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Installation

This guide will help you install Kubiya SDK and its dependencies.

Prerequisites

Before installing Kubiya SDK, make sure you have the following prerequisites:

  1. Python 3.8+: Kubiya SDK requires Python 3.8 or higher.
  2. Docker: Since Kubiya uses Docker images for tools, you'll need Docker installed and running.

Installing Python

If you don't have Python 3.8+, you can download it from the official Python website.

Verify your Python installation:

Bash
python --version

Installing Docker

Kubiya relies on Docker to run tools. Follow the instructions for your operating system:

Verify your Docker installation:

Bash
docker --version

Make sure Docker is running:

Bash
docker ps

Installing Kubiya SDK

The easiest way to install Kubiya SDK is with pip:

Bash
pip install kubiya-sdk

Optional Dependencies

Kubiya SDK has several optional dependencies for different features:

  • AWS Tools: pip install kubiya-sdk[aws]
  • Kubernetes Integration: pip install kubiya-sdk[kubernetes]
  • Server Components: pip install kubiya-sdk[server]
  • LLM Integration: pip install kubiya-sdk[llm]
  • Full Installation: pip install kubiya-sdk[all]

Verifying the Installation

You can verify that Kubiya SDK is installed correctly by running:

Bash
python -c "import kubiya_sdk; print(kubiya_sdk.__version__)"

Setting Up Kubernetes (Optional)

If you plan to run tools on Kubernetes, you'll need access to a Kubernetes cluster and proper configuration:

  1. Install kubectl: Install kubectl instructions
  2. Configure access to your cluster
  3. Verify you can connect to your cluster:
Bash
kubectl cluster-info

It's good practice to use virtual environments for Python projects:

Bash
# Create a virtual environment
python -m venv venv

# Activate the virtual environment
# On macOS/Linux:
source venv/bin/activate
# On Windows:
venv\Scripts\activate

# Install Kubiya SDK in the virtual environment
pip install kubiya-sdk

Next Steps

Now that you have Kubiya SDK installed, check out the Quick Start Guide to create your first Docker-based tools and workflows.