Kubernetes vs. Docker Swarm vs. Nomad: The 2023 Orchestration Reality Check

I recently watched a competent team of developers burn three weeks trying to debug a service mesh implementation for a simple e-commerce site that served barely 5,000 requests per day. They were defaulting to Kubernetes because it's the "industry standard." Meanwhile, their latency to the database was spiking because their underlying VPS provider was throttling I/O credits.

It was a classic case of resume-driven development meeting bad infrastructure.

In late 2023, the container orchestration landscape in Europe is stable, but the choices are stricter. With Datatilsynet (The Norwegian Data Protection Authority) tightening the screws on GDPR compliance and data sovereignty, where and how you run your clusters matters just as much as the software you choose. Let's cut through the noise and look at the actual operational reality of running containers on Norwegian soil.

The Three Contenders

1. Kubernetes (K8s): The Heavyweight Champion

Kubernetes version 1.28 (released August 2023) introduced SidecarContainers, which is a massive win for service meshes, but let's be honest: K8s is a beast. It requires significant overhead. If you aren't managing at least 20 microservices or require complex autoscaling rules, you are likely burning money on the control plane.

The Hidden Cost: etcd. Kubernetes relies heavily on etcd for state. If your disk latency is high, your cluster will fail. I've seen API servers crash simply because the VPS hosting the master node had noisy neighbors stealing IOPS.

Pro Tip: Always check your etcd disk write latency. If wal_fsync_duration_seconds exceeds 10ms, your cluster is unstable. On CoolVDS NVMe instances, we typically see this under 2ms, which is why we recommend them for control planes.

Here is a standard deployment config for a stateless app in K8s. Notice the complexity just to get a port open:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: nordic-api
  labels:
    app: backend
spec:
  replicas: 3
  selector:
    matchLabels:
      app: backend
  template:
    metadata:
      labels:
        app: backend
    spec:
      containers:
      - name: go-api
        image: registry.coolvds.com/api:v1.4
        ports:
        - containerPort: 8080
        resources:
          requests:
            memory: "64Mi"
            cpu: "250m"
          limits:
            memory: "128Mi"
            cpu: "500m"
---
apiVersion: v1
kind: Service
metadata:
  name: nordic-api-svc
spec:
  selector:
    app: backend
  ports:
    - protocol: TCP
      port: 80
      targetPort: 8080
  type: LoadBalancer

2. Docker Swarm: The "It Just Works" Option

Despite the rumors of its death, Docker Swarm remains the most pragmatic choice for small-to-medium teams in 2023. It is built into the Docker engine. There is no separate binary to install. If you can run docker run, you can run a cluster.

Swarm shines in scenarios where you need to go from "local dev" to "production in Oslo" in under an hour. It lacks the rich ecosystem of Helm charts, but for a standard LAMP stack or a Node.js cluster, it is unbeatable in terms of TCO.

Initialize a swarm in one command:

Then deploy a stack. Compare this simplicity to the K8s manifest above:

version: '3.8'
services:
  web:
    image: nginx:alpine
    deploy:
      replicas: 5
      restart_policy:
        condition: on-failure
    ports:
      - "80:80"
    networks:
      - webnet
networks:
  webnet:

3. HashiCorp Nomad: The Unix Philosophy

Nomad is the dark horse. It creates a single binary that handles scheduling. Unlike K8s, it doesn't care if you run a Docker container, a Java JAR, or a raw binary. For hybrid workloads—common in legacy Norwegian banking or telecom sectors—Nomad is superior.

It integrates seamlessly with Consul for service discovery and Vault for secrets. If you are already in the HashiCorp ecosystem, Nomad is a no-brainer.

job "docs" {
  datacenters = ["oslo-dc1"]

  group "example" {
    count = 3
    network {
      port "http" {
        to = 5678
      }
    }
    task "server" {
      driver = "docker"
      config {
        image = "hashicorp/http-echo"
        ports = ["http"]
        args  = [
          "-listen", ":5678",
          "-text", "hello world",
        ]
      }
    }
  }
}

The Infrastructure Layer: Where Orchestrators Die

You can argue about schedulers all day, but the battle is lost if the kernel panics or the network drops packets. In a containerized environment, the OS kernel is shared. If your hosting provider oversubscribes CPU, a single "noisy neighbor" can cause CPU steal time that ruins your scheduler's ability to allocate resources effectively.

We see this constantly with budget VPS providers. You pay for 4 vCPUs, but you can only sustain 50% usage before the hypervisor throttles you.

This is why we built CoolVDS on KVM.

With KVM (Kernel-based Virtual Machine), you get hardware-level virtualization. When you provision a CoolVDS instance, the memory is reserved. The NVMe I/O is direct. This is critical for databases like PostgreSQL or MongoDB running inside containers.

Comparison: Resource Overhead

Latency and Sovereignty: The Norwegian Context

If your users are in Oslo, Bergen, or Trondheim, hosting your cluster in Frankfurt adds 20-30ms of latency. For a real-time application or high-frequency trading bot, that is an eternity. Hosting locally in Norway cuts that down to <5ms.

Furthermore, post-Schrems II, transferring personal data outside the EEA is a legal minefield. Running your orchestration layer on CoolVDS ensures your data stays within Norwegian jurisdiction, simplifying your GDPR compliance posture significantly.

Technical Verification: Testing Network Throughput

Before you deploy your cluster, verify your node-to-node connectivity. In 2023, 1Gbps private networking is the baseline requirement for reliable replication.

On the client node:

If you aren't getting near line speed, your orchestration overlay network (like Calico or Flannel) will choke under load.

Final Verdict

Don't over-engineer. If you are a team of three managing a monolith and a Redis cache, use Docker Swarm on a couple of robust VPS instances. If you are migrating a legacy Java stack alongside new Go microservices, look at Nomad.

But if you must use Kubernetes, ensure your foundation is solid. Don't run K8s on cheap, shared hosting. The control plane demands consistent IOPS and CPU.

Ready to build a cluster that doesn't wake you up at 3 AM? Deploy a KVM-based, NVMe-powered instance on CoolVDS today and get single-digit latency to Oslo.