tasks like CI/CD, infrastructure-as-code, and Kubernetes deployments with human oversight?

DevOps Autopilot demonstrates a six-layer architecture where LangGraph orchestrates specialized agents (Pipeline, IaC, Deploy, Monitor, Diagnose, Cost) via a Chainlit chat interface. A human-in-the-loop protocol gates risk—low-risk tasks run autonomously, medium-risk require confirmation, high-risk require double confirmation. All tool calls to GitHub, Terraform, Kubernetes, and Prometheus are log