DevOps help for Cloud Platform Engineers
  • Welcome!
  • Quick Start Guide
  • About Me
  • CV
  • 🧠DevOps & SRE Foundations
    • DevOps Overview
      • Engineering Fundamentals
      • Implementing DevOps Strategy
      • DevOps Readiness Assessment
      • Lifecycle Management
      • The 12 Factor App
      • Design for Self Healing
      • Incident Management Best Practices (2025)
    • SRE Fundamentals
      • Toil Reduction
      • System Simplicity
      • Real-world Scenarios
        • AWS VM Log Monitoring API
    • Agile Development
      • Team Agreements
        • Definition of Done
        • Definition of Ready
        • Team Manifesto
        • Working Agreement
    • Industry Scenarios
      • Finance and Banking
      • Public Sector (UK/EU)
      • Energy Sector Edge Computing
  • DevOps Practices
    • Platform Engineering
    • FinOps
    • Observability
      • Modern Practices
  • 🚀Modern DevOps Practices
    • Infrastructure Testing
    • Modern Development
    • Database DevOps
  • 🛠️Infrastructure as Code (IaC)
    • Terraform
      • Getting Started - Installation and initial setup [BEGINNER]
      • Cloud Integrations - Provider-specific implementations
        • Azure Scenarios
        • AWS Scenarios
        • GCP Scenarios
      • Testing and Validation - Ensuring infrastructure quality
        • Unit Testing
        • Integration Testing
        • End-to-End Testing
        • Terratest Guide
      • Best Practices - Production-ready implementation strategies
        • State Management
        • Security
        • Code Organization
        • Performance
      • Tools & Utilities - Enhancing the Terraform workflow
        • Terraform Docs
        • TFLint
        • Checkov
        • Terrascan
      • CI/CD Integration - Automating infrastructure deployment
        • GitHub Actions - GitHub-based automation workflows
        • Azure Pipelines - Azure DevOps integration
        • GitLab CI - GitLab-based deployment pipelines
    • Bicep
      • Getting Started - First steps with Bicep [BEGINNER]
      • Template Specs
      • Best Practices - Guidelines for effective Bicep implementations
      • Modules - Building reusable components [INTERMEDIATE]
      • Examples - Sample implementations for common scenarios
      • Advanced Features
      • CI/CD Integration - Automating Bicep deployments
        • GitHub Actions
        • Azure Pipelines
  • 💰Cost Management & FinOps
    • Cloud Cost Optimization
  • 🐳Containers & Orchestration
    • Containerization Overview
    • Docker
      • Dockerfile Best Practices
      • Docker Compose
    • Kubernetes
      • CLI Tools - Essential command-line utilities
        • Kubectl
        • Kubens
        • Kubectx
      • Core Concepts
      • Components
      • Best Practices
        • Pod Security
        • Security Monitoring
        • Resource Limits
      • Advanced Features - Beyond the basics [ADVANCED]
        • Service Mesh
        • Ingress Controllers
          • NGINX
          • Traefik
          • Kong
          • Gloo Edge
      • Troubleshooting - Diagnosing and resolving common issues
        • Pod Troubleshooting Commands
      • Enterprise Architecture
      • Health Management
      • Security & Compliance
      • Virtual Clusters
    • OpenShift
  • Service Mesh & Networking
    • Service Mesh Implementation
  • Architecture Patterns
    • Data Mesh
    • Multi-Cloud Networking
    • Disaster Recovery
    • Chaos Engineering
  • Edge Computing
    • Implementation Guide
    • Serverless Edge
    • IoT Edge Patterns
    • Real-Time Processing
    • Edge AI/ML
    • Security Hardening
    • Observability Patterns
    • Network Optimization
    • Storage Patterns
  • 🔄CI/CD & GitOps
    • CI/CD Overview
    • Continuous Integration
    • Continuous Delivery
      • Deployment Strategies
      • Secrets Management
      • Blue-Green Deployments
      • Deployment Metrics
      • Progressive Delivery
      • Release Management for DevOps/SRE (2025)
    • CI/CD Platforms - Tool selection and implementation
      • Azure DevOps
        • Pipelines
          • Stages
          • Jobs
          • Steps
          • Templates - Reusable pipeline components
          • Extends
          • Service Connections - External service authentication
          • Best Practices for 2025
          • Agents and Runners
          • Third-Party Integrations
          • Azure DevOps CLI
        • Boards & Work Items
      • GitHub Actions
      • GitLab
        • GitLab Runner
        • Real-life scenarios
        • Installation guides
        • Pros and Cons
        • Comparison with alternatives
    • GitOps
      • Modern GitOps Practices
      • GitOps Patterns for Multi-Cloud (2025)
      • Flux
        • Overview
        • Progressive Delivery
        • Use GitOps with Flux, GitHub and AKS
  • Source Control
    • Source Control Overview
    • Git Branching Strategies
    • Component Versioning
    • Kubernetes Manifest Versioning
    • GitLab
    • Creating a Fork
    • Naming Branches
    • Pull Requests
    • Integrating LLMs into Source Control Workflows
  • ☁️Cloud Platforms
    • Cloud Strategy
    • Azure
      • Best Practices
      • Landing Zones
      • Services
      • Monitoring
      • Administration Tools - Platform management interfaces
        • Azure PowerShell
        • Azure CLI
      • Tips & Tricks
    • AWS
      • Authentication
      • Best Practices
      • Tips & Tricks
    • Google Cloud
      • Services
    • Private Cloud
  • 🔐Security & Compliance
    • DevSecOps Overview
    • DevSecOps Pipeline Security
    • DevSecOps
      • Real-life Examples
      • Scanning & Protection - Automated security tooling
        • Dependency Scanning
        • Credential Scanning
        • Container Security Scanning
        • Static Code Analysis
          • Best Practices
          • Tool Integration Guide
          • Pipeline Configuration
      • CI/CD Security
      • Secrets Rotation
    • Supply Chain Security
      • SLSA Framework
      • Binary Authorization
      • Artifact Signing
    • Security Best Practices
      • Threat Modeling
      • Kubernetes Security
    • SecOps
    • Zero Trust Model
    • Cloud Compliance
      • ISO/IEC 27001:2022
      • ISO 22301:2019
      • PCI DSS
      • CSA STAR
    • Security Frameworks
    • SIEM and SOAR
  • Security Architecture
    • Zero Trust Implementation
      • Identity Management
      • Network Security
      • Access Control
  • 🔍Observability & Monitoring
    • Observability Fundamentals
    • Logging
    • Metrics
    • Tracing
    • Dashboards
    • SLOs and SLAs
    • Observability as Code
    • Pipeline Observability
  • 🧪Testing Strategies
    • Testing Overview
    • Modern Testing Approaches
    • End-to-End Testing
    • Unit Testing
    • Performance Testing
      • Load Testing
    • Fault Injection Testing
    • Integration Testing
    • Smoke Testing
  • 🤖AI Integration
    • AIops Overview
      • Workflow Automation
      • Predictive Analytics
      • Code Quality
  • 🧠AI & LLM Integration
    • Overview
    • Claude
      • Installation Guide
      • Project Guides
      • MCP Server Setup
      • LLM Comparison
    • Ollama
      • Installation Guide
      • Configuration
      • Models and Fine-tuning
      • DevOps Usage
      • Docker Setup
      • GPU Setup
      • Open WebUI
    • Copilot
      • Installation Guide
      • VS Code Integration
      • CLI Usage
    • Gemini
      • Installation Guides - Platform-specific setup
        • Linux Installation
        • WSL Installation
        • NixOS Installation
      • Gemini 2.5 Features
      • Roles and Agents
      • NotebookML Guide
      • Cloud Infrastructure Deployment
      • Summary
  • 💻Development Environment
    • Tools Overview
    • DevOps Tools
    • Operating Systems - Development platforms
      • NixOS
        • Installation
        • Nix Language Guide
        • DevEnv with Nix
        • Cloud Deployments
      • WSL2
        • Distributions
        • Terminal Setup
    • Editor Environments
    • CLI Tools
      • Azure CLI
      • PowerShell
      • Linux Commands
      • YAML Tools
  • 📚Programming Languages
    • Python
    • Go
    • JavaScript/TypeScript
    • Java
    • Rust
  • 📖Documentation Best Practices
    • Documentation Strategy
    • Project Documentation
    • Release Notes
    • Static Sites
    • Documentation Templates
    • Real-World Examples
  • 📋Reference Materials
    • Glossary
    • Tool Comparison
    • Recommended Reading
    • Troubleshooting Guide
  • Platform Engineering
    • Implementation Guide
  • FinOps
    • Implementation Guide
  • AIOps
    • LLMOps Guide
  • Development Setup
    • Development Setup
Powered by GitBook
On this page
  • System Requirements
  • Linux Installation (Direct Method)
  • Using the Install Script (Recommended)
  • Manual Installation (Debian/Ubuntu)
  • Manual Installation (Red Hat/Fedora)
  • Manual Installation (Binary Installation)
  • NixOS Installation
  • Using Nix Package Manager
  • NixOS Configuration (Configuration.nix)
  • Using Home Manager
  • Docker Installation
  • Basic Docker Setup
  • Docker Compose Setup
  • Docker with GPU Support (NVIDIA)
  • Post-Installation Setup
  • Troubleshooting
  • Common Issues
  • Next Steps
Edit on GitHub
  1. AI & LLM Integration
  2. Ollama

Installation Guide

This guide provides detailed instructions for installing Ollama on various Linux distributions, NixOS, and using Docker containers.

System Requirements

Before installing Ollama, ensure your system meets these minimum requirements:

  • CPU: 64-bit Intel/AMD (x86_64) or ARM64 processor

  • RAM: 8GB minimum (16GB+ recommended for larger models)

  • Storage: 10GB+ free space (varies by model size)

  • Operating System: Linux (kernel 4.15+), macOS 12.0+, or Windows 10/11

  • GPU (optional but recommended):

    • NVIDIA GPU with CUDA 11.4+ support

    • AMD GPU with ROCm 5.4.3+ support

    • Intel Arc GPU with OneAPI support

Linux Installation (Direct Method)

Using the Install Script (Recommended)

For most Linux distributions, the simplest installation method is using the official install script:

curl -fsSL https://ollama.com/install.sh | sh

This script automatically detects your Linux distribution and installs the appropriate package.

Manual Installation (Debian/Ubuntu)

For Debian-based distributions (Ubuntu, Debian, Linux Mint, etc.):

# Download the latest .deb package
wget https://github.com/ollama/ollama/releases/latest/download/ollama-linux-amd64.deb

# Install the package
sudo dpkg -i ollama-linux-amd64.deb

# Install any missing dependencies
sudo apt-get install -f

Manual Installation (Red Hat/Fedora)

For Red Hat-based distributions (RHEL, Fedora, CentOS, etc.):

# Download the latest .rpm package
wget https://github.com/ollama/ollama/releases/latest/download/ollama-linux-x86_64.rpm

# Install the package
sudo rpm -i ollama-linux-x86_64.rpm

Manual Installation (Binary Installation)

If packages are not available for your distribution:

# Download the latest binary
wget https://github.com/ollama/ollama/releases/latest/download/ollama-linux-amd64

# Make it executable
chmod +x ollama-linux-amd64

# Move to a directory in PATH
sudo mv ollama-linux-amd64 /usr/local/bin/ollama

NixOS Installation

Ollama is available in the Nixpkgs collection, making it easy to install on NixOS.

Using Nix Package Manager

nix-env -iA nixos.ollama

NixOS Configuration (Configuration.nix)

For a system-wide installation, add Ollama to your configuration.nix:

{ config, pkgs, ... }:

{
  # Enable Ollama service
  services.ollama = {
    enable = true;
    acceleration = "cuda"; # Options: none, cuda, rocm, or oneapi
    package = pkgs.ollama;
  };
  
  # Add ollama package to system packages
  environment.systemPackages = with pkgs; [
    ollama
  ];
}

After updating your configuration, apply the changes:

sudo nixos-rebuild switch

Using Home Manager

If you're using Home Manager:

{ config, pkgs, ... }:

{
  home.packages = with pkgs; [
    ollama
  ];
}

Docker Installation

Running Ollama in Docker provides a consistent environment across different systems.

Basic Docker Setup

Pull and run the official Ollama Docker image:

# Pull the latest Ollama image
docker pull ollama/ollama:latest

# Run Ollama container
docker run -d \
  --name ollama \
  -p 11434:11434 \
  -v ollama:/root/.ollama \
  ollama/ollama

Docker Compose Setup

Create a docker-compose.yml file:

version: '3'

services:
  ollama:
    image: ollama/ollama:latest
    container_name: ollama
    volumes:
      - ollama_data:/root/.ollama
    ports:
      - "11434:11434"
    restart: unless-stopped

volumes:
  ollama_data:

Launch with Docker Compose:

docker-compose up -d

Docker with GPU Support (NVIDIA)

To enable NVIDIA GPU support:

# Install NVIDIA Container Toolkit
distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
curl -s -L https://nvidia.github.io/libnvidia-container/gpgkey | sudo apt-key add -
curl -s -L https://nvidia.github.io/libnvidia-container/$distribution/libnvidia-container.list | sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit

# Run Ollama with GPU support
docker run -d \
  --name ollama \
  --gpus all \
  -p 11434:11434 \
  -v ollama:/root/.ollama \
  ollama/ollama

Post-Installation Setup

After installing Ollama, perform these steps to complete the setup:

  1. Start the Ollama service:

    ollama serve
  2. Test the installation by running a model:

    ollama pull mistral
    ollama run mistral
  3. Verify API access:

    curl http://localhost:11434/api/generate -d '{
      "model": "mistral",
      "prompt": "Hello, how are you?"
    }'

Troubleshooting

Common Issues

  1. Permission Denied Errors:

    sudo chown -R $USER:$USER ~/.ollama
  2. Network Connectivity Issues:

    # Verify Ollama service is running
    ps aux | grep ollama
    
    # Check if port 11434 is open
    sudo lsof -i:11434
  3. GPU Not Detected:

    # Verify CUDA installation
    nvidia-smi
    
    # Check Ollama logs
    journalctl -u ollama

Next Steps

Now that you have Ollama installed, proceed to:

PreviousOllamaNextConfiguration

Last updated 3 days ago

for optimal performance

for faster inference

For DevOps engineers, check out to see how Ollama can be integrated into your workflows.

🧠
Configure Ollama
Explore available models
Set up GPU acceleration
DevOps Usage Examples