Cloud Server for Kubernetes in Europe

Cloud Server for Kubernetes in Europe

Cloud Server for Kubernetes in Europe

Kubernetes is the standard orchestration platform for containerized workloads at scale. Running it well requires more than just installing k8s - you need sufficient hardware per node, reliable networking between nodes, and an understanding of what a minimum viable cluster actually looks like.

Hosting your Kubernetes cluster in Europe is a practical requirement if your users or data are here. Low-latency private networking between nodes, GDPR-compliant data residency, and physical proximity to your engineering team all push toward EU hosting.

Why EU hosting matters for Kubernetes

A Kubernetes cluster is a distributed system. Control plane components communicate constantly with worker nodes, and pods communicate with each other across the cluster. Network latency between nodes is not just a performance concern - it directly affects cluster stability. Etcd, the key-value store at the heart of Kubernetes, requires low-latency writes to maintain consistency. Nodes with high latency to the control plane can appear unhealthy and be evicted.

Placing all nodes in the same EU data center, or at least the same region, keeps inter-node latency under 1 ms. That is the baseline you want for a healthy cluster.

GDPR compliance is equally straightforward: workloads that process EU personal data should run on infrastructure that stays within EU jurisdiction.

Minimum server requirements

Kubernetes has real hardware requirements. The control plane and worker nodes have different profiles.

For the control plane node:

  • RAM: 4 GB minimum (8 GB recommended for clusters with more than 10 workers)
  • CPU: 2 cores minimum (4 cores recommended)
  • Disk: 40 GB SSD (etcd is write-intensive; use fast disk)

For each worker node:

  • RAM: 4 GB minimum per node
  • CPU: 2 cores minimum per node
  • Disk: 40 GB SSD per node

A production-ready minimum setup is 1 control plane node plus 2 worker nodes. For high availability, use 3 control plane nodes and 3 or more workers. k3s is a lighter alternative to full Kubernetes and can run on slightly less RAM, making it practical for smaller clusters.

Recommended DCXV configuration

DCXV cloud instances at https://dcxv.com/data-center#cloud start from EUR 15/month. For a 3-node Kubernetes cluster (1 control + 2 workers), three instances with 4 GB RAM and 4 vCPUs each is a reasonable starting point.

DCXV cloud instances on the same data center share a private network with very low inter-instance latency, which is exactly what Kubernetes needs. 24/7 engineer support is included without extra cost - useful when you are debugging a node that will not rejoin the cluster at midnight.

For larger clusters or workloads that need dedicated hardware guarantees, DCXV dedicated servers start from EUR 49/month.

Setup guide

Deploying a k3s cluster (lightweight Kubernetes) on three DCXV instances:

# On the control plane node: install k3s
curl -sfL https://get.k3s.io | sh -

# Get the join token from control plane
cat /var/lib/rancher/k3s/server/node-token

# On each worker node: join the cluster
curl -sfL https://get.k3s.io | K3S_URL=https://<control-plane-ip>:6443 K3S_TOKEN=<token> sh -

# Verify all nodes are ready (run on control plane)
kubectl get nodes

After the cluster is up, install an ingress controller and cert-manager for TLS:

kubectl apply -f https://raw.githubusercontent.com/kubernetes/ingress-nginx/main/deploy/static/provider/cloud/deploy.yaml

Performance expectations

On a 3-node k3s cluster using DCXV 4 GB / 4 vCPU instances:

  • Pod scheduling latency under 2 seconds for typical workloads
  • Inter-pod network throughput of 1-5 Gbps within the same data center
  • Ingress handling 1,000-3,000 HTTP requests per second depending on workload
  • Control plane API response times under 50 ms for standard kubectl operations
  • etcd write latency under 5 ms with SSD-backed storage

These are baseline figures for a cluster running moderate workloads. Heavy batch jobs, large numbers of pods, or workloads with intense inter-service communication will require additional nodes or larger instances.

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