Kubernetes vs Docker: When to Use Each (2025 Guide)

"Should I use Kubernetes or Docker?" is one of the most common questions in modern software development—and it's based on a misunderstanding. Kubernetes and Docker aren't competitors; they solve different problems and often work together.

Docker revolutionized how we package and run applications. Kubernetes revolutionized how we manage those applications at scale. Understanding what each tool does, where they overlap, and when to use them is essential for any developer or operations engineer working with containers in 2025.

This guide clarifies the relationship between Docker and Kubernetes, helps you understand when each is appropriate, and covers the current state of the container ecosystem.

Understanding Containers

Before comparing Docker and Kubernetes, you need to understand containers—the technology both tools work with.

What Containers Are

Containers package an application with everything it needs to run:

• Application code
• Runtime environment (Node.js, Python, Java, etc.)
• System libraries and dependencies
• Configuration files

This package runs consistently across any environment that supports containers—your laptop, a test server, or production cloud infrastructure.

Container vs Virtual Machine:

Benefits Over Traditional Deployment

Consistency: "It works on my machine" becomes "it works everywhere." The container includes all dependencies, so environment differences don't cause failures.

Isolation: Containers are isolated from each other and the host. One container's dependencies don't conflict with another's.

Efficiency: Containers share the host OS kernel, so they're lightweight and fast to start. You can run many more containers than VMs on the same hardware.

Portability: Containers run the same way across different clouds, on-premises data centers, and developer laptops.

Container Images

A container image is a read-only template containing everything needed to run an application. When you run an image, you create a container—a running instance of that image.

Images are built in layers. Each instruction in a Dockerfile creates a new layer. Layers are cached and reused, making builds and distribution efficient.

# Base layer - Alpine Linux with Node.js
FROM node:20-alpine

# Application layer - copy code
COPY package*.json ./
RUN npm install
COPY . .

# Configuration layer - expose port and set command
EXPOSE 3000
CMD ["node", "server.js"]

Container Runtimes

Container runtimes actually execute containers. The most common runtimes:

• containerd: Industry standard, used by Docker and Kubernetes
• CRI-O: Kubernetes-native runtime
• Docker Engine: Docker's runtime (uses containerd internally)

Understanding this distinction matters because Kubernetes supports multiple runtimes, and Docker Engine is just one option (and no longer the default in Kubernetes).

Docker Explained

Docker provides tools for building, distributing, and running containers.

Docker's Core Components

Docker Engine: The runtime that runs containers on a host. Includes:

• dockerd: Background daemon managing containers
• containerd: Low-level container runtime
• runc: Creates and runs containers

Docker CLI: Command-line interface for interacting with Docker:

# Build an image
docker build -t myapp:1.0 .

# Run a container
docker run -d -p 8080:3000 myapp:1.0

# View running containers
docker ps

# Stop a container
docker stop container_id

Docker Hub: Public registry for sharing container images. Contains official images for common software (nginx, postgres, node) and community-contributed images.

Dockerfile

Dockerfiles define how to build images:

# Use official Node.js base image
FROM node:20-alpine

# Set working directory
WORKDIR /app

# Copy dependency files first (better layer caching)
COPY package*.json ./

# Install dependencies
RUN npm ci --only=production

# Copy application code
COPY . .

# Create non-root user for security
RUN addgroup -S appgroup && adduser -S appuser -G appgroup
USER appuser

# Expose port and define startup command
EXPOSE 3000
CMD ["node", "server.js"]

Docker Compose

Docker Compose defines multi-container applications:

# docker-compose.yml
version: '3.8'

services:
  web:
    build: .
    ports:
      - "8080:3000"
    environment:
      - DATABASE_URL=postgres://db:5432/myapp
    depends_on:
      - db

  db:
    image: postgres:15-alpine
    volumes:
      - postgres_data:/var/lib/postgresql/data
    environment:
      - POSTGRES_DB=myapp
      - POSTGRES_PASSWORD=secret

volumes:
  postgres_data:

Start the entire stack with:

docker compose up -d

Docker Desktop

Docker Desktop provides a complete Docker development environment for Mac and Windows:

• Docker Engine running in a Linux VM
• Kubernetes cluster (optional)
• GUI for managing containers
• Volume management and networking

Alternatives to Docker Desktop:

• Podman Desktop
• Rancher Desktop
• Lima (macOS)
• Colima (macOS)

Kubernetes Explained

Kubernetes (K8s) orchestrates containers at scale, handling deployment, scaling, and management across multiple hosts.

The Problem Kubernetes Solves

Docker runs containers on a single host. But production applications need:

• Multiple hosts: For capacity and fault tolerance
• Automatic scaling: Adding/removing containers based on load
• Load balancing: Distributing traffic across containers
• Self-healing: Restarting failed containers automatically
• Rolling updates: Deploying without downtime
• Service discovery: Containers finding each other

Kubernetes provides all of this.

Kubernetes Architecture

Control Plane (Master):

• API Server: Entry point for all cluster operations
• etcd: Distributed key-value store for cluster state
• Scheduler: Assigns containers to nodes
• Controller Manager: Ensures desired state matches actual state

Nodes (Workers):

• kubelet: Agent ensuring containers run on the node
• kube-proxy: Network proxy for service communication
• Container runtime: Actually runs containers (containerd, CRI-O)

Core Concepts

Pod: Smallest deployable unit—one or more containers that share networking and storage:

apiVersion: v1
kind: Pod
metadata:
  name: myapp
spec:
  containers:
  - name: web
    image: myapp:1.0
    ports:
    - containerPort: 3000

Deployment: Manages replica sets and handles updates:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: myapp
spec:
  replicas: 3
  selector:
    matchLabels:
      app: myapp
  template:
    metadata:
      labels:
        app: myapp
    spec:
      containers:
      - name: web
        image: myapp:1.0
        ports:
        - containerPort: 3000
        resources:
          requests:
            memory: "128Mi"
            cpu: "250m"
          limits:
            memory: "256Mi"
            cpu: "500m"

Service: Stable network endpoint for accessing pods:

apiVersion: v1
kind: Service
metadata:
  name: myapp-service
spec:
  selector:
    app: myapp
  ports:
  - port: 80
    targetPort: 3000
  type: LoadBalancer

ConfigMap and Secret: Configuration and sensitive data management:

apiVersion: v1
kind: ConfigMap
metadata:
  name: myapp-config
data:
  LOG_LEVEL: "info"
  API_URL: "https://api.example.com"

---
apiVersion: v1
kind: Secret
metadata:
  name: myapp-secrets
type: Opaque
data:
  DATABASE_PASSWORD: cGFzc3dvcmQxMjM=  # base64 encoded

Kubernetes Features

Auto-scaling:

# Horizontal Pod Autoscaler
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: myapp-hpa
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: myapp
  minReplicas: 2
  maxReplicas: 10
  metrics:
  - type: Resource
    resource:
      name: cpu
      target:
        type: Utilization
        averageUtilization: 70

Rolling updates:

# Update image with zero downtime
kubectl set image deployment/myapp web=myapp:2.0

# Rollback if needed
kubectl rollout undo deployment/myapp

Self-healing: Kubernetes automatically restarts failed containers, reschedules containers when nodes die, and replaces containers that don't respond to health checks.

Key Differences

Understanding what each tool does clarifies when to use each.

Scope of Responsibility

Complexity

Docker: Straightforward to learn and use. A developer can be productive with Docker in hours.

# Build and run - that's it
docker build -t myapp .
docker run -p 8080:3000 myapp

Kubernetes: Significant learning curve. Requires understanding clusters, networking, storage, RBAC, and many resource types.

# Kubernetes equivalent requires multiple resources
kubectl apply -f deployment.yaml
kubectl apply -f service.yaml
kubectl apply -f configmap.yaml
kubectl apply -f ingress.yaml

Use Case Alignment

Docker alone is sufficient for:

• Local development
• Single-server deployments
• Learning containerization
• CI/CD build environments
• Simple applications

Kubernetes is necessary for:

• Multi-server production deployments
• Applications requiring high availability
• Microservices architectures
• Automatic scaling requirements
• Complex networking needs
• Enterprise-grade operations

When to Use Docker (Without Kubernetes)

Docker without Kubernetes is appropriate for many scenarios.

Local Development

Docker provides consistent development environments:

# Start development environment
docker compose up -d

# Develop with live reload
docker compose exec app npm run dev

# Run tests
docker compose exec app npm test

Every developer gets the same environment regardless of their host OS.

Small Projects

For applications that don't need:

• Multiple replicas
• Auto-scaling
• High availability
• Complex networking

Docker Compose on a single server is simpler and sufficient:

# Simple production setup
version: '3.8'
services:
  web:
    image: myapp:1.0
    ports:
      - "80:3000"
    restart: always

  db:
    image: postgres:15
    volumes:
      - db_data:/var/lib/postgresql/data
    restart: always

CI/CD Builds

CI/CD pipelines use Docker to create consistent build environments:

# GitHub Actions example
jobs:
  build:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4

      - name: Build image
        run: docker build -t myapp:${{ github.sha }} .

      - name: Run tests
        run: docker run myapp:${{ github.sha }} npm test

      - name: Push to registry
        run: docker push myapp:${{ github.sha }}

Learning Containers

Start with Docker. Understanding container basics (images, Dockerfiles, networking, volumes) is prerequisite knowledge for Kubernetes anyway.

When to Use Kubernetes

Kubernetes shines when you need production-grade container orchestration.

Production at Scale

When you need multiple replicas across multiple servers:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: api
spec:
  replicas: 5  # Run 5 instances
  selector:
    matchLabels:
      app: api
  template:
    metadata:
      labels:
        app: api
    spec:
      containers:
      - name: api
        image: myapi:1.0
      affinity:
        podAntiAffinity:  # Spread across nodes
          preferredDuringSchedulingIgnoredDuringExecution:
          - weight: 100
            podAffinityTerm:
              topologyKey: kubernetes.io/hostname

High Availability

Kubernetes ensures your application survives failures:

• Automatic pod restarts when containers crash
• Rescheduling to healthy nodes when nodes fail
• Health checks that remove unhealthy pods from load balancers
• Multiple replicas ensure service continuity

Microservices

Kubernetes excels at managing many interconnected services:

• Service discovery lets services find each other
• Internal load balancing distributes traffic
• Network policies control service-to-service communication
• Namespaces isolate different environments or teams

Auto-Scaling

Automatically scale based on demand:

# Scale web tier based on CPU
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
spec:
  minReplicas: 3
  maxReplicas: 20
  metrics:
  - type: Resource
    resource:
      name: cpu
      target:
        type: Utilization
        averageUtilization: 70

Kubernetes can also scale the cluster itself (cluster autoscaler), adding or removing nodes based on demand.

Multi-Cloud and Hybrid

Kubernetes abstracts infrastructure differences:

• Same manifests work across AWS, GCP, Azure, on-premises
• Avoid vendor lock-in
• Run workloads where they make most sense
• Consistent operations across environments

Security Considerations

Both Docker and Kubernetes require security attention.

Docker Security

Image security:

# Use specific, minimal base images
FROM node:20-alpine  # Not FROM node:latest

# Run as non-root user
RUN addgroup -S app && adduser -S app -G app
USER app

# Don't store secrets in images
# Use environment variables or secret management

Runtime security:

# Run with reduced privileges
docker run --read-only --security-opt=no-new-privileges myapp

# Limit resources
docker run --memory=256m --cpus=0.5 myapp

Kubernetes Security

Pod security:

spec:
  securityContext:
    runAsNonRoot: true
    runAsUser: 1000
    fsGroup: 2000
  containers:
  - name: app
    securityContext:
      allowPrivilegeEscalation: false
      readOnlyRootFilesystem: true
      capabilities:
        drop:
          - ALL

Network policies:

apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
metadata:
  name: api-network-policy
spec:
  podSelector:
    matchLabels:
      app: api
  policyTypes:
  - Ingress
  - Egress
  ingress:
  - from:
    - podSelector:
        matchLabels:
          app: web
  egress:
  - to:
    - podSelector:
        matchLabels:
          app: database

RBAC:

apiVersion: rbac.authorization.k8s.io/v1
kind: Role
metadata:
  name: pod-reader
rules:
- apiGroups: [""]
  resources: ["pods"]
  verbs: ["get", "list", "watch"]

2025 Ecosystem Update

The container ecosystem continues evolving.

containerd as Default

Kubernetes removed Docker Engine support in version 1.24 (2022). Kubernetes now uses containerd or CRI-O directly. This doesn't affect how you build images—Docker images work fine—just how Kubernetes runs them.

Managed Kubernetes Options

Major cloud providers offer managed Kubernetes, removing operational burden:

• Amazon EKS: AWS-managed Kubernetes
• Google GKE: GCP-managed Kubernetes (generally considered best)
• Azure AKS: Azure-managed Kubernetes
• DigitalOcean Kubernetes: Simpler, lower cost

These handle control plane management, upgrades, and scaling.

Docker Desktop Alternatives

Licensing changes prompted Docker Desktop alternatives:

• Podman: Daemonless, rootless containers
• Rancher Desktop: Free, open source, K8s included
• Colima: Minimal, macOS focused
• Lima: Lightweight VM manager for containers

Serverless Containers

Container-based serverless options blur the lines:

• AWS Fargate: Serverless containers on ECS/EKS
• Google Cloud Run: Serverless containers, scales to zero
• Azure Container Instances: On-demand containers
• Knative: Kubernetes-native serverless

These provide Kubernetes benefits without managing clusters.

Frequently Asked Questions

1. Is Kubernetes replacing Docker?

No. Kubernetes replaced Docker Engine as its default runtime, but this doesn't affect Docker's role in building and developing containers. You still use Docker to build images and for local development. Kubernetes uses containerd or CRI-O to run containers in production, but Docker-built images work perfectly with these runtimes.

2. Do I need both Docker and Kubernetes?

It depends on your use case. For local development, you need Docker (or an alternative like Podman). For simple deployments, Docker Compose may be sufficient. For production at scale with high availability needs, you need an orchestrator like Kubernetes. Most organizations use Docker for development and Kubernetes for production.

3. Can I run Kubernetes without Docker?

Yes. Kubernetes supports multiple container runtimes through the Container Runtime Interface (CRI). containerd and CRI-O are common choices. Since Kubernetes 1.24, Docker Engine is no longer a supported runtime (though Docker-built images still work). You can build images with Docker and run them on Kubernetes using containerd.

4. What is Docker Swarm vs Kubernetes?

Docker Swarm is Docker's native orchestration tool—simpler than Kubernetes but less feature-rich. It's easier to set up and uses Docker Compose syntax. However, Kubernetes has become the industry standard with broader ecosystem support, more features, and better scalability. Most new projects choose Kubernetes, and Docker has de-emphasized Swarm development.

5. Which should I learn first?

Learn Docker first. Understanding containers, images, Dockerfiles, and Docker Compose is prerequisite knowledge for Kubernetes. You can be productive with Docker in days, while Kubernetes takes longer to master. Once you're comfortable with Docker, Kubernetes concepts will make more sense.

6. Is Kubernetes overkill for small projects?

Often, yes. Kubernetes adds operational complexity that small projects don't benefit from. If you're running a few containers on a single server without scaling or high-availability needs, Docker Compose is simpler and sufficient. Consider Kubernetes when you have multiple services, need auto-scaling, or require high availability.

7. How do I migrate from Docker Compose to Kubernetes?

Tools like Kompose can convert Docker Compose files to Kubernetes manifests as a starting point. However, Kubernetes resources work differently—you'll need to understand Services, Deployments, ConfigMaps, and other concepts. The migration usually involves rewriting rather than just converting. Start by running both in parallel and migrating services incrementally.

8. What is containerd?

containerd is a container runtime that manages the complete container lifecycle—pulling images, managing storage, executing containers, and networking. It's the runtime that Docker Engine uses internally and is now the default runtime for Kubernetes. It's lower-level than Docker, focusing on running containers rather than building images.

9. Is Docker still relevant in 2025?

Absolutely. Docker remains the standard for building container images and local development. The docker build and docker run commands aren't going anywhere. What changed is that Kubernetes doesn't use Docker Engine as its runtime anymore, but this is largely transparent to developers. You still use Docker daily for development, CI/CD, and testing.

10. What are managed Kubernetes options?

Managed Kubernetes services (EKS, GKE, AKS) run the Kubernetes control plane for you—handling API servers, etcd, upgrades, and availability. You manage your applications and worker nodes (or use managed node pools). This significantly reduces operational burden and is how most organizations run Kubernetes in production.

Conclusion

Kubernetes and Docker aren't competing technologies—they're complementary. Docker builds and runs containers locally. Kubernetes orchestrates containers at scale across clusters. Most organizations use both: Docker for development and building images, Kubernetes (or a managed Kubernetes service) for production orchestration.

For small projects or single-server deployments, Docker Compose provides simplicity without Kubernetes complexity. For microservices, high availability, auto-scaling, or multi-cloud deployments, Kubernetes is the industry standard.

The key is matching technology to needs. Don't add Kubernetes complexity if Docker Compose meets your requirements. But don't try to manually orchestrate containers across multiple servers when Kubernetes solves that problem. Start simple, understand your requirements, and adopt complexity only when it provides clear value.

Related Tools

• Docker Command Builder - Generate Docker commands for common operations