Why hetzner-k3s Stands Out

There are several ways to run Kubernetes on Hetzner Cloud. This page explains why hetzner-k3s might be the right choice for your needs, with an honest look at how it compares to alternatives.

At a Glance

Factor	hetzner-k3s	Managed Services	Terraform-based	Cluster API
Setup time	2-3 minutes	5-10 minutes	15-30+ minutes	20+ minutes
Dependencies	CLI only	Account signup	Terraform, Packer, HCL	Management cluster
Data privacy	Full control	Third-party access	Full control	Full control
Monthly cost	Infrastructure only	Infrastructure + platform fees (scale with cluster size)	Infrastructure only	Infrastructure only
Credential exposure	None	API tokens to third party	None	None
Learning curve	Low	Low	Medium-High	High
Best for	Most Hetzner users	Zero-ops teams	Terraform-native teams	Multi-cloud standardization

What hetzner-k3s Offers

Speed

Creating a highly available cluster with 3 masters and 3 workers takes 2-3 minutes. This includes:

Provisioning all infrastructure (instances, load balancer, private network, firewall)
Deploying k3s to all nodes
Installing Cloud Controller Manager, CSI driver, System Upgrade Controller, and Cluster Autoscaler

In stress testing, a 500-node cluster was created in under 11 minutes.

Minimal Dependencies

You need exactly three things:

A Hetzner Cloud API token
An SSH key pair
The hetzner-k3s CLI tool

No Terraform, Packer, Ansible, or existing Kubernetes cluster. No need to learn HCL or manage Terraform state.

Lightweight Kubernetes

k3s uses significantly less memory and CPU than standard Kubernetes, leaving more resources for your workloads. It's a single binary, making deployments and upgrades fast and reliable.

Full Data Sovereignty

Run the tool on your own machine
Your Hetzner API token never leaves your system
No third party gains access to your clusters, credentials, or data
Complete control with no intermediary

Cost Efficiency

The tool is free and open source
You only pay for Hetzner infrastructure
No per-user fees, per-cluster fees, or management fees
No surprise charges as your team or infrastructure grows

How Alternatives Compare

Managed Services (Cloudfleet, Edka, Syself)

Managed services handle cluster operations for you, which is valuable if you want zero operational overhead.

Considerations

Credential sharing: You provide your Hetzner API token to the service. The provider has ongoing access to your cloud account and can see your workloads. For regulated industries or security-conscious teams, this may be a concern.

Pricing structure: Managed services typically charge: - A base cluster management fee - Per-vCPU fees for worker nodes - Sometimes per-user fees for enterprise tiers

These platform fees add up quickly as clusters grow. A small development cluster might have modest fees, but production clusters with dozens of nodes can see platform costs that rival or exceed the underlying Hetzner infrastructure costs.

For example, Cloudfleet's free tier limits you to 24 vCPUs with standard availability. Beyond that, costs scale with each additional vCPU. The difference between hetzner-k3s (infrastructure only) and managed services becomes substantial at scale—potentially saving hundreds or thousands of euros per month on larger deployments.

Vendor dependency: Your cluster management depends on the service's availability. If the provider changes pricing, terms, or discontinues service, you're affected. Migration requires effort.

When managed services make sense: Teams that prioritize zero operational overhead over cost or data privacy. Organizations where someone else handling infrastructure is worth the ongoing fees.

Terraform-based Solutions (terraform-hcloud-kube-hetzner, etc.)

Terraform-based solutions are powerful and flexible, especially for teams already using Terraform.

Considerations

Multiple dependencies: You need: - Terraform or OpenTofu - Packer (for custom images) - kubectl CLI - hcloud CLI

Each tool requires installation, configuration, and learning.

Learning curve: You need to understand: - Terraform state management - HCL syntax - How changes propagate through Terraform plans - Debugging across multiple tools

Ongoing maintenance: Terraform state must be stored and managed carefully. Upgrades require understanding how Terraform handles infrastructure drift.

What you gain: More flexibility, infrastructure-as-code patterns familiar to platform teams, integration with existing Terraform workflows.

When Terraform-based solutions make sense: Teams already using Terraform extensively. Organizations with platform engineering teams comfortable with IaC tooling.

Claudie

Claudie is designed for multi-cloud and hybrid deployments. It provisions clusters across different cloud providers from a single management interface.

Considerations

Requires a management cluster: Claudie runs on an existing Kubernetes cluster. You need Kubernetes to create Kubernetes.

For production use, this management cluster needs to be resilient since Claudie maintains state for all clusters it provisions.

Significant dependencies: The management cluster needs: - cert-manager - Multiple Claudie components (ansible, builder, claudie-operator, dynamodb, kube-eleven, kuber, minio, mongodb, scheduler, terraformer)

Operational overhead: You're responsible for keeping the management cluster healthy. If it has issues, you can't manage your provisioned clusters.

When Claudie makes sense: Organizations running clusters across multiple cloud providers who need unified management. Hybrid cloud scenarios where Hetzner is one of several providers.

Talos Linux

Talos is an immutable, secure operating system built specifically for Kubernetes.

Considerations

More complex setup: Deploying Talos on Hetzner requires: - Manually creating network components - Setting up a NAT gateway VM - Generating Talos-specific configuration files - Bootstrapping nodes individually

Different operational model: Talos has no SSH access and is managed entirely via API. This provides enhanced security but requires adapting your workflows.

When Talos makes sense: Organizations prioritizing immutable infrastructure and maximum security. Teams comfortable with the Talos operational model.

Cluster API (CAPH)

Cluster API provides declarative, Kubernetes-style management of cluster infrastructure.

Considerations

Requires a management cluster: Like Claudie, you need an existing Kubernetes cluster (often a local kind cluster) to provision your workload cluster.

Steeper learning curve: Understanding Cluster API concepts and CAPH-specific resources takes time.

Kubernetes-native approach: If you're comfortable with Kubernetes operators and CRDs, this model may feel natural.

When CAPH makes sense: Organizations standardizing on Cluster API across multiple providers. Teams that want to manage infrastructure with kubectl and GitOps.

Real-World Considerations

Development and Testing

For quick iteration, hetzner-k3s excels. Creating and destroying clusters in minutes enables: - Ephemeral test environments - Rapid prototyping - Cost-effective experimentation (pay only for what you use)

Small to Medium Production

Most teams running 1-50 node clusters on Hetzner find hetzner-k3s sufficient. You get: - High availability with multi-location masters - Autoscaling for variable workloads - Zero recurring platform fees

Large Scale (100+ nodes)

hetzner-k3s has been tested with 500 nodes and is designed to scale beyond. Clusters over 100 nodes require some configuration changes—see the Recommendations page for setup details.

Multi-Cloud Requirements

If you need clusters across AWS, GCP, and Hetzner with unified management, consider Claudie or Cluster API. hetzner-k3s is designed specifically for Hetzner.

The Bottom Line

hetzner-k3s is designed for teams who want:

Production-ready clusters in minutes, not hours
Complete control over credentials and data
No ongoing platform fees
Minimal tooling complexity

It's not the right choice if you:

Want someone else to handle all operations (consider managed services)
Need multi-cloud standardization (consider Cluster API or Claudie)
Already have extensive Terraform infrastructure (consider terraform-hcloud-kube-hetzner)

For most teams running Kubernetes on Hetzner Cloud, hetzner-k3s provides the best balance of speed, simplicity, and control.