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Kubernetes and Docker

flowchart TD
    A[Kubernetes Docker] --> B[Key Concepts]
    A --> C[Core Principles]
    A --> D[Practical Applications]
    B --> E[Fundamental definitions]
    C --> F[Design patterns]
    D --> G[Real-world usage]

Introduction to Containers

Section titled “Introduction to Containers”
  • What are containers?
  • Benefits of containers
  • Container vs VM
  • Docker overview

Docker Fundamentals

Section titled “Docker Fundamentals”
  • Docker installation
  • Docker images
  • Docker containers
  • Dockerfile
  • Docker Compose

Kubernetes Basics

Section titled “Kubernetes Basics”
  • Kubernetes architecture
  • Pods
  • Services
  • Deployments
  • Namespaces

Kubernetes Networking

Section titled “Kubernetes Networking”
  • Service types
  • Ingress
  • Network policies
  • DNS

Kubernetes Storage

Section titled “Kubernetes Storage”
  • Volumes
  • Persistent volumes
  • Storage classes
  • ConfigMaps
  • Secrets

Kubernetes Security

Section titled “Kubernetes Security”
  • RBAC
  • Network policies
  • Pod security
  • Image security

Production Deployment

Section titled “Production Deployment”
  • Monitoring
  • Logging
  • Scaling
  • Rolling updates
  • Helm charts

See Also

Section titled “See Also”

Worked Examples

Section titled “Worked Examples”

Example 1: Dockerfile for a Python Application

Section titled “Example 1: Dockerfile for a Python Application”
FROM python:3.11-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt
COPY . .
EXPOSE 8000
CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]

Key principles: use slim base images, copy requirements before source (better layer caching), run as non-root in production, use multi-stage builds for compiled languages.

Example 2: Kubernetes Deployment with Health Checks

Section titled “Example 2: Kubernetes Deployment with Health Checks”
apiVersion: apps/v1
kind: Deployment
metadata:
  name: web-app
spec:
  replicas: 3
  selector:
    matchLabels:
      app: web-app
  template:
    spec:
      containers:
      - name: app
        image: myapp:1.0
        ports:
        - containerPort: 8000
        readinessProbe:
          httpGet:
            path: /health
            port: 8000
          initialDelaySeconds: 5
          periodSeconds: 10
        livenessProbe:
          httpGet:
            path: /health
            port: 8000
          initialDelaySeconds: 15
          periodSeconds: 20
        resources:
          requests:
            memory: "128Mi"
            cpu: "250m"
          limits:
            memory: "256Mi"
            cpu: "500m"

Health probes ensure Kubernetes restarts unhealthy pods and only routes traffic to ready ones. Resource requests enable scheduling; limits prevent OOM kills.

Common Pitfalls

Section titled “Common Pitfalls”
  1. Using latest tag in production: Always pin specific versions. latest makes deployments non-reproducible and rollbacks impossible.
  2. Running as root in containers: Use USER directive in Dockerfile. Root containers can escape to the host if a vulnerability is exploited.
  3. Ignoring resource limits: Without limits, a single pod can consume all node resources, starving other workloads. Always set requests and limits.

Summary

Section titled “Summary”

Docker packages applications with their dependencies into portable containers. Kubernetes orchestrates containers at scale with automated scheduling, scaling, and self-healing. Together they form the foundation of modern cloud-native architecture. Docker handles the build/package stage; Kubernetes handles the deploy/run stage.