K8s, Swarm, or Nomad? A 2024 Orchestration Reality Check

Let's be honest: 80% of the companies I consult for in Oslo do not need Kubernetes. There, I said it. We are currently seeing an epidemic of "Resume Driven Development" where startups with three microservices are deploying complex K8s clusters, burning weeks on configuration, and creating a maintenance nightmare that requires a dedicated team to keep alive.

I have spent the last decade debugging distributed systems across Europe, from high-frequency trading platforms in London to government data portals here in Norway. The lesson is always the same: complexity is technical debt. If you cannot explain your networking topology on a napkin, it will break at 3 AM on a Saturday.

Today, we represent the state of container orchestration as it stands in late 2024. We are comparing the heavyweight champion (Kubernetes), the persistent underdog (Docker Swarm), and the pragmatic alternative (Nomad). We will look at this through the lens of performance, cost, and specifically, the infrastructure required to run them effectively—because an orchestrator is only as good as the VPS Norway creates for it.

The Infrastructure Foundation: Latency and IOPS

Before we touch the software, we must address the hardware. Orchestrators are chatty. They constantly communicate state between manager nodes and worker nodes. If your underlying infrastructure has high latency or "noisy neighbors" stealing CPU cycles, your cluster will become unstable regardless of which software you choose.

In a recent project migrating a logistics platform from a US-based cloud to local Norwegian hosting, we faced constant etcd timeouts. The issue wasn't configuration; it was disk latency. etcd (the brain of Kubernetes) is incredibly sensitive to fsync latency. If you aren't running on NVMe storage, you are playing with fire.

Here is a quick check I run on every fresh node to ensure it qualifies for cluster membership. If the result is 1, get a new provider. If it's 0, you're on solid state storage:

On CoolVDS NVMe instances, we consistently see write latencies well under the recommended thresholds for etcd, ensuring leader elections don't time out during peak load.

1. Docker Swarm: The "Good Enough" Solution

Docker Swarm is not dead. In 2024, it remains the fastest way to go from "code on laptop" to "cluster in production." It is built into the Docker engine, meaning if you have Docker installed, you have Swarm.

The Use Case

Small to medium teams who want High Availability (HA) without managing a separate networking overlay or storage interface. It is perfect for monolithic apps transitioning to microservices.

Configuration

Setting up a Swarm cluster takes exactly two commands. Compare this to the bootstrap process of K8s.

And on the worker node:

Below is a production-ready stack file. Notice how simple the syntax is compared to K8s manifests. We define replicas, update configurations, and restart policies in a single file.

version: '3.8'
services:
  web:
    image: nginx:1.25-alpine
    deploy:
      replicas: 3
      update_config:
        parallelism: 1
        delay: 10s
      restart_policy:
        condition: on-failure
      placement:
        constraints:
          - node.role == worker
    ports:
      - "80:80"
    networks:
      - webnet

  api:
    image: my-registry.no/api:v2
    deploy:
      replicas: 2
      resources:
        limits:
          cpus: '0.50'
          memory: 512M
    networks:
      - webnet
      - backend

networks:
  webnet:
  backend:

The Catch: Swarm struggles with complex stateful workloads and advanced autoscaling logic. However, for serving stateless web apps with low latency to Norwegian users, it is often more performant due to lower networking overhead.

2. Kubernetes (K8s): The Industrial Standard

Kubernetes is the operating system of the cloud. By late 2024, version 1.31+ has stabilized many features, but the learning curve remains a wall. It decouples infrastructure from applications completely.

The Use Case

Enterprise environments requiring complex compliance (GDPR/Schrems II), granular RBAC (Role-Based Access Control), and massive scale. If you need to separate your "Dev" team permissions from your "Ops" team permissions strictly, K8s is mandatory.

The Reality of Resource Consumption

K8s is heavy. A control plane node needs significant RAM just to exist. On cheap shared hosting, the kube-apiserver will be starved of CPU. This is why we recommend dedicated core VPS Norway instances for the control plane.

To inspect your node resource usage to ensure you aren't overcommitting:

Here is a standard Deployment manifest. Note the verbosity. This achieves roughly the same as the Swarm file above but requires significantly more boilerplate.

apiVersion: apps/v1
kind: Deployment
metadata:
  name: production-api
  namespace: backend
spec:
  replicas: 3
  selector:
    matchLabels:
      app: api
  strategy:
    type: RollingUpdate
    rollingUpdate:
      maxSurge: 1
      maxUnavailable: 0
  template:
    metadata:
      labels:
        app: api
    spec:
      containers:
      - name: api-container
        image: my-registry.no/api:v2
        ports:
        - containerPort: 8080
        resources:
          requests:
            memory: "256Mi"
            cpu: "250m"
          limits:
            memory: "512Mi"
            cpu: "500m"
        livenessProbe:
          httpGet:
            path: /healthz
            port: 8080
          initialDelaySeconds: 5
          periodSeconds: 10
      nodeSelector:
        disktype: nvme

Pro Tip: Always set resources.requests and resources.limits. Without them, a single memory leak in one pod can trigger the Linux OOM Killer and crash your entire node. This is the #1 cause of instability I see in unmanaged clusters.

3. Nomad: The Unix Philosophy Approach

Nomad by HashiCorp is often overlooked, which is a tragedy. It is a single binary. It schedules containers, but also Java JARs, binaries, and virtual machines. It integrates tightly with Consul and Vault.

The Use Case

Mixed workloads. If you have legacy binaries that cannot be containerized yet, but you still want orchestration, Nomad is your only choice. It is also incredibly lightweight, making it ideal for edge computing or smaller VPS instances.

Running a job is as simple as:

The syntax (HCL) is human-readable and bridges the gap between the simplicity of Swarm and the power of K8s.

job "payment-gateway" {
  datacenters = ["oslo-dc1"]
  type = "service"

  group "api" {
    count = 3

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

    task "server" {
      driver = "docker"

      config {
        image = "payment-service:1.4.2"
        ports = ["http"]
      }

      resources {
        cpu    = 500
        memory = 256
      }

      service {
        name = "payments"
        tags = ["urlprefix-/pay"]
        port = "http"
        check {
          type     = "http"
          path     = "/health"
          interval = "10s"
          timeout  = "2s"
        }
      }
    }
  }
}

Latency and Data Sovereignty in Norway

Regardless of the orchestrator, data placement is critical in 2024. With the Norwegian Datatilsynet keeping a close watch on international data transfers, hosting your cluster inside Norway is not just a performance decision; it is a legal one.

When you host on CoolVDS, you are pinging 1-2ms from major Norwegian ISPs. Compare this to 30ms+ roundtrip to Frankfurt or Amsterdam. For a microservices architecture where a single user request might trigger 10 internal service calls, that latency compounds.

10 internal calls @ 2ms = 20ms overhead.
10 internal calls @ 30ms = 300ms overhead.

That is the difference between a snappy UI and a frustrated user. You can check your latency to your current provider using mtr to see where the packets are dropping:

Conclusion: Choose Based on Ops Capacity

Here is the verdict for 2024:

• Choose Docker Swarm if you have a small team (1-5 devs), need a straightforward setup, and want to sleep at night without debugging ingress controllers.
• Choose Kubernetes if you are building a platform, need strict namespace isolation, or have a dedicated DevOps engineer on payroll.
• Choose Nomad if you appreciate simplicity, need to run non-container workloads, or want to squeeze every ounce of performance out of your hardware.

Whatever you choose, the orchestration layer cannot fix a weak foundation. You need ddos protection, stable throughput, and hardware isolation.

Don't let IO wait times kill your cluster's performance. Deploy your orchestrator on a platform built for engineers, by engineers. Spin up a high-performance test instance on CoolVDS in under 60 seconds and feel the difference raw NVMe power makes.