Day 1: Welcome to Docker

What You'll Learn Today

What container technology is and why we need it
The history and background of Docker
The differences between Virtual Machines (VMs) and containers
The benefits Docker brings to development

The Challenge of Application Development

"It worked on my machine..."

If you've been in software development for any length of time, you've probably heard this phrase. Applications that work perfectly in development suddenly break when deployed to test or production environments. This is one of the most common problems in software development.

Why Does Behavior Change Across Environments?

Applications don't run in isolation. They depend on OS versions, libraries, configuration files, environment variables, and many other factors.

Development Env         Production Env
┌──────────────┐       ┌──────────────┐
│ Python 3.11  │       │ Python 3.9   │  ← Version mismatch
│ Ubuntu 22.04 │       │ CentOS 7     │  ← Different OS
│ Library A v2.0│       │ Library A v1.8│  ← Library mismatch
└──────────────┘       └──────────────┘

These "environment differences" cause numerous problems:

"It doesn't work" issues: Errors due to dependency differences
Hard-to-reproduce bugs: Problems that only occur in specific environments
Deployment fear: Anxiety about changes to production

The Emergence of Container Technology

Containers were born to solve this "environment difference" problem.

What is a Container?

A container is a lightweight executable unit that packages an application with all its dependencies.

flowchart TB
    subgraph Container["Container"]
        App["Application"]
        Deps["Dependencies"]
        Config["Configuration"]
        Runtime["Runtime"]
    end

    Container --> |"Same environment everywhere"| Dev["Development"]
    Container --> |"Same environment everywhere"| Test["Testing"]
    Container --> |"Same environment everywhere"| Prod["Production"]

    style Container fill:#3b82f6,color:#fff
    style Dev fill:#22c55e,color:#fff
    style Test fill:#f59e0b,color:#fff
    style Prod fill:#8b5cf6,color:#fff

Containers include everything needed for an application to run. This means containers behave exactly the same regardless of where they're executed.

What is Docker?

Docker is a container platform announced in 2013 by Solomon Hykes of DotCloud (later Docker, Inc.).

Why Did Docker Revolutionize Computing?

Container technology existed before Docker (LXC, FreeBSD Jail, etc.). However, Docker was revolutionary for the following reasons:

Ease of use: Simple commands to operate containers
Image sharing: Easy sharing via Docker Hub
Dockerfile: Build images from text files
Ecosystem: Rich tools and community support

flowchart LR
    subgraph Before["Before Docker"]
        direction TB
        B1["Complex configuration"]
        B2["Manual installation"]
        B3["Hard to reproduce environments"]
    end

    subgraph After["After Docker"]
        direction TB
        A1["Simple commands"]
        A2["Automated builds"]
        A3["Complete environment reproduction"]
    end

    Before --> |"Docker arrives"| After

    style Before fill:#ef4444,color:#fff
    style After fill:#22c55e,color:#fff

Virtual Machines vs Containers

Traditionally, virtual machines (VMs) were used for environment isolation. How do containers differ from VMs?

Virtual Machines (VMs)

VMs use a hypervisor to virtualize physical hardware. Each VM contains a complete OS.

flowchart TB
    subgraph VM["Virtual Machines"]
        direction TB
        subgraph VM1["VM 1"]
            App1["App"]
            Bins1["Libraries"]
            Guest1["Guest OS"]
        end
        subgraph VM2["VM 2"]
            App2["App"]
            Bins2["Libraries"]
            Guest2["Guest OS"]
        end
        Hyper["Hypervisor"]
        HostOS["Host OS"]
        HW["Hardware"]
    end

    App1 --> Bins1 --> Guest1
    App2 --> Bins2 --> Guest2
    Guest1 --> Hyper
    Guest2 --> Hyper
    Hyper --> HostOS --> HW

    style VM fill:#f59e0b,color:#fff

Containers

Containers share the host OS kernel and are isolated at the process level.

flowchart TB
    subgraph Container["Containers"]
        direction TB
        subgraph C1["Container 1"]
            App1["App"]
            Bins1["Libraries"]
        end
        subgraph C2["Container 2"]
            App2["App"]
            Bins2["Libraries"]
        end
        Docker["Docker Engine"]
        HostOS["Host OS"]
        HW["Hardware"]
    end

    App1 --> Bins1
    App2 --> Bins2
    Bins1 --> Docker
    Bins2 --> Docker
    Docker --> HostOS --> HW

    style Container fill:#3b82f6,color:#fff

Comparison Table

Feature	Virtual Machine	Container
Startup time	Minutes	Seconds
Size	Several GB to tens of GB	Tens to hundreds of MB
Resource efficiency	Low (OS needed for each VM)	High (shared kernel)
Isolation level	Strong (complete OS isolation)	Medium (process isolation)
Portability	Limited	Very high

Docker Architecture

Docker uses a client-server architecture.

flowchart LR
    subgraph Client["Docker Client"]
        CLI["docker CLI"]
    end

    subgraph Server["Docker Server"]
        Daemon["Docker Daemon\n(dockerd)"]
        Images["Images"]
        Containers["Containers"]
        Volumes["Volumes"]
        Networks["Networks"]
    end

    subgraph Registry["Registry"]
        Hub["Docker Hub"]
    end

    CLI --> |"REST API"| Daemon
    Daemon --> Images
    Daemon --> Containers
    Daemon --> Volumes
    Daemon --> Networks
    Daemon <--> |"push/pull"| Hub

    style Client fill:#3b82f6,color:#fff
    style Server fill:#8b5cf6,color:#fff
    style Registry fill:#22c55e,color:#fff

Main Components

Docker Client: CLI for users to interact with Docker
Docker Daemon: Background service that manages containers
Docker Images: Blueprints for containers
Docker Containers: Running instances created from images
Docker Registry: Storage for sharing images

Key Benefits of Docker

1. Environment Consistency

Use the same containers in development, testing, and production. The "it worked on my machine" problem is eliminated.

2. Fast Startup

While VMs take minutes, containers start in seconds. Development cycles are significantly shortened.

3. Efficient Resource Usage

Multiple containers share the OS kernel, allowing more applications to run with fewer resources than VMs.

4. Easy Scaling

Containers are lightweight, making it easy to scale up or down as needed.

5. Version Control

Images can be tagged for version control. If problems occur, you can easily roll back to previous versions.

6. Microservices Compatibility

Each service can run as an independent container, making Docker ideal for microservices architecture.

Docker Terminology

Let's organize the important terms you'll need as you learn Docker.

Term	Description
Image	Read-only template for creating containers
Container	Executable instance created from an image
Dockerfile	Text file containing instructions to build an image
Registry	Place to store and distribute images (Docker Hub, etc.)
Layer	Individual layers that make up an image
Volume	Mechanism for persisting container data

Summary

Concept	Description
Container	Lightweight execution unit packaging app and dependencies
Docker	Platform for easily creating and managing containers
VM vs Container	Containers share kernel, making them lightweight and fast
Image	Blueprint for containers (read-only)
Docker Hub	Registry for sharing images

Key Points

Containers solve the "environment difference" problem
Docker popularized container technology through ease of use
Containers are lighter and faster than VMs
Docker uses a client-server architecture
Containers are created from images

Practice Problems

Problem 1: Basic Concepts

What is the biggest difference between containers and virtual machines? Explain in your own words.

Problem 2: Understanding Terminology

Fill in the blanks:

A Docker "___" is a read-only template for creating containers
A "___" is a place to store and distribute images
A "___" is a file containing instructions to build an image

Challenge Problem

Imagine you have a web application in development. List three problems that might occur when deploying from development to production, and explain how Docker could solve each one.

References

Next Up: In Day 2, we'll learn about "Setting Up Your Docker Environment." We'll actually install Docker and get ready to start using it.