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Rancher Desktop

Desktop application providing Kubernetes and container management, with a user-friendly interface for running AI workloads locally.

Beginner Kubernetes Containers Desktop Application
🐙 GitHub Repository 🌐 Official Website

Alternative To

  • • Docker Desktop
  • • Minikube
  • • Kind

Difficulty Level

Beginner

Suitable for users with basic technical knowledge. Easy to set up and use.

Overview

Rancher Desktop is an open-source desktop application that brings Kubernetes and container management to your desktop. It provides a user-friendly interface for running Kubernetes and Docker containers locally, making it ideal for AI developers who need to test their applications in a Kubernetes environment.

Why Rancher Desktop for AI Development?

Rancher Desktop simplifies the process of running AI workloads in a Kubernetes environment:

  • Easy-to-use graphical interface for managing Kubernetes clusters
  • Seamless switching between Kubernetes versions
  • Built-in container management with containerd or Docker
  • Simple resource allocation for CPU, memory, and disk
  • Cross-platform support for Windows, macOS, and Linux

System Requirements

  • CPU: 4+ cores
  • RAM: 8GB+
  • Storage: 20GB+

Installation Guide

Prerequisites

  • Basic knowledge of command line interfaces
  • Git installed on your system

Manual Installation

  1. Clone the repository:

    git clone https://github.com/rancher-sandbox/rancher-desktop.git

  2. Navigate to the project directory:

    cd rancher-desktop

  3. Install dependencies:

    pip install -r requirements.txt

  4. Run the application:

    python app.py

  5. Access the application: Open your browser and navigate to http://localhost:8000 (port may vary based on the project)

Note: For detailed installation instructions specific to your operating system and environment, please refer to the official documentation on the project’s GitHub repository.

Practical Exercise: Getting Started with Rancher Desktop

Now that you have Rancher Desktop installed, let’s walk through a simple exercise to help you get familiar with the basics.

Step 1: Basic Configuration

After installation, you’ll need to configure some basic settings to get started.

# Example configuration steps
cd rancher-desktop
cp config.example.yml config.yml
# Edit the config.yml file with your preferred settings

Step 2: Your First Project

Let’s create a simple project to test that everything is working correctly.

Example Task: Create a simple Kubernetes deployment for a TensorFlow model serving application.

  1. Open Rancher Desktop
  2. Navigate to the Kubernetes settings
  3. Set the Kubernetes version to 1.25.x
  4. Allocate at least 4GB of RAM and 2 CPUs
  5. Start the Kubernetes cluster
  6. Use kubectl to deploy a TensorFlow Serving application:
kubectl create deployment tensorflow-serving --image=tensorflow/serving
kubectl expose deployment tensorflow-serving --type=NodePort --port=8501

Step 3: Exploring Advanced Features

Once you’re comfortable with the basics, try exploring some of the more advanced features:

  • Use the built-in container management to build and run custom AI containers
  • Configure persistent volumes for storing model data
  • Set up port forwarding to access your AI services from other applications
  • Explore the Kubernetes dashboard for monitoring your AI workloads

Resources