Kubernetes Basics on RamNode

Server Requirements

• • RamNode VPS (2GB+ RAM minimum)
• • Ubuntu 20.04/22.04 or CentOS 7+
• • At least 2 CPU cores
• • 20GB+ disk space
• • Docker installed

Knowledge Requirements

• • Docker fundamentals
• • Basic Linux administration
• • YAML syntax understanding
• • Networking concepts
• • Command line proficiency

🎯 Purpose

While Docker manages individual containers, Kubernetes orchestrates entire fleets of containers across multiple servers, ensuring high availability, scalability, and efficient resource utilization.

🏗️ Architecture

Kubernetes uses a master-worker architecture with a control plane managing worker nodes that run your containerized applications in pods.

⚙️ Key Features

Automatic scaling, load balancing, self-healing, rolling updates, service discovery, and configuration management out of the box.

🏎️ Resource Efficiency

KVM-based virtualization with dedicated resources ensures consistent performance, eliminating "noisy neighbor" issues common in shared hosting.

📈 Scalability

Easily add more RamNode instances to expand your Kubernetes cluster as your applications grow.

💰 Cost-Effectiveness

Competitive pricing allows running multiple nodes without breaking the budget, perfect for both learning and production use.

🌐 Network Performance

Low-latency network infrastructure ensures fast communication between cluster nodes, crucial for optimal performance.

🏗️ Pods

The smallest deployable unit. Contains one or more containers sharing storage and network resources.

🖥️ Nodes

Worker machines in your cluster. Each RamNode VPS can serve as a Kubernetes node running pods.

🌐 Cluster

A set of nodes grouped together, allowing Kubernetes to distribute applications across multiple machines.

🚀 Deployments

Describe desired state for applications, managing replicas, updates, and rollbacks automatically.

🔗 Services

Provide stable network endpoints and load balancing for accessing applications.

🔧 ConfigMaps & Secrets

Manage configuration data and sensitive information separately from application code.

K3s (Recommended for Beginners)

Lightweight, easy to install, includes everything in a single binary. Perfect for development or small production workloads.

kubeadm (Standard Kubernetes)

Official Kubernetes installer providing full upstream compatibility. Best for learning standard Kubernetes or multi-node clusters.

MicroK8s

Canonical's lightweight distribution with useful addons. Great for development and testing environments.

curl -sfL https://get.k3s.io | sh -

sudo kubectl get nodes

sudo cat /etc/rancher/k3s/k3s.yaml

mkdir -p ~/.kube
sudo cp /etc/rancher/k3s/k3s.yaml ~/.kube/config
sudo chown $(id -u):$(id -g) ~/.kube/config

curl -fsSL https://packages.cloud.google.com/apt/doc/apt-key.gpg | sudo gpg --dearmor -o /etc/apt/keyrings/kubernetes-archive-keyring.gpg
echo "deb [signed-by=/etc/apt/keyrings/kubernetes-archive-keyring.gpg] https://apt.kubernetes.io/ kubernetes-xenial main" | sudo tee /etc/apt/sources.list.d/kubernetes.list

sudo apt-get update
sudo apt-get install -y kubelet kubeadm kubectl
sudo apt-mark hold kubelet kubeadm kubectl

sudo kubeadm init --pod-network-cidr=10.244.0.0/16

mkdir -p $HOME/.kube
sudo cp -i /etc/kubernetes/admin.conf $HOME/.kube/config
sudo chown $(id -u):$(id -g) $HOME/.kube/config

kubectl apply -f https://raw.githubusercontent.com/flannel-io/flannel/master/Documentation/kube-flannel.yml

apiVersion: apps/v1
kind: Deployment
metadata:
 name: nginx-deployment
spec:
 replicas: 3
 selector:
 matchLabels:
 app: nginx
 template:
 metadata:
 labels:
 app: nginx
 spec:
 containers:
 - name: nginx
 image: nginx:latest
 ports:
 - containerPort: 80
 resources:
 requests:
 memory: "64Mi"
 cpu: "50m"
 limits:
 memory: "128Mi"
 cpu: "100m"

kubectl apply -f nginx-deployment.yaml

apiVersion: v1
kind: Service
metadata:
 name: nginx-service
spec:
 selector:
 app: nginx
 ports:
 - protocol: TCP
 port: 80
 targetPort: 80
 type: NodePort

kubectl apply -f nginx-service.yaml

# View all pods
kubectl get pods
# Check service status
kubectl get services
# Get service details
kubectl describe service nginx-service

# Cluster information
kubectl cluster-info
# Node information
kubectl get nodes -o wide
# Resource usage (requires metrics-server)
kubectl top nodes
kubectl top pods

# Create resources from files
kubectl apply -f deployment.yaml
# Delete resources
kubectl delete -f deployment.yaml
# Scale deployments
kubectl scale deployment nginx-deployment --replicas=5
# Rolling updates
kubectl set image deployment/nginx-deployment nginx=nginx:1.21
# Rollback
kubectl rollout undo deployment/nginx-deployment

# Describe resources for debugging
kubectl describe pod <pod-name>
kubectl describe service <service-name>
# View logs
kubectl logs <pod-name>
kubectl logs -f <pod-name> # Follow logs
# Execute commands in pods
kubectl exec -it <pod-name> -- /bin/bash
# Port forwarding for testing
kubectl port-forward pod/<pod-name> 8080:80

resources:
 requests:
 memory: "128Mi"
 cpu: "100m"
 limits:
 memory: "256Mi"
 cpu: "200m"

livenessProbe:
 httpGet:
 path: /health
 port: 8080
 initialDelaySeconds: 30
 periodSeconds: 10
readinessProbe:
 httpGet:
 path: /ready
 port: 8080
 initialDelaySeconds: 5
 periodSeconds: 5

kubectl apply -f https://github.com/kubernetes-sigs/metrics-server/releases/latest/download/components.yaml

# View resource usage
kubectl top nodes
kubectl top pods --all-namespaces
# Monitor events
kubectl get events --sort-by=.metadata.creationTimestamp
# Watch resource changes
kubectl get pods -w

# Backup cluster configuration
kubectl get all --all-namespaces -o yaml > cluster-backup.yaml
# For etcd backup (kubeadm clusters)
sudo ETCDCTL_API=3 etcdctl snapshot save /backup/etcd-snapshot.db \
 --endpoints=https://127.0.0.1:2379 \
 --cacert=/etc/kubernetes/pki/etcd/ca.crt \
 --cert=/etc/kubernetes/pki/etcd/server.crt \
 --key=/etc/kubernetes/pki/etcd/server.key

# Scale up
kubectl scale deployment nginx-deployment --replicas=5
# Scale down
kubectl scale deployment nginx-deployment --replicas=2

apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
 name: nginx-hpa
spec:
 scaleTargetRef:
 apiVersion: apps/v1
 kind: Deployment
 name: nginx-deployment
 minReplicas: 3
 maxReplicas: 10
 metrics:
 - type: Resource
 resource:
 name: cpu
 target:
 type: Utilization
 averageUtilization: 70

kubectl apply -f hpa.yaml

Pod Startup Issues

Networking Problems

Resource Constraints

Storage Problems