Most Kubernetes tutorials show you the easy path with automated tools and managed services. This guide takes you down the hard road—building a Kubernetes cluster from scratch using manual setup techniques.
This deep dive is for DevOps engineers, system administrators, and infrastructure specialists who want to understand every component that makes Kubernetes tick. You’ll gain the knowledge needed to troubleshoot complex cluster issues, make informed architecture decisions, and master the platform at its core.
We’ll start by breaking down Kubernetes architecture and preparing your infrastructure for manual Kubernetes deployment. You’ll learn to install and configure the control plane components piece by piece, then bootstrap worker nodes from the ground up.
Next, we’ll tackle cluster networking setup—one of the trickiest parts of hand-built Kubernetes clusters. You’ll implement pod networking, configure service discovery, and ensure all components communicate properly.
By the end, you’ll have a fully functional Kubernetes cluster built entirely by hand, plus the deep understanding that comes only from assembling each component yourself.
Understanding Kubernetes Architecture for Manual Deployment
Master Node Components and Their Critical Functions
The master node serves as the brain of your Kubernetes cluster from scratch, housing essential control plane components that orchestrate all cluster operations. The API server acts as the central communication hub, handling all REST requests and serving as the primary interface for kubectl commands and internal component interactions. The etcd key-value store maintains the entire cluster state, storing configuration data, secrets, and metadata that drives your manual Kubernetes deployment. The scheduler intelligently places pods on appropriate worker nodes based on resource requirements and constraints, while the controller manager runs various controllers that maintain desired cluster state through continuous reconciliation loops.
Worker Node Components and Communication Patterns
Worker nodes execute the actual application workloads through a carefully orchestrated set of components that communicate seamlessly with the control plane. The kubelet serves as the primary node agent, continuously polling the API server for pod specifications and ensuring containers run as expected on the local node. The kube-proxy manages network rules and load balancing for services, implementing iptables or IPVS rules to route traffic correctly across your hand-built Kubernetes cluster. The container runtime (Docker, containerd, or CRI-O) handles the low-level container lifecycle operations, pulling images and managing container execution. Communication flows from the API server to kubelets via secure TLS connections, while kube-proxy watches for service and endpoint changes to update network routing rules dynamically.
Essential Network Requirements for Cluster Connectivity
Proper network configuration forms the backbone of successful Kubernetes manual setup, requiring careful planning of IP address ranges and routing policies. Your cluster needs three distinct network segments: the node network for inter-node communication, the pod network (typically 10.244.0.0/16) for container-to-container communication, and the service network (usually 10.96.0.0/12) for stable service discovery. Each node must reach every other node directly, while pods require connectivity across the entire cluster through a Container Network Interface (CNI) plugin like Flannel, Calico, or Weave. Port requirements include 6443 for the API server, 2379-2380 for etcd, 10250 for kubelet API, and 30000-32767 for NodePort services in your Kubernetes infrastructure preparation.
Storage Considerations for Persistent Data Management
Storage planning becomes critical when building Kubernetes clusters by hand, as persistent data requirements vary significantly across different workloads and applications. Local storage works well for testing but lacks the durability needed for production deployments, making network-attached storage or cloud-based solutions more suitable for critical data. Persistent Volume (PV) and Persistent Volume Claim (PVC) abstractions allow applications to request storage resources without knowing underlying infrastructure details. Storage classes define different tiers of storage with varying performance characteristics, from high-IOPS SSDs for databases to cost-effective spinning disks for archival data. Your Kubernetes control plane configuration must account for storage driver installation, volume provisioning policies, and backup strategies to ensure data persistence across pod restarts and node failures.
Preparing Your Infrastructure for Manual Kubernetes Setup
Hardware and Virtual Machine Specifications
Your Kubernetes manual setup demands robust infrastructure planning before diving into the actual deployment process. For a production-ready cluster, allocate at least 2 CPU cores and 4GB RAM per control plane node, while worker nodes need minimum 1 CPU core and 2GB RAM. Virtual machines work perfectly for testing environments, but bare metal servers deliver superior performance for production workloads. Consider using three control plane nodes for high availability, ensuring odd numbers prevent split-brain scenarios. Storage requirements vary significantly based on your workload expectations, but provision at least 20GB disk space per node for system components and container images. Network connectivity between nodes requires low latency and high bandwidth – aim for gigabit connections in production environments.
Operating System Configuration and Updates
Starting with a fresh Linux installation creates the cleanest foundation for your Kubernetes infrastructure preparation. Ubuntu 20.04 LTS, CentOS 8, or Red Hat Enterprise Linux provide excellent stability and community support for manual Kubernetes deployment scenarios. Disable swap completely across all nodes since Kubernetes requires this for optimal memory management and performance. Configure your package repositories to ensure consistent software versions during installation processes. Set up SSH key-based authentication between nodes to streamline administrative tasks and component communication. Update all system packages to their latest versions, paying special attention to kernel updates that might affect container runtime functionality. Configure proper hostname resolution either through DNS or local hosts files, ensuring each node can resolve others by name rather than IP addresses alone.
Container Runtime Installation and Configuration
Container runtime selection significantly impacts your cluster’s performance and compatibility with Kubernetes components installation. Docker remains popular, but containerd offers better integration with Kubernetes architecture and consumes fewer system resources. Install your chosen runtime using official repositories rather than distribution packages to maintain version control. Configure the container runtime to use systemd as the cgroup driver, matching Kubernetes expectations for process management. Create proper runtime configuration files specifying registry mirrors, insecure registries, and storage drivers based on your environment requirements. Verify runtime functionality by pulling and running test containers before proceeding with control plane bootstrap. Configure runtime logging to integrate with your monitoring solutions, ensuring container logs remain accessible through standard Kubernetes logging mechanisms.
Installing and Configuring the Control Plane Components
Setting Up etcd for Cluster State Management
The etcd cluster serves as Kubernetes’ distributed key-value store, maintaining all cluster state and configuration data. Install etcd on multiple control plane nodes for high availability, configuring secure client-server communication with TLS certificates. Create the etcd service configuration file specifying cluster members, data directories, and peer URLs. Start etcd services across nodes and verify cluster health using etcdctl cluster-health. This distributed database ensures your Kubernetes control plane components can reliably store and retrieve critical cluster information during manual Kubernetes deployment.
Configuring the API Server for Cluster Communication
The kube-apiserver acts as the central communication hub for your Kubernetes cluster from scratch setup. Download the binary and create a systemd service file with essential parameters including etcd endpoints, service account key files, and admission controllers. Configure authentication mechanisms, authorization policies, and enable audit logging for security. The API server validates and processes all REST requests, serving as the gateway between kubectl commands and cluster resources. Proper configuration ensures secure, efficient communication between all Kubernetes components during your manual setup process.
Installing the Controller Manager for Resource Orchestration
The kube-controller-manager runs essential control loops that regulate cluster state through continuous reconciliation. Download the binary and configure it to connect with your API server using service account credentials and cluster signing certificates. Enable controllers like deployment, replicaset, and node controllers by specifying them in the service configuration. The controller manager monitors desired vs actual state, automatically creating, updating, or deleting resources to maintain cluster health. This component orchestrates resource management across your hand-built Kubernetes cluster infrastructure.
Setting Up the Scheduler for Pod Placement
The kube-scheduler intelligently assigns pods to worker nodes based on resource requirements, constraints, and policies. Install the scheduler binary and create a service configuration pointing to your API server endpoint with appropriate authentication credentials. Configure scheduling policies, priority classes, and resource quotas to optimize pod placement decisions. The scheduler evaluates node capacity, affinity rules, and taints before making placement decisions. This critical component ensures efficient resource utilization across your manually configured Kubernetes worker nodes bootstrap setup.
Securing Control Plane Components with Certificates
Certificate-based authentication secures communication between all Kubernetes control plane configuration components. Generate a Certificate Authority (CA) using OpenSSL or cfssl, then create individual certificates for etcd, API server, controller manager, and scheduler. Configure each component with appropriate certificate files, private keys, and CA certificates in their service definitions. Implement proper certificate rotation policies and secure storage mechanisms. Client certificates authenticate components while server certificates encrypt communication channels, establishing a robust security foundation for your manual Kubernetes deployment infrastructure.
Bootstrapping Worker Nodes from Scratch
Installing kubelet for Node Agent Functionality
The kubelet serves as the primary node agent on each Kubernetes worker node, communicating with the API server and managing container lifecycle operations. Download the kubelet binary matching your cluster version and place it in /usr/local/bin/ with executable permissions. Create a systemd service file at /etc/systemd/system/kubelet.service that specifies the kubelet configuration path, cluster DNS settings, and container runtime endpoint. Configure kubelet through /etc/kubernetes/kubelet/kubelet-config.yaml with essential parameters including cluster domain, authentication settings, and resource management policies. The kubelet requires proper certificates for secure communication with the control plane components.
Configuring kube-proxy for Service Networking
Kube-proxy handles service discovery and load balancing across pods in your Kubernetes cluster from scratch setup. Install the kube-proxy binary alongside kubelet and create its dedicated systemd service configuration. Generate a kubeconfig file for kube-proxy authentication, specifying the API server endpoint and appropriate certificates. Configure kube-proxy through /etc/kubernetes/kube-proxy/kube-proxy-config.yaml, selecting your preferred proxy mode – iptables offers broad compatibility while IPVS provides better performance for larger clusters. Set cluster CIDR ranges to match your pod networking configuration, ensuring proper traffic routing between services and backend pods across worker nodes.
Joining Worker Nodes to the Control Plane
Before joining worker nodes to your manual Kubernetes deployment, verify that kubelet and kube-proxy services are running correctly on each node. Copy the cluster CA certificate and create appropriate kubeconfig files for both kubelet and kube-proxy components. Configure node labels and taints as needed for workload scheduling requirements. Start the kubelet service first, which automatically registers the node with the API server using the configured authentication credentials. Monitor node status through kubectl get nodes from the control plane to confirm successful registration. The node should transition from “NotReady” to “Ready” status once the container network interface plugin is properly configured and all components communicate successfully with the control plane.
Implementing Cluster Networking Solutions
Understanding Container Network Interface Requirements
Your manual Kubernetes deployment needs proper CNI implementation to enable pod communication across nodes. CNI plugins handle IP address allocation, routing configuration, and network policy enforcement. Popular options include Calico for advanced networking features, Flannel for simplicity, or Weave Net for ease of setup. Each plugin requires specific kernel modules and iptables rules to function correctly.
Installing and Configuring CNI Plugins
Download your chosen CNI plugin binaries to /opt/cni/bin/ on all nodes. Create the CNI configuration file in /etc/cni/net.d/ with network CIDR blocks that don’t overlap with your node subnets. For Calico, install the manifest using kubectl apply and configure BGP peering if needed. Flannel requires setting up the backend type (VXLAN or host-gw) based on your infrastructure. Verify plugin installation by checking kubelet logs and ensuring network interface creation.
Validating Pod-to-Pod Communication
Deploy test pods on different nodes to verify cross-node communication works properly. Use simple nginx containers and attempt to reach one pod from another using ping or curl commands. Check that each pod receives a unique IP address from the configured CIDR range. Examine the routing tables and bridge configurations to ensure packets flow correctly between nodes through your CNI solution.
Testing Service Discovery and Load Balancing
Create a deployment with multiple replicas and expose it through a ClusterIP service to test internal load balancing. Deploy a test pod and use nslookup or dig commands to verify DNS resolution works for service names. Test external access by creating a NodePort service and accessing it from outside the cluster. Validate that traffic distributes evenly across pod replicas and that failed pods get removed from service endpoints automatically.
Validating Your Hand-Built Kubernetes Cluster
Running Connectivity Tests Between Components
Testing connectivity between your hand-built Kubernetes cluster components ensures proper communication across the control plane and worker nodes. Start by verifying etcd cluster health using etcdctl cluster-health and checking API server accessibility from all nodes. Test pod-to-pod communication across different worker nodes to validate your networking setup. Use kubectl get nodes and kubectl get componentstatuses to confirm all components register correctly. Network connectivity tests should include DNS resolution within the cluster and external traffic routing.
Deploying Sample Applications for Functionality Testing
Deploy a simple nginx pod and service to test basic Kubernetes functionality in your manual setup. Create a multi-pod application that spans multiple worker nodes to verify scheduling and load distribution. Test persistent volume claims and storage classes to ensure your storage backend integrates properly. Deploy applications that require secrets and configmaps to validate these core features. Run a DaemonSet to confirm it deploys across all worker nodes, and test horizontal pod autoscaling if you’ve configured metrics collection.
Monitoring Cluster Health and Performance Metrics
Monitor your hand-built Kubernetes cluster using native tools like kubectl top nodes and kubectl top pods to track resource utilization. Check kubelet logs on each worker node and API server logs on control plane nodes for any errors or warnings. Implement basic monitoring by deploying metrics-server to collect resource metrics from your manually configured nodes. Watch for certificate expiration dates, especially for etcd and API server certificates you generated during setup. Set up log aggregation to centralize troubleshooting across your distributed cluster components.
Building a Kubernetes cluster from scratch gives you an unmatched understanding of how this powerful orchestration platform actually works. You’ve walked through setting up the control plane, configuring worker nodes, and implementing networking solutions that connect everything together. This hands-on approach means you now know exactly what happens behind the scenes when you run kubectl commands or deploy applications to your cluster.
The knowledge you’ve gained by manually configuring each component will serve you well when troubleshooting production issues or optimizing cluster performance. While managed Kubernetes services are great for most use cases, there’s real value in understanding the nuts and bolts of etcd, the API server, and how pods communicate across nodes. Take what you’ve learned here and apply it to your next project – whether that’s setting up a development environment or diving deeper into Kubernetes networking and security configurations.
