Kubernetes vs. Docker Swarm vs. Nomad: The 2024 Orchestration Reality Check for Nordic Ops

Let’s be honest: in September 2024, the default answer to "how should we deploy this?" is almost aggressively "Kubernetes." But for many engineering teams operating out of Oslo or Trondheim, blindly adopting K8s is a resume-driven decision, not a technical one. I've spent the last six months migrating a logistics platform away from a bloated managed Kubernetes service because the egress fees and control plane latency were bleeding the budget dry. The reality of container orchestration is that complexity is not a feature; it’s a tax.

If you are managing infrastructure in Norway, you have specific constraints: GDPR compliance (post-Schrems II), latency to NIX (Norwegian Internet Exchange), and the absolute necessity of high I/O performance for stateful workloads. We are going to look at the three main contenders—Kubernetes (v1.31), Docker Swarm, and HashiCorp Nomad—not through the lens of a marketing brochure, but through the terminal of a sysadmin who gets pagertwo alerts at 3 AM.

The Heavyweight: Kubernetes (K8s)

Kubernetes won the war. With the release of version 1.31 recently, it has stabilized into the operating system of the cloud. However, running K8s requires a fundamental understanding of networking, storage classes, and RBAC that can paralyze a small team. The main argument for K8s is ecosystem. You want GitOps? ArgoCD. You want service mesh? Istio. It is all there.

But here is the catch: K8s eats resources. On a standard VPS, the control plane components (etcd, kube-apiserver, scheduler, controller-manager) consume significant CPU cycles. If you are deploying on CoolVDS, you have the advantage of dedicated resources, but you must tune the kubelet to prevent it from starving your actual applications.

Here is a battle-tested kubeadm init configuration I use for bare-metal-style VPS deployments to ensure the control plane binds correctly to the private interface, keeping traffic off the public internet:

apiVersion: kubeadm.k8s.io/v1beta3
kind: InitConfiguration
localAPIEndpoint:
  advertiseAddress: "10.0.0.5" # Your CoolVDS Private IP
  bindPort: 6443
nodeRegistration:
  kubeletExtraArgs:
    node-ip: "10.0.0.5"
---
apiVersion: kubeadm.k8s.io/v1beta3
kind: ClusterConfiguration
kubernetesVersion: 1.31.0
networking:
  podSubnet: "10.244.0.0/16"
  serviceSubnet: "10.96.0.0/12"
controllerManager:
  extraArgs:
    bind-address: "0.0.0.0"
scheduler:
  extraArgs:
    bind-address: "0.0.0.0"
etcd:
  local:
    extraArgs:
      listen-metrics-urls: "http://0.0.0.0:2381"

When running K8s on a VPS in Norway, latency matters. If your nodes are in Oslo but your control plane is in a "managed" region in Frankfurt, you are adding 20-30ms to every `kubectl` command and every API call your operators make. Self-hosting the control plane on a high-performance VPS in the same datacenter eliminates this lag.

The Storage Problem

Kubernetes is stateless, but your business isn't. The number one killer of self-hosted K8s clusters is slow disk I/O causing etcd to timeout. Etcd is incredibly sensitive to disk write latency. If fsync takes too long, the cluster elects a new leader, and your pods restart. This is where CoolVDS NVMe storage becomes critical. You cannot run a stable K8s cluster on standard HDD or shared SATA SSDs.

Check your disk latency before installing K8s. If the 99th percentile write latency is above 10ms, do not deploy.

The Pragmatic Choice: Docker Swarm

Docker Swarm is not dead. In 2024, for teams of 2-5 developers, it remains the most efficient path from "code on laptop" to "code in production." It lacks the CRDs (Custom Resource Definitions) of Kubernetes, but it processes updates faster and uses a fraction of the RAM.

Swarm's overlay networking is built-in. You don't need to choose between Calico, Flannel, or Cilium. You just initialize it. For a recent client needing a GDPR-compliant internal CRM hosted in Norway, we chose Swarm on three CoolVDS instances. The setup time was 15 minutes.

Initializing a Swarm manager:

The beauty of Swarm is the stack file. It is nearly identical to Docker Compose. Here is how we deploy a high-availability Nginx service with placement constraints to ensure it runs on specific nodes (e.g., nodes with higher bandwidth):

version: "3.8"
services:
  web:
    image: nginx:1.27-alpine
    deploy:
      replicas: 4
      update_config:
        parallelism: 2
        delay: 10s
      restart_policy:
        condition: on-failure
      placement:
        constraints:
          - node.labels.region == oslo
    ports:
      - "80:80"
    networks:
      - webnet

networks:
  webnet:
    driver: overlay

Pro Tip: Docker Swarm encryption is on by default for the overlay network control plane, but not for the data plane. If you are routing sensitive data between nodes over a public interface (even if it's a private VLAN provided by the host), enable data plane encryption by adding --opt encrypted when creating the network.

The Hipster Alternative: HashiCorp Nomad

Nomad takes a different approach. It is a scheduler, not a complete container platform. It can schedule Docker containers, but it can also schedule raw binaries, Java JARs, or QEMU virtual machines. This flexibility is powerful if you have legacy workloads that cannot be containerized yet.

Nomad is a single binary. It is incredibly lightweight. In 2024, Nomad has gained traction among Ops teams who are tired of K8s YAML complexity but need more power than Swarm. It integrates tightly with Consul for service discovery and Vault for secrets.

Checking the status of a Nomad node is instant:

Performance & Latency: The Nordic Context

The geography of your infrastructure defines your performance. Routing traffic from a user in Bergen to a server in Stockholm and back involves unnecessary hops. Hosting on CoolVDS in Norway ensures your data stays within the jurisdiction of Datatilsynet and your latency to end-users is minimal.

Furthermore, the "Noisy Neighbor" effect in multi-tenant cloud environments is a silent killer of orchestration performance. Kubernetes schedulers depend on consistent CPU time. If a neighbor steals CPU cycles (Steal Time), your liveness probes fail, and pods enter a crash loop. CoolVDS utilizes strict KVM virtualization limits, ensuring that the cores you pay for are the cores you get.

Comparison: Resource Overhead

Automating the Node Prep

Regardless of which orchestrator you choose, the OS must be tuned for containers. Default Linux settings are often too conservative for high-concurrency docker networking. On Ubuntu 24.04 LTS, you should apply these sysctl settings before joining the node to any cluster:

#!/bin/bash
# Optimize sysctl for Container Networking
cat <