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'''Introduction to containerization with Docker and Kubernetes''' provides a detailed guide to both technologies. For a quick overview, see [[Docker and Kubernetes: Getting Started]]. This article goes deeper into practical usage patterns and production considerations.

== Why Containerization? ==

Traditional server deployments suffer from several problems:

* '''Dependency conflicts''' — different applications need different library versions
* '''Environment drift''' — development, staging, and production diverge over time
* '''"Works on my machine"''' — code behaves differently across environments
* '''Slow deployments''' — setting up new servers takes hours or days

Containers solve all of these by packaging applications with their exact dependencies into portable, reproducible units.

== Docker in Depth ==

=== Image Layers and Caching ===

Docker images are built in layers. Each instruction in a Dockerfile creates a new layer:

FROM python:3.11-slim # base layer
WORKDIR /app # layer 2
COPY requirements.txt . # layer 3
RUN pip install -r requirements.txt # layer 4 (cached if requirements unchanged)
COPY . . # layer 5 (changes often)

'''Best practice:''' put rarely-changing instructions first to maximize cache utilization.

=== Docker Networking ===

Docker provides several network modes:

* '''bridge''' (default) — containers communicate via an internal network
* '''host''' — container shares the host network stack (best performance)
* '''overlay''' — multi-host networking for Docker Swarm

# Create a custom network
docker network create myapp-network

# Run containers on the same network
docker run -d --network myapp-network --name db postgres:15
docker run -d --network myapp-network --name web myapp

Containers on the same network can reach each other by name (e.g., <code>db</code> resolves to the database container).

=== Docker Volumes ===

Volumes persist data beyond the container lifecycle:

# Named volume
docker run -d -v pgdata:/var/lib/postgresql/data postgres:15

# Bind mount (host directory)
docker run -d -v /host/path:/container/path nginx

=== Docker Compose for Multi-Container Apps ===

A production-ready Docker Compose example:

version: '3.8'
services:
web:
build: .
ports:
- "80:8000"
environment:
- DATABASE_URL=postgres://user:pass@db:5432/app
depends_on:
- db
- redis
restart: unless-stopped

db:
image: postgres:15
volumes:
- pgdata:/var/lib/postgresql/data
environment:
POSTGRES_PASSWORD: secret
restart: unless-stopped

redis:
image: redis:7-alpine
restart: unless-stopped

volumes:
pgdata:

== Kubernetes Architecture ==

=== Control Plane Components ===

* '''API Server''' — the front door for all cluster operations
* '''etcd''' — distributed key-value store for cluster state
* '''Scheduler''' — assigns pods to nodes based on resource requirements
* '''Controller Manager''' — maintains desired cluster state

=== Worker Node Components ===

* '''kubelet''' — manages pods on each node
* '''kube-proxy''' — handles network routing
* '''Container runtime''' — runs containers (containerd, CRI-O)

=== Key Resources ===

'''Deployment''' — manages a set of identical pods:

apiVersion: apps/v1
kind: Deployment
metadata:
name: web-app
spec:
replicas: 3
selector:
matchLabels:
app: web
template:
metadata:
labels:
app: web
spec:
containers:
- name: web
image: myapp:latest
ports:
- containerPort: 8000
resources:
requests:
memory: "128Mi"
cpu: "250m"
limits:
memory: "256Mi"
cpu: "500m"

'''Service''' — stable endpoint for accessing pods:

apiVersion: v1
kind: Service
metadata:
name: web-service
spec:
selector:
app: web
ports:
- port: 80
targetPort: 8000
type: ClusterIP

== Docker vs Kubernetes: When to Use What ==

{| class="wikitable"
|-
! Scenario !! Recommendation
|-
| Single server, few containers || Docker Compose
|-
| Need auto-scaling || Kubernetes
|-
| Small team, simple app || Docker Compose
|-
| Microservices architecture || Kubernetes
|-
| High availability required || Kubernetes
|-
| Quick prototyping || Docker Compose
|}

== See Also ==

* [[Docker and Kubernetes: Getting Started]]
* [[Building a Scalable Cloud Infrastructure]]
* [[Cloud Computing Explained: From Basics to Advanced]]

[[Category:Cloud Computing]]

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