About This Architecture

DevOps Autopilot is a multi-layer AI-powered CI/CD orchestration system combining FastAPI, LangGraph, and specialized LLM agents to automate pipeline generation, infrastructure-as-code validation, and deployment workflows. Layer 0 provides a secure REST API with Chainlit UI, Redis caching, and secret scanning via TruffleHop and Groq NLP; Layer 1 orchestrates task planning and conditional routing through LangGraph StateGraph with human-in-the-loop (HILP) gates at low/medium/high risk levels. Seven specialized agents—spanning generation (Pipeline, IaC, Deploy), operations (Monitor, Cost), and transversal (Diagnose, Post-mortem)—leverage Qwen and Groq LLMs with Langfuse observability and MCP servers for Kubernetes, Terraform, GitHub, Prometheus, and Docker control. This architecture solves the DevOps bottleneck by automating repetitive tasks while maintaining audit trails, cost visibility, and human oversight through a unified memory engine combining Redis sessions, PostgreSQL audit logs, and ChromaDB RAG. Fork, customize, or embed this diagram in your platform documentation to showcase enterprise-grade AI-native DevOps automation.

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How can I build an AI-driven DevOps platform that automates CI/CD pipelines, IaC validation, and deployments while maintaining human oversight and audit trails?

DevOps Autopilot demonstrates a four-layer architecture: a FastAPI + PostgreSQL secure API layer, a LangGraph orchestration layer with HILP gates, seven specialized LLM agents (Groq Llama 3.3, Qwen) for generation and operations, and MCP servers controlling Kubernetes, Terraform, GitHub, and Prometheus. This design enables autonomous task execution with centralized audit logging, cost tracking, an