The open-source, AI-powered SRE control room.
Diagnose incidents in seconds with an AI agent that reads your logs, checks your metrics, and proposes a fix. 3D visualization. Human-in-the-loop safety. Self-hosted.
- 3D Spatial Topology Map - See your infrastructure as a living, breathing 3D space. Green is healthy, red is on fire, spinning means failing.
- AI Agent Diagnostics - Describe the incident ("checkout API 500s, DB restarting") and the LLM (Claude 3.7) investigates using real tools.
- Human-in-the-Loop Safety - The AI never applies a fix directly. It generates a unified diff. A human must review and approve it. Requires a two-person rule (requester cannot self-approve).
- Defense-in-Depth - Append-only audit logs, prompt-injection defenses, and a strict tool allowlist. Destructive actions are disabled by default.
- Hand Gestures (Optional) - Wave your hand to control the camera via MediaPipe (pinch = zoom, wrist = rotate, point = select).
- Real-time Telemetry - Live host metrics (CPU, RAM, Disk) and Docker container states via Socket.IO.
- Distributed Telemetry: Install the lightweight remote agent on any server (AWS, GCP, homelab) and securely stream its Docker and host metrics back to the central 3D cockpit.
Prerequisites: Node.js 20+ and pnpm.
# 1. Clone the repo
git clone https://github.com/matricphase-dot/aiops.git
cd aiops
# 2. Install dependencies
pnpm install
# 3. Copy environment variables
cp .env.example .env
# (Optional: Edit .env to add your ANTHROPIC_API_KEY or AWS credentials)
# 4. Start everything (frontend + backend)
pnpm start