Thomas Burridge
Why Building Your Own Kubernetes Cluster is an Amazing DevOps Experience
4/26/2025

Creating your own Kubernetes cluster from scratch is one of the most educational and rewarding experiences you can have as a DevOps engineer. While managed Kubernetes offerings from major cloud providers are convenient, they abstract away many of the inner workings that are crucial for developing a deep understanding of container orchestration. Let me share why taking the DIY approach can be transformative for your skills and career.

The Learning Goldmine

When you build your own Kubernetes cluster, you're forced to understand the architecture at a fundamental level. You'll learn about:

  • Control plane components (API server, scheduler, controller manager)
  • Worker node elements (kubelet, kube-proxy, container runtime)
  • Networking models and overlay networks
  • Storage provisioning and management
  • Authentication and authorization mechanisms

This knowledge isn't just academic—it's practical wisdom that will help you troubleshoot issues, optimize performance, and make better architectural decisions regardless of which environment you ultimately work in.

Local Development Options

Before diving into cloud deployments, you might want to start with local options that let you experiment with Kubernetes on your own machine:

Kind (Kubernetes in Docker)

Kind is a lightweight tool that lets you run Kubernetes clusters using Docker containers as nodes. It's perfect for local development and testing:

  • Easy to install and configure
  • Supports multi-node clusters
  • Fast cluster creation and deletion
  • Enables testing of Kubernetes features without cloud costs
  • Great for CI/CD testing environments

Getting started is as simple as:

# Install Kind
brew install kind  # MacOS
# or
curl -Lo ./kind https://kind.sigs.k8s.io/dl/v0.20.0/kind-linux-amd64
chmod +x ./kind
sudo mv ./kind /usr/local/bin/kind  # Linux

# Create a cluster
kind create cluster --name my-cluster

Docker Desktop

If you're already using Docker Desktop for Windows or Mac, you have a built-in option to enable Kubernetes:

  • One-click Kubernetes setup in Docker Desktop settings
  • Seamless integration with your Docker environment
  • Perfect for developers new to Kubernetes
  • Minimal configuration required
  • Shares resources with your host system

To enable it, simply open Docker Desktop preferences, navigate to the Kubernetes section, and check "Enable Kubernetes". After a restart, you'll have a fully functional single-node cluster ready for experimentation.

These local options are excellent for learning and development, but they lack some of the challenges and features of production environments. Once you're comfortable with the basics, moving to a self-managed cloud solution is the next step in your learning journey.

Budget-Friendly Cloud Options

One common misconception is that running your own Kubernetes cluster must be expensive. While that can be true on major cloud providers, there are excellent budget-friendly alternatives. Kube-Hetzner is a standout example that leverages Hetzner Cloud's affordable infrastructure.

Kube-Hetzner provides Terraform modules that allow you to deploy a production-ready Kubernetes cluster on Hetzner Cloud with remarkable ease. The project combines cost-effectiveness with powerful features:

  • Automated deployment through Terraform
  • Integration with popular CNIs like Cilium
  • Support for multiple node pools
  • Automatic load balancer provisioning
  • Built-in backup solutions

What makes this option particularly attractive is the price point—you can run a small production cluster starting at around €20-30 per month, a fraction of what you'd pay on AWS, GCP, or Azure.

Developing Practical Automation Skills

Building your cluster involves working with infrastructure as code (IaC) tools like Terraform, which is a crucial skill in modern DevOps. The process teaches you to:

  1. Think declaratively about infrastructure
  2. Version control your infrastructure definitions
  3. Create repeatable deployment processes
  4. Test infrastructure changes safely
  5. Integrate with CI/CD pipelines

These automation skills transfer directly to other aspects of your DevOps work, making you more effective across the board.

Gaining Confidence in Complex Systems

There's something uniquely satisfying about seeing your cluster come alive—pods scheduling, services connecting, and workloads running—knowing that you built the foundation. This hands-on experience builds confidence that's hard to develop when working exclusively with managed services.

When issues inevitably arise, you'll have the context to dive deep into troubleshooting rather than being limited to the interfaces and diagnostics provided by managed service providers.

Real-World Scenario: Development Environment on a Budget

Let me share a practical example: Our team needed a full-featured development environment but had limited budget. Using Kube-Hetzner, we created a 3-node cluster (1 control plane, 2 workers) for approximately €40/month that supported:

  • Multiple development namespaces
  • CI/CD pipelines with ArgoCD
  • Monitoring stack with Prometheus and Grafana
  • Persistent storage for development databases
  • Testing environments for microservices

This allowed our developers to work with the same tools and workflows used in production without incurring significant infrastructure costs.

Getting Started

If you're convinced to embark on this journey, here's how to get started:

Local Development with Kind

# Create a 3-node cluster (1 control-plane, 2 workers)
cat <<EOF > kind-config.yaml
kind: Cluster
apiVersion: kind.x-k8s.io/v1alpha4
nodes:
- role: control-plane
- role: worker
- role: worker
EOF

kind create cluster --config kind-config.yaml

Cloud Deployment with Kube-Hetzner

  1. Sign up for a Hetzner Cloud account
  2. Install Terraform on your local machine
  3. Clone the terraform-hcloud-kube-hetzner repository
  4. Configure your cluster definition
  5. Run terraform apply and watch your cluster materialize

The project's documentation is comprehensive and will guide you through the process, including post-installation steps for setting up ingress controllers, storage classes, and more.

Conclusion

Building your own Kubernetes cluster isn't just about saving money—it's about investing in your skills and understanding. The knowledge gained through this process will make you a more effective DevOps engineer, even if you eventually move to managed services for production workloads.

With both local options like Kind and Docker Desktop for learning, and affordable cloud options like Kube-Hetzner for more production-like environments, there's never been a better time to dive in and start learning by doing. The experience will transform your understanding of container orchestration and provide you with valuable skills that will serve you throughout your career.

So go ahead—build that cluster, break things, fix them, and emerge with expertise that can't be gained from documentation alone.