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Avinash wagh
Avinash wagh

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🚀 Day 10 of My Cloud Journey: Setting Up Kubernetes with Kind & kubectl on AWS EC2

#docker #kubernetes #aws #cloudcomputing

After getting hands-on with Docker, the next natural step in my journey was Kubernetes — the backbone of modern container orchestration.

Today, I took my first step into Kubernetes by setting up a cluster using Kind and kubectl on an AWS EC2 instance ☁️

🧩 Why Kubernetes?

While Docker helps us run containers, managing multiple containers across environments becomes complex.

👉 That’s where Kubernetes comes in:

  • Automates deployment and scaling
  • Ensures high availability
  • Manages container lifecycle efficiently

This is exactly what real-world systems use in production.

⚙️ My Setup (AWS EC2)

Instead of using local machine, I chose AWS EC2 to simulate a real-world environment.

🔹 Why EC2?

  • Closer to production setup
  • Better for remote access and testing
  • Helps understand cloud infrastructure

🛠️ Tools I Installed

1. kubectl (Kubernetes CLI)

kubectl is the command-line tool used to interact with Kubernetes clusters.

🔹 Install latest version:

curl -LO "https://dl.k8s.io/release/$(curl -L -s https://dl.k8s.io/release/stable.txt)/bin/linux/amd64/kubectl"
chmod +x kubectl
sudo mv kubectl /usr/local/bin/
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🔹 Verify:

kubectl version --client
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2. Kind (Kubernetes in Docker)

Kind allows us to run Kubernetes clusters inside Docker containers.

🔹 Install stable version:

curl -Lo ./kind https://kind.sigs.k8s.io/dl/v0.31.0/kind-linux-amd64
chmod +x ./kind
sudo mv ./kind /usr/local/bin/kind
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🔹 Verify:

kind --version
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🚀 Creating My First Kubernetes Cluster

Once both tools were installed, I created my first cluster:

kind create cluster
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⏳ It took a couple of minutes to set up everything automatically.

✅ Verifying the Cluster 

kubectl get nodes
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Output:

kind-control-plane   Ready   control-plane
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✔️ My Kubernetes cluster is now up and running!

🔥 First Deployment (Nginx)

To test everything, I deployed a simple Nginx application:

kubectl create deployment nginx --image=nginx
kubectl expose deployment nginx --type=NodePort --port=80
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Check resources:

kubectl get pods
kubectl get svc
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🌐 Accessing the Application

Since I'm using EC2, I used port forwarding:

kubectl port-forward service/nginx 8080:80
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Now accessible via:
👉 http://:8080

💡 Key Takeaways

  • kubectl is used to interact with Kubernetes
  • Kind makes it easy to run local clusters using Docker
  • Kubernetes abstracts infrastructure and manages containers efficiently
  • Setting up on EC2 gives a more real-world experience

🔄 My Learning Reflection

Today’s learning shifted my mindset from:

👉 “Running containers with Docker”
to
👉 “Orchestrating containers using Kubernetes”

This feels like a big step toward becoming a Cloud/DevOps Engineer 🚀

📘 Learning in Public

I’m documenting my journey as I transition from .NET Developer to Cloud Engineer.

🔗 LinkedIn → https://www.linkedin.com/in/avinashwagh-
🔗 GitHub → https://github.com/Avinash8600

💬 Let’s Connect

If you're learning Kubernetes, DevOps, or Cloud — let’s grow together 🙌

Would love feedback, suggestions, or tips from the community!

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