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Linux GlusterFS HA DATA Storage Lab Ansible Vagrant AI Agent
New
Rating: 4.8 out of 5(3 ratings)
41 students

Linux GlusterFS HA DATA Storage Lab Ansible Vagrant AI Agent

INFRA:: Build a 3-node VM GlusterFS HA cluster on Ubuntu 24 using VMware, Vagrant, Ansible, AI for Docker and K8s labs.
Last updated 7/2026
English

What you'll learn

  • Linux GlusterFS HA DATA Storage Lab Ansible Vagrant AI Agent
  • INFRA:: Build a 3-node VM GlusterFS HA cluster on Ubuntu 24 using VMware, Vagrant, Ansible & AI for Docker and K8s labs.
  • PRACTICAL LAB
  • DATA STORAGE
  • AUTOMATION
  • IAC
  • HA Cluster
  • Server Infra Config
  • DEVIN WINDSURF AI Coding AGENT - How to work?!
  • Docker Swarm and K8S Example
  • VMware + Vagrant

Course content

1 section7 lectures2h 4m total length
  • Linux GlusterFS HA DATA Storage Lab Ansible Vagrant AI Agent1:57:47

    Linux GlusterFS high-availability data storage lab workflows using Ansible and Vagrant, and design an AI agent to automate storage management.

  • New to Linux Virtualization? Start Here First0:22
  • Advantages & Use Cases0:34
  • Disadvantages0:31
  • Problems & Solutions2:55
  • FAQs2:43
  • glusterfs_ha_data_storage_docker_swarm_kubernetes_ansible_lab.zip0:01

Requirements

  • To successfully complete this course, learners should have a foundational understanding of Linux systems and virtualization concepts. Basic familiarity with Ubuntu or any Linux distribution (such as CentOS or Red Hat) is required, including command-line navigation, file system operations, package management, and service control using systemd. Participants should understand basic networking concepts such as IP addressing, SSH connectivity, hostname resolution, and firewall basics. Prior exposure to virtualization tools like VMware Workstation, VirtualBox, or similar hypervisors is highly recommended. A beginner-level understanding of DevOps concepts such as infrastructure automation, configuration management, and CI/CD pipelines will be helpful but not mandatory. Some familiarity with Docker and Kubernetes basics is beneficial for later modules. Learners should have access to a system capable of running multiple virtual machines (minimum 16GB RAM recommended) and be able to install tools such as Vagrant, VMware Workstation, and Ansible. Basic scripting knowledge (Bash or Python) is helpful for understanding automation workflows. No prior experience with GlusterFS is required, as the course starts from fundamentals and gradually progresses toward advanced distributed storage deployment and integration.

Description


This hands-on practical lab course teaches how to design, deploy, and manage a highly available distributed storage system using GlusterFS on Ubuntu 24 Server. Learners build a complete 3-node storage cluster using VMware Workstation and HashiCorp Vagrant, and automate full infrastructure provisioning with Ansible Infrastructure as Code (IaC). The lab is enhanced with modern AI-assisted development workflows using tools like Devin / Windsurf AI coding agents to simulate real-world DevOps acceleration.

The course focuses on building a production-style storage backend that can be mounted and consumed by multiple compute platforms including Docker Swarm clusters and Kubernetes (K8s) environments. Students will learn how distributed storage works, how replication and redundancy ensure high availability, and how shared storage integrates with container orchestration platforms.

This course is important because modern cloud systems depend heavily on fault-tolerant, scalable, and distributed storage systems. Enterprises running microservices, cloud-native applications, and AI workloads require reliable shared storage that survives node failure. Understanding GlusterFS and automation tooling bridges the gap between system administration, DevOps engineering, and cloud architecture.

Key advantages of this course include:

  • Real-world infrastructure simulation using virtualized environments

  • Full automation using Ansible for repeatable deployments

  • Hands-on experience with distributed storage architecture

  • Integration with container platforms (Docker & Kubernetes)

  • Exposure to AI-assisted infrastructure coding workflows

  • Cross-platform learning (Windows, Linux, macOS environments)

This course is ideal for SREs, DevOps engineers, cloud engineers, system administrators, and infrastructure learners who want to master storage systems and automation. It is especially valuable for those preparing for production-grade cloud infrastructure roles.

In the future, distributed storage and automation will become even more critical as organizations move toward edge computing, hybrid cloud, and AI-driven infrastructure management. Skills learned here directly apply to modern cloud-native ecosystems and scalable enterprise systems.


This course is designed to be fully accessible on your personal computer, whether you are using Windows, macOS, or Linux. You can follow and practice every step using free tools such as VMware Workstation Pro / VMware Fusion (free personal use options where available), HashiCorp Vagrant (free), and Ansible (open source) to build and automate your infrastructure lab environments. In addition, you can optionally enhance your learning experience by using AI coding agents like Devin or Windsurf (free tiers where available) to assist with infrastructure scripting, automation, and troubleshooting. This ensures you can realistically simulate enterprise-grade DevOps and cloud infrastructure setups directly on your personal machine without requiring paid cloud resources.



Who this course is for:

  • DevOps Engineers – To automate infrastructure provisioning and build scalable storage backends for cloud-native applications.
  • SRE / System Administrators – To gain hands-on experience with high availability storage systems and improve reliability engineering skills.
  • Cloud & Platform Engineers – To understand distributed storage integration with Kubernetes and Docker Swarm environments.
  • Students & Beginners in Cloud Computing – To build real-world practical skills in virtualization, automation, and storage cluster architecture.