VM vs Container: Understanding Virtualization
Welcome to this foundational course on virtualization technologies. Whether you're deploying AI models, running data pipelines, or managing cloud infrastructure, understanding the difference between Virtual Machines (VMs) and Containers is essential.
Why This Matters
In the world of cloud computing and GPU infrastructure, choosing between VMs and Containers can significantly impact:
- Performance - How fast your applications run
- Cost - How much you pay for resources
- Scalability - How easily you can grow
- Security - How isolated your workloads are
What You'll Learn
By the end of this course, you'll be able to:
- Explain the architecture of VMs and Containers
- Identify the pros and cons of each approach
- Make informed decisions for your specific use cases
- Understand how these technologies apply to GPU workloads
Course Structure
This course is divided into 5 chapters:
Chapter 1: Introduction
A high-level overview of both technologies and why they exist.
Chapter 2: Virtual Machines Deep Dive
Understanding hypervisors, hardware virtualization, and VM architecture.
Chapter 3: Containers Deep Dive
Understanding Docker, container images, and container runtime.
Chapter 4: Comparison
Side-by-side comparison of performance, security, and use cases.
Chapter 5: GPU Workloads
Specific considerations for AI/ML and GPU-intensive applications.
Prerequisites
- Basic understanding of operating systems
- Familiarity with command-line interfaces
- No prior virtualization experience required
Let's Get Started
Click on Chapter 1 to begin your journey into understanding VM vs Container technologies.