Container orchestration is the automation of deploying, scaling, networking, and managing containerized applications across one or more hosts. When you have a single server running Docker Compose, "orchestration" might feel like overkill. But the moment you add a second server, need automatic restarts, require zero-downtime deployments, or want to scale services based on load, you need some form of orchestration.

The challenge is choosing the right tool. The container ecosystem offers options ranging from dead-simple to extraordinarily complex. This guide provides an honest comparison of the four most relevant orchestration approaches: Docker Compose, Docker Swarm, Kubernetes, and HashiCorp Nomad.

What is Container Orchestration?

At its core, orchestration handles the following concerns:

  • Scheduling: Deciding which host runs which container, based on available resources.
  • Networking: Enabling containers across different hosts to communicate.
  • Service discovery: Allowing containers to find each other by name rather than IP address.
  • Scaling: Running multiple instances of a service and load balancing between them.
  • Health management: Detecting failed containers and restarting or replacing them automatically.
  • Rolling updates: Deploying new versions without downtime.
  • Secret management: Distributing sensitive configuration to containers securely.

Docker Compose: Single-Node Simplicity

Docker Compose is not an orchestrator in the traditional sense. It defines and runs multi-container applications on a single host. But it is the starting point for most Docker deployments, and its simplicity is its greatest strength.

# docker-compose.yml - A typical self-hosted stack
services:
  traefik:
    image: traefik:v3.0
    restart: unless-stopped
    ports:
      - "80:80"
      - "443:443"
    volumes:
      - /var/run/docker.sock:/var/run/docker.sock:ro
      - ./traefik.yml:/etc/traefik/traefik.yml:ro

  app:
    image: myapp:latest
    restart: unless-stopped
    deploy:
      resources:
        limits:
          memory: 512M
          cpus: '0.5'
    depends_on:
      db:
        condition: service_healthy
    labels:
      - "traefik.enable=true"
      - "traefik.http.routers.app.rule=Host(`app.example.com`)"

  db:
    image: postgres:16
    restart: unless-stopped
    volumes:
      - pgdata:/var/lib/postgresql/data
    healthcheck:
      test: ["CMD-SHELL", "pg_isready -U postgres"]
      interval: 10s
      timeout: 5s
      retries: 5

volumes:
  pgdata:
Pros Cons
Extremely simple to learn and use Single node only (no multi-host)
Standard YAML format understood by everyone No automatic scaling
Built into Docker (no extra installation) No rolling updates (stop then start)
Excellent for development and small deployments No cross-host networking
Health checks and restart policies Limited load balancing
Tip: Docker Compose is not "lesser" than Kubernetes. For a single server running 10-50 containers, Compose is the right tool. Adding orchestration complexity when you do not need it creates more problems than it solves.

Docker Swarm: Simple Multi-Node

Docker Swarm is Docker's built-in orchestration mode. It extends Docker Compose concepts across multiple hosts with minimal additional complexity:

# Initialize a Swarm cluster
docker swarm init --advertise-addr 192.168.1.101

# Join additional nodes
docker swarm join --token SWMTKN-1-xxxxx 192.168.1.101:2377

# Deploy a stack (uses the same Compose format)
docker stack deploy -c docker-compose.yml mystack

# docker-compose.yml for Swarm
services:
  web:
    image: nginx:alpine
    deploy:
      replicas: 3
      update_config:
        parallelism: 1
        delay: 10s
        order: start-first
      rollback_config:
        parallelism: 1
        delay: 10s
      restart_policy:
        condition: on-failure
        max_attempts: 3
      placement:
        constraints:
          - node.role == worker
      resources:
        limits:
          cpus: '0.5'
          memory: 256M
    ports:
      - "80:80"
    networks:
      - frontend

  api:
    image: myapi:latest
    deploy:
      replicas: 2
      update_config:
        parallelism: 1
        delay: 30s
    secrets:
      - db_password
    networks:
      - frontend
      - backend

secrets:
  db_password:
    external: true

networks:
  frontend:
    driver: overlay
  backend:
    driver: overlay
# Swarm management commands
docker node ls                    # List cluster nodes
docker service ls                 # List running services
docker service ps mystack_web     # Show service tasks
docker service scale mystack_web=5  # Scale a service
docker service update --image nginx:1.25 mystack_web  # Rolling update
docker stack rm mystack           # Remove a stack
Pros Cons
Built into Docker (no extra installation) Limited ecosystem compared to Kubernetes
Uses familiar Compose syntax Docker, Inc. has deprioritized Swarm development
Easy to set up (one command to initialize) Fewer third-party integrations
Built-in overlay networking No auto-scaling based on metrics
Rolling updates and rollbacks Smaller community support
Built-in secrets management Limited storage orchestration

Kubernetes: The Industry Standard

Kubernetes (K8s) is the most powerful and complex container orchestration platform. It was designed by Google to manage containers at planet scale, and it is the de facto standard for production container deployments in enterprise environments.

# A Kubernetes Deployment (equivalent to a Compose service with replicas)
apiVersion: apps/v1
kind: Deployment
metadata:
  name: myapp
  labels:
    app: myapp
spec:
  replicas: 3
  selector:
    matchLabels:
      app: myapp
  strategy:
    type: RollingUpdate
    rollingUpdate:
      maxSurge: 1
      maxUnavailable: 0
  template:
    metadata:
      labels:
        app: myapp
    spec:
      containers:
        - name: myapp
          image: myapp:v1.0
          ports:
            - containerPort: 8080
          resources:
            requests:
              memory: "128Mi"
              cpu: "250m"
            limits:
              memory: "512Mi"
              cpu: "500m"
          livenessProbe:
            httpGet:
              path: /health
              port: 8080
            initialDelaySeconds: 15
            periodSeconds: 10
          readinessProbe:
            httpGet:
              path: /ready
              port: 8080
            initialDelaySeconds: 5
            periodSeconds: 5
          env:
            - name: DATABASE_URL
              valueFrom:
                secretKeyRef:
                  name: app-secrets
                  key: database-url
---
apiVersion: v1
kind: Service
metadata:
  name: myapp-service
spec:
  selector:
    app: myapp
  ports:
    - port: 80
      targetPort: 8080
  type: ClusterIP
---
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
  name: myapp-ingress
  annotations:
    cert-manager.io/cluster-issuer: letsencrypt-prod
spec:
  rules:
    - host: app.example.com
      http:
        paths:
          - path: /
            pathType: Prefix
            backend:
              service:
                name: myapp-service
                port:
                  number: 80
  tls:
    - hosts:
        - app.example.com
      secretName: myapp-tls
# k3s: Lightweight Kubernetes for homelabs and edge
# Install k3s (single node, takes about 30 seconds)
curl -sfL https://get.k3s.io | sh -

# Add a worker node
curl -sfL https://get.k3s.io | K3S_URL=https://192.168.1.101:6443 \
  K3S_TOKEN=$(cat /var/lib/rancher/k3s/server/node-token) sh -

# kubectl basics
kubectl get nodes
kubectl get pods -A
kubectl apply -f deployment.yml
kubectl get services
kubectl logs myapp-pod-xxxxx
kubectl scale deployment myapp --replicas=5
Pros Cons
Industry standard with massive ecosystem Extremely complex (steep learning curve)
Auto-scaling (HPA, VPA, cluster auto-scaler) Resource-hungry (control plane needs 2+ GB RAM)
Advanced networking (service mesh, network policies) YAML configuration is verbose and error-prone
Extensive storage orchestration (CSI drivers) Overkill for small deployments
Self-healing with probes and restart policies Operational overhead for self-hosted clusters
Huge community and job market Abstractions hide Docker (debugging is harder)
Warning: Kubernetes is not "better" than Docker Compose or Swarm -- it is more powerful and more complex. Running Kubernetes on a single server for a homelab with 20 containers is like driving a semi truck to the grocery store. It works, but it is not the right tool for that job.

HashiCorp Nomad: The Flexible Alternative

Nomad is HashiCorp's workload orchestrator. Unlike Kubernetes, which is container-focused, Nomad can orchestrate containers, VMs, Java applications, and raw executables. It is simpler than Kubernetes while being more capable than Swarm:

# myapp.nomad.hcl - Nomad job specification
job "myapp" {
  datacenters = ["dc1"]
  type = "service"

  group "web" {
    count = 3

    network {
      port "http" {
        to = 8080
      }
    }

    service {
      name = "myapp"
      port = "http"
      tags = ["traefik.enable=true"]

      check {
        type     = "http"
        path     = "/health"
        interval = "10s"
        timeout  = "5s"
      }
    }

    task "app" {
      driver = "docker"

      config {
        image = "myapp:v1.0"
        ports = ["http"]
      }

      resources {
        cpu    = 500  # MHz
        memory = 256  # MB
      }

      env {
        DATABASE_URL = "postgres://user:pass@db:5432/myapp"
      }

      template {
        data = <<EOF
{{ with secret "secret/data/myapp" }}
API_KEY={{ .Data.data.api_key }}
{{ end }}
EOF
        destination = "secrets/env"
        env         = true
      }
    }

    update {
      max_parallel     = 1
      health_check     = "checks"
      min_healthy_time = "30s"
      healthy_deadline = "5m"
      auto_revert      = true
    }
  }
}
# Install Nomad
curl -fsSL https://apt.releases.hashicorp.com/gpg | sudo gpg --dearmor -o /usr/share/keyrings/hashicorp.gpg
echo "deb [signed-by=/usr/share/keyrings/hashicorp.gpg] https://apt.releases.hashicorp.com $(lsb_release -cs) main" | \
  sudo tee /etc/apt/sources.list.d/hashicorp.list
sudo apt update && sudo apt install -y nomad

# Start Nomad in dev mode (single node)
nomad agent -dev

# Deploy a job
nomad job run myapp.nomad.hcl

# Check status
nomad status myapp
nomad alloc logs <alloc-id>
Pros Cons
Simpler than Kubernetes, more capable than Swarm Smaller ecosystem than Kubernetes
Orchestrates containers AND non-container workloads Requires Consul for service discovery (separate tool)
Single binary, easy to deploy Fewer learning resources available
Native Vault integration for secrets Less job market demand than Kubernetes
Multi-region and federation support HCL syntax has a learning curve
Excellent upgrade and canary deployment support Networking is less feature-rich than K8s

Comparison Table

Feature Compose Swarm Kubernetes Nomad
Multi-host No Yes Yes Yes
Auto-scaling No Manual Yes (HPA) Yes (external)
Rolling updates No Yes Yes Yes
Service discovery DNS (same host) DNS + VIP DNS + Services Consul
Secrets management Env files Docker Secrets K8s Secrets Vault
Learning curve Low Low-Medium High Medium
Resource overhead Minimal Low High Low-Medium
Community size Huge Medium Huge Medium
Best for Single server 2-10 nodes 10+ nodes, enterprise Mixed workloads
Minimum nodes 1 1 (3 for HA) 1 (3 for HA) 1 (3 for HA)

When to Use Each Tool

Use Docker Compose When

  • You have a single server (homelab, VPS, small business)
  • You run fewer than 50 containers
  • You do not need automatic failover across hosts
  • Simplicity is a priority

Use Docker Swarm When

  • You have 2-10 servers and want multi-host deployment
  • You want the simplest path from single-node to multi-node
  • Your team already knows Docker Compose
  • You need basic rolling updates and high availability

Use Kubernetes When

  • You have 10+ nodes or expect to grow to that scale
  • You need auto-scaling based on metrics
  • You need advanced networking (service mesh, network policies)
  • Your organization already invests in the Kubernetes ecosystem
  • You want to learn skills directly applicable to most tech companies

Use Nomad When

  • You need to orchestrate mixed workloads (containers + non-containers)
  • You already use other HashiCorp tools (Consul, Vault, Terraform)
  • You want Kubernetes-like capabilities with less complexity
  • You need multi-region federation

Migration Paths

Your orchestration needs will evolve. Here are practical migration paths:

  1. Compose to Swarm: The easiest migration. Swarm uses the same Compose file format. Add a deploy section to your existing Compose files, initialize Swarm mode, and deploy as a stack. Most Compose files work in Swarm with minimal changes.
  2. Compose to Kubernetes: Use kompose to convert Compose files to Kubernetes manifests. The conversion is imperfect and requires manual tuning, but it provides a starting point. Consider k3s for a lightweight Kubernetes that works well in homelabs.
  3. Swarm to Kubernetes: No direct migration tool. Rewrite your stack definitions as Kubernetes manifests. The concepts map roughly: Swarm services become Deployments, overlay networks become Services and Ingress.
  4. Any to Nomad: Rewrite in HCL. Nomad's Docker driver understands Docker images directly, so the container side is straightforward. The main work is translating networking and service discovery.
# Convert Docker Compose to Kubernetes with kompose
kompose convert -f docker-compose.yml

# This generates:
# - deployment.yaml for each service
# - service.yaml for exposed ports
# - persistentvolumeclaim.yaml for volumes
# Review and adjust before applying

The usulnet Approach: Multi-Node Without the Complexity

usulnet takes a different approach to multi-node Docker management. Instead of replacing Docker with an orchestration layer, it works with native Docker on each host. An agent running on each server communicates with a central master, giving you unified management, monitoring, and control across all your Docker hosts without requiring you to change how you run containers.

This approach sits between Docker Compose (single-node) and full orchestration (Swarm/Kubernetes). You keep the simplicity of Compose files on each host while gaining cross-host visibility, centralized monitoring, backup management, and security scanning. For self-hosted environments with 2-5 servers that do not need auto-scaling or cross-host container scheduling, this provides the management capabilities you actually need without the operational overhead of a full orchestrator.

The right tool is the simplest one that meets your requirements. Do not adopt Kubernetes because it is popular. Do not dismiss Docker Compose because it is simple. Start with Compose, grow to Swarm or a management tool like usulnet when you add servers, and consider Kubernetes only when you genuinely need its capabilities.