Richard Atodo

Posted on Oct 1

Building IncidentCopilot: Establishing a Local-First AI DevOps Development Foundation

#ai #docker #react #typescript

Project: IncidentCopilot — AI DevOps Incident Investigation

Milestone: 1 — Repository & Local Development Foundation

Status: ✅ Completed

🎯 Why Start With the Foundation?

When building an AI-powered DevOps system, it’s tempting to jump straight into the LLM.

For IncidentCopilot, I deliberately chose not to.

Evidence first. AI second. Human in the loop.

The AI should reason over verified evidence, not replace deterministic systems like parsing, normalization, persistence, or correlation.

So Milestone 1 focused on:

Repository structure
Local dev environment
Backend & frontend foundations
Config management
Testing setup
Docker & Compose
Documentation & reproducibility

🖥️ Local-First Decision

IncidentCopilot is intentionally local-first. No reliance on:

AWS / Azure / GCP
Paid APIs
Proprietary SaaS infrastructure

Instead, the stack runs via Docker Compose:

FastAPI
PostgreSQL
Qdrant
Ollama
React

📂 Repository Structure

incidentcopilot/
├── backend/
├── frontend/
├── runbooks/
├── test-data/
├── evaluation/
├── docker-compose.yml
├── .env.example
├── README.md
└── Makefile

Backend packages were defined but left intentionally empty — establishing architectural direction without premature implementation.

⚙️ Backend Foundation

FastAPI app with two endpoints:

GET /health → {"status": "ok"}
GET /ready → {"status": "ready"}

Config management via pydantic-settings
Testing with Pytest + FastAPI’s TestClient
Dockerized backend (minimal container, no DB/AI yet)

🎨 Frontend Foundation

React + TypeScript + Vite + Tailwind CSS + Lucide icons
Minimal shell:

IncidentCopilot — AI DevOps Incident Investigation

Cleaned unused Vite starter files
Dockerized frontend with Node-based build image

🛠️ Real Problems & Fixes

Node.js mismatch: upgraded from v20 → v24 for Vite
Docker Desktop: CLI installed but engine not running — fixed by starting Docker Desktop
Windows make: used mingw32-make instead of GNU make
Git hygiene: fixed invalid UTF-8 README + refined .gitignore

✅ Verification

Git hygiene → clean
Backend tests → 1 passed
Frontend lint → 0 errors
Frontend build → ✓ built
Docker Compose config → valid
Backend & frontend containers → running locally

🧩 What We Didn’t Build (Yet)

Milestone 1 deliberately excluded:

PostgreSQL models
Log ingestion APIs
Parsers (Nginx, Kubernetes, Docker, GitHub Actions)
Normalization & correlation
Qdrant + RAG integration
Ollama integration
Structured AI diagnosis
Full incident dashboard

These belong to future milestones.

🏗️ Architecture Principle

Reliable evidence
       ↓
Deterministic analysis
       ↓
AI reasoning

The LLM will sit after the deterministic evidence pipeline.

📌 Key Takeaways

Foundation work = real development
Verification > assumptions
Starter templates should be questioned
Local-first changes dev strategy
AI shouldn’t be the first thing we build

🔮 What’s Next?

Milestone 2 — FastAPI Foundation + PostgreSQL

Moving toward:

FastAPI
   ↓
Services
   ↓
PostgreSQL

🏁 Final Thoughts

IncidentCopilot is still at the beginning. No AI diagnosis yet. No RAG. No ingestion pipeline.

And that’s okay.

Milestone 1 established the engineering environment needed to build those capabilities correctly.

The project now has:

Structured monorepo
FastAPI + React/TypeScript
Tailwind CSS
Config management
Testing
Docker + Compose
Verified local workflow

Most importantly:

Build the evidence pipeline first. Let AI reason over verified evidence later.

🔗 GitHub: https://www.github.com/richardatodo/incidentcopilot

➡️ Next: Milestone 2 — FastAPI + PostgreSQL

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