El Bruno

⚠️ This blog post was created with the help of AI tools. Yes, I used a bit of magic from language models to organize my thoughts and automate the boring parts, but the geeky fun and the 🤖 in C# are 100% mine.

Hi!

If you’re running Ollama locally on Windows—whether you’re tinkering with LLMs, building local AI demos, or just curious about the overhead of large models—you’ve probably wondered: Is it still running? How much CPU is it chewing? Did that model load?

Welcome to ElBruno.OllamaMonitor.

It’s a no-frills system tray app that sits in your Windows notification area and tells you, at a glance, exactly what your local Ollama instance is doing. No dashboards. No complexity. Just real-time status, resource metrics, and a floating details window when you need more info.

ElBruno.OllamaMonitor sits in your Windows system tray and tells you:

• Is Ollama running? A glance at the tray icon shows you the status.
• Is a model loaded? See what’s currently active.
• How much CPU, RAM, and GPU is it using? Real-time resource metrics from the Ollama process.
• Any errors? Get instant visual feedback if something’s wrong.

Perfect for:

• Local AI developers who need quick visibility into Ollama
• Demo presenters who want to know resource impact in real-time
• Anyone running large models locally who’s curious about the overhead

Installation

Via NuGet (Recommended)

dotnet tool install --global ElBruno.OllamaMonitor

Then launch anytime:

ollamamon

From Source

git clone https://github.com/elbruno/ElBruno.OllamaMonitor.git
cd ElBruno.OllamaMonitor
dotnet build src/ElBruno.OllamaMonitor/
dotnet run --project src/ElBruno.OllamaMonitor/

Quick Start

1. Launch the app:ollamamon The app starts minimized to the tray. Click the icon to open the details window or mini monitor.
2. Check your status: Look at the tray icon color—it tells you Ollama’s status at a glance.
3. Configure (optional): See Configuration Guide for endpoint, refresh rate, and threshold settings.

Features

• ✅ System Tray Integration — Runs in the background, always visible
• ✅ Visual Status Indicators — Color-coded icons for quick status checks
• ✅ Standard Details Window — A normal Windows window with minimize/close behavior that keeps the app in the tray when closed
• ✅ Mini Monitor Window — A semi-transparent always-on-top compact view for CPU, RAM, GPU, and model status
• ✅ Local Configuration — Customize endpoint, refresh rate, thresholds
• ✅ CLI Commands — Fully scriptable configuration
• ✅ GPU Metrics — Best-effort NVIDIA GPU tracking (if nvidia-smi is available)
• ✅ Copy to Clipboard — Quickly share diagnostics
• ✅ Manual Refresh — Force an immediate check
• ✅ Open Ollama URL — Quick link to the Ollama API

Requirements

• Windows 10 / Windows 11 (requires .NET 10 runtime, which can be downloaded from dotnet.microsoft.com)
• Ollama running locally (download from ollama.ai)
• .NET 10 SDK to build from source

Optional:

• nvidia-smi (NVIDIA GPU drivers) for GPU metrics

Configuration

See Configuration Guide for detailed setup, CLI commands, custom thresholds, and advanced options like remote Ollama monitoring.

Try it: dotnet tool install --global ElBruno.OllamaMonitor

Docs: See the GitHub repository

Made by: El Bruno — A .NET developer obsessed with local AI and productivity.