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Replayable, offline-verifiable records for AI-assisted go/no-go decisions: experiment promotions, typed model answers and human-approved actions.
InfraEye is an agentless observability platform. Deploy your unified infrastructure command center in seconds.
Developer toolsTypeScript · GoGitHub @mnshchtriConnection unstableOwner unconfirmed
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Observing the Unseen • Healing the Broken
InfraEye is an enterprise-grade, agentless observability platform designed for modern DevOps teams. It provides a unified "Command Center" for your entire infrastructure—from bare-metal Linux servers to complex Kubernetes clusters—featuring real-time telemetry, AI-driven diagnostics, and a proactive self-healing engine.Read the full README ↗Observing the Unseen • Healing the Broken
InfraEye is an enterprise-grade, agentless observability platform designed for modern DevOps teams. It provides a unified "Command Center" for your entire infrastructure—from bare-metal Linux servers to complex Kubernetes clusters—featuring real-time telemetry, AI-driven diagnostics, and a proactive self-healing engine.
Explore Documentation • Report Bug • Request Feature
In an era of microservices and ephemeral infrastructure, observability shouldn't be expensive or complex. InfraEye bridges the gap between raw metrics and actionable intelligence by providing a high-fidelity, real-time cockpit that doesn't just tell you what's wrong, but helps you fix it—automatically.
| Module | Description | status |
|---|---|---|
| Infrastructure Navigator | Unified view of Linux servers with real-time CPU, Mem, Disk & Network telemetry. | Production |
| Kubernetes 'Lens' | Advanced resource explorer for Pods, Deployments, and Events with 1-click diagnostics. | Production |
| Netra AI Assistant | LLM-powered infrastructure consulting and log analysis. | Beta |
| Self-Healing Engine | XML-defined alert rules that trigger automated SSH remediation commands. | Production |
| OIDC/SSO Authentication | Keycloak, Auth0, Okta, Azure AD integration for enterprise single sign-on. | Production |
| MCP Sidecar | Model Context Protocol integration for AI-driven cluster troubleshooting. | Experimental |
| SSH Terminal | Full browser-based xterm.js terminal over secure SSH tunnels. | Production |
| Desktop App | Native macOS (Apple Silicon)/Linux app (Wails) — SQLite-backed, single binary, no Docker required. | Beta |
| Infrastructure-as-Code Sync | Sync server lists and alert rules from a Git repo — non-destructive, credentials never read from Git. | Beta |
InfraEye uses a Distributed Bridge architecture. Instead of installing heavy agents on every node, our Go-backend establishes secure, lightweight SSH connections to gather metrics and stream logs.
graph TD
User((DevOps Engineer)) -->|HTTPS/WSS| Web[React Frontend]
Web -->|API/RPC| API[Go Backend]
API -->|Port 22/SSH| DB[Target Servers]
API -->|Port 6443/API| K8s[Kubernetes Clusters]
API -->|JSON-RPC/SSE| MCP[MCP Sidecar]
API -->|GORM| DB_PG[(PostgreSQL)]
API -->|Pub/Sub| REDIS[(Redis)]
MCP -->|Tools| K8s
InfraEye can be deployed fully containerized. We deliver automated installer scripts for both native Kubernetes (recommended) and Docker Compose. Images are pulled directly from ghcr.io/mnshchtri/infra-eye.
This deploys InfraEye, Postgres, Redis, and the MCP sidecar into the infra-eye namespace via Kustomize. It bypasses Docker networking conflicts by using a direct NodePort.
# Ensure KUBECONFIG is set (e.g., export KUBECONFIG=/etc/rancher/k3s/k3s.yaml)
curl -fsSL https://raw.githubusercontent.com/mnshchtri/infra-eye/main/install-k8s.sh | bash
If you prefer a pure Docker setup, this isolates the stack and manages the reverse proxy bindings.
curl -fsSL https://raw.githubusercontent.com/mnshchtri/infra-eye/main/install.sh | bash
A fully self-contained native app — no Docker, no Postgres, no Redis. The same backend and frontend run embedded inside a Wails shell, backed by a local SQLite database. Intended for single-user local use. Currently built for macOS (Apple Silicon) and Linux (amd64).
macOS, via Homebrew:
brew tap mnshchtri/infra-eye
brew install --cask infra-eye
Or download directly from the GitHub Releases page — InfraEye-macOS-arm64.dmg or InfraEye-Linux.deb — or build it yourself:
# Requires Go 1.25+, Node.js 20+, and the Wails v2 CLI
go install github.com/wailsapp/wails/v2/cmd/wails@latest
git clone https://github.com/mnshchtri/infra-eye && cd infra-eye
make desktop-build
This builds the frontend, embeds it into the Go binary, and packages a native .dmg/.deb via Wails, landing in backend/cmd/desktop/build/bin/. On Linux, libgtk-3-dev and libwebkit2gtk-4.1-dev (or 4.0-dev on older distros) must be installed first.
The app creates its own SQLite database and a random JWT secret on first launch, stored under your OS's standard app-data directory (~/Library/Application Support/InfraEye on macOS, ~/.config/InfraEye on Linux). Kubernetes cluster management works if kubernetes-mcp-server is installed and on your PATH; Linux-server (SSH) monitoring works regardless. See documentation.md for details.
If you pull new updates from the GitHub repository or edit your .env configuration file, you can apply these changes instantaneously using our automated hot-reload script.
# Must be executed from the infra-eye directory
./reload.sh
This automatically fetches the latest code, evaluates updated .env credentials, forces container recreations, and sanitizes dangling Docker images to keep your server clean.
After installation, the scripts will output the exact URL you need to access (e.g., http://<node-ip>:30080 for K8s or http://<node-ip>:8080 for Docker).
Default Login:
admininfra123(⚠ Change this password immediately after the first login!)
For active development, we recommend running databases in Docker and the app natively.
# 1. Start core infrastructure
make infra
# 2. Install dependencies
make backend-install
make frontend-install
# 3. Run Development Servers
# Terminal 1: Backend
make backend
# Terminal 2: Frontend
make frontend
We are constantly evolving. Here's what's currently in the pipeline:
We ❤️ contributions! Whether you're fixing a bug, adding a new feature, or improving documentation, your help is appreciated.
git checkout -b feature/amazing-feature).git commit -m 'Add amazing feature').git push origin feature/amazing-feature).How you can help right now: