What is K3d? What is K3s? and What is the Difference Between Both?

Introduction
What is K3s?
- Features of K3s
- Benefits of K3s
- Use Cases of K3s
What is K3d?
- Features of K3d
- Benefits of K3d
- Use Cases of K3d
Key Differences Between K3s and K3d
K3s vs. K3d: Which One Should You Choose?
How to Install K3s and K3d?
Frequently Asked Questions (FAQs)

1. Introduction

Kubernetes is the leading container orchestration tool, but its complexity and resource demands can be overwhelming. This led to the creation of K3s and K3d, two lightweight alternatives designed to simplify Kubernetes deployment and management.

If you're wondering "What is K3d? What is K3s? and What is the difference between both?", this in-depth guide will provide a clear understanding of these tools, their features, benefits, and use cases.

By the end, you'll be able to decide which one is best suited for your needs.

2. What is K3s?

K3s is a lightweight, certified Kubernetes distribution developed by Rancher Labs. It is designed to provide a simplified, resource-efficient alternative to the full-fledged Kubernetes.

Features of K3s

Single Binary (~100MB): Unlike traditional Kubernetes, K3s is packaged as a single binary, making installation and upgrades easier.
Reduced Dependencies: Uses SQLite instead of etcd (can be configured to use etcd if needed).
Optimized for Edge Computing: Perfect for IoT, ARM-based devices, and small clusters.
Lower Resource Usage: Requires fewer CPU and RAM resources compared to full Kubernetes.
Embedded Networking & Storage Solutions: Supports Flannel, Traefik, and other lightweight networking solutions.
Supports Multi-Node Clusters: Works for both single-node and multi-node deployments.

Benefits of K3s

Easy to install and configure.
Requires less system overhead.
Great for production workloads in resource-constrained environments.
Secure by default with automated certificate management.
Works on ARM devices like Raspberry Pi.

Use Cases of K3s

Edge Computing: Running Kubernetes on low-power devices.
Development Environments: Lightweight clusters for testing and CI/CD.
IoT Applications: Deploying Kubernetes in IoT-based infrastructures.
Resource-Constrained Kubernetes Clusters: When you need Kubernetes but have limited hardware.

3. What is K3d?

K3d is a wrapper that runs K3s inside Docker containers, making it even lighter and easier to manage. It is a great tool for local development and CI/CD testing.

Features of K3d

Runs K3s inside Docker containers instead of directly on the host machine.
Multi-cluster support on a single system.
Fast cluster creation and deletion (useful for testing different configurations).
Lower resource usage as it leverages Docker's networking and storage.
CLI Tool for Easy Cluster Management (create, delete, list clusters easily).

Benefits of K3d

Super fast setup (can spin up a Kubernetes cluster in seconds).
Easy cleanup (no need to uninstall Kubernetes, just stop the container).
Portable and lightweight (since it runs inside Docker, it can be used anywhere Docker is supported).
Ideal for CI/CD Pipelines (helps test Kubernetes workloads without setting up a full cluster).

Use Cases of K3d

Local Kubernetes Development: Quickly spin up and test applications locally.
CI/CD Pipelines: Automate Kubernetes testing without setting up dedicated clusters.
Multiple Isolated Clusters: Run different Kubernetes versions on the same machine.
Testing Kubernetes Configurations: Experiment with different cluster settings easily.

4. Key Differences Between K3s and K3d

Feature	K3s	K3d
Definition	Lightweight Kubernetes distribution	Tool to run K3s in Docker
Installation	Installed directly on Linux/macOS/WSL	Runs inside Docker
Use Case	Production and edge computing	Local development and testing
Resource Usage	Lower than full Kubernetes	Even lighter (since it's inside Docker)
Persistence	Runs as a standalone system	Clusters exist only while Docker is running

5. K3s vs. K3d: Which One Should You Choose?

Choose K3s if you need a lightweight production Kubernetes cluster for edge computing, IoT, or resource-limited environments.
Choose K3d if you need a fast, ephemeral Kubernetes cluster for development, testing, and CI/CD pipelines.

If you're working in a local development environment and need quick setup/teardown, K3d is the best choice. For deploying real workloads in production, go with K3s.

6. How to Install K3s and K3d?

Installing K3s

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

Installing K3d

curl -s https://raw.githubusercontent.com/k3d-io/k3d/main/install.sh | bash

To create a K3d cluster:

k3d cluster create mycluster

7. Frequently Asked Questions (FAQs)

1. Is K3s a full Kubernetes distribution?

Yes, K3s is a fully certified Kubernetes distribution but optimized for lightweight deployment.

2. Does K3s support multi-node clusters?

Yes, K3s supports multi-node clusters, although it is optimized for single-node setups.

3. Can K3d be used in production?

No, K3d is meant for local development and testing, not production workloads.

4. What are the hardware requirements for K3s?

K3s requires at least 512MB RAM and 1 CPU, but 1GB RAM is recommended.

5. Can I use K3s on Raspberry Pi?

Yes, K3s is optimized for ARM devices like Raspberry Pi.

6. Does K3d require Docker?

Yes, K3d runs K3s inside Docker containers, so Docker must be installed.

7. How do I delete a K3d cluster?

k3d cluster delete mycluster

8. Can I use K3s without root access?

Yes, but some configurations require additional permissions.

9. How do I uninstall K3s?

/usr/local/bin/k3s-uninstall.sh

10. Is K3d faster than Minikube?

Yes, K3d is generally faster than Minikube because it leverages K3s and Docker.

11. how many k3d cluster i can create?

The number of K3d clusters you can create depends on:

1. System Resources (CPU, RAM, Disk)

Since K3d runs K3s inside Docker containers, each cluster consumes CPU, RAM, and disk storage.
More clusters mean higher resource consumption.
If you have a high-performance machine (e.g., 16GB RAM, multi-core CPU), you can run multiple clusters efficiently.

2. Docker Limitations

K3d creates Docker containers for each cluster.
Docker itself does not have a strict limit, but excessive containers may impact system performance.

3. Networking Constraints

Each K3d cluster gets assigned a Docker network.
Too many networks might cause conflicts or performance issues.

4. Port Assignments

Each K3d cluster requires unique port mappings.
If ports overlap, conflicts can occur.

Practical Limits

On a typical developer machine (8GB–16GB RAM), you can comfortably create 3–5 K3d clusters.
On a powerful workstation or cloud VM (32GB+ RAM, high CPU cores), you can create 10+ clusters.

Checking Running Clusters

To list all active K3d clusters:

k3d cluster list

Would you like help optimizing K3d for running multiple clusters?

12. How to chage k3d clustor?

Changing a K3d cluster can mean different things based on what exactly you want to modify. Below are common scenarios and how to achieve them:

1. Change the Context to a Different K3d Cluster

If you have multiple K3d clusters running, you can switch between them using:

kubectl config use-context k3d-<cluster-name>

To list all available contexts:

kubectl config get-contexts

2. Modify an Existing K3d Cluster (Not Recommended)

K3d does not support modifying a running cluster directly. However, you can delete and recreate the cluster with updated configurations.

For example, if you want to:

Change the number of worker nodes
Modify the network settings
Enable additional ports

You need to delete and recreate the cluster.

3. Delete and Recreate a K3d Cluster with New Settings

Step 1: Delete the Existing Cluster

k3d cluster delete mycluster

Step 2: Create a New Cluster with Desired Changes

For example, to create a new cluster with 3 worker nodes and a specific port mapping:

k3d cluster create mycluster --agents 3 -p "8080:80@loadbalancer"

4. Modify a Cluster’s Node Configuration

K3d nodes run inside Docker containers, so you can make temporary changes using Docker commands:

Change CPU and Memory Limits

docker update --cpus=2 --memory=4g k3d-mycluster-server-0

(Note: Changes will be lost when you restart the cluster.)

5. Add a New Node to an Existing Cluster

If you want to scale your cluster by adding nodes:

k3d node create new-agent --cluster mycluster --role agent

Would you like help with a specific change in your K3d cluster? 🚀

13. Understanding K3d Nodes on a Local Ubuntu Laptop ?

Understanding K3d Nodes on a Local Ubuntu Laptop

In Kubernetes, a node is a machine that runs workloads (Pods). When using K3d, nodes are Docker containers that simulate real Kubernetes nodes. This allows you to run a Kubernetes cluster entirely inside Docker, making it lightweight and easy to manage.

Key Node Types in K3d

K3d creates different types of nodes inside Docker:

Server Node (Control Plane)
- This is the Kubernetes master node that manages the cluster.
- It handles scheduling, API requests, and cluster control.
- Example: k3d-mycluster-server-0
Agent Nodes (Worker Nodes)
- These nodes run the actual applications (Pods).
- More agent nodes = better workload distribution.
- Example: k3d-mycluster-agent-0, k3d-mycluster-agent-1
Load Balancer (Optional)
- Balances traffic across multiple nodes.
- Helps simulate production-like networking.
- Example: k3d-mycluster-loadbalancer

Example: Running a Multi-Node K3d Cluster on Ubuntu

1. Create a 3-Node K3d Cluster

k3d cluster create mycluster --servers 1 --agents 2

This creates:
- 1 Server Node (k3d-mycluster-server-0)
- 2 Agent Nodes (k3d-mycluster-agent-0, k3d-mycluster-agent-1)

2. Check Running Nodes

kubectl get nodes

Output:

NAME                         STATUS   ROLES    AGE   VERSION
k3d-mycluster-server-0       Ready    master   1m    v1.27.3+k3s1
k3d-mycluster-agent-0        Ready    <none>   1m    v1.27.3+k3s1
k3d-mycluster-agent-1        Ready    <none>   1m    v1.27.3+k3s1

3. Deploy an App on Agent Nodes

kubectl apply -f https://k8s.io/examples/application/deployment.yaml

This schedules Pods on agent nodes automatically.

4. Check Where Pods Are Running

kubectl get pods -o wide

You will see Pods running on agent nodes (k3d-mycluster-agent-0, k3d-mycluster-agent-1).

Why Use K3d Nodes on a Local Ubuntu Laptop?

✅ Lightweight Kubernetes: Runs entirely in Docker without heavy VM overhead.
✅ Fast Cluster Setup: Create and delete clusters quickly for testing.
✅ CI/CD & Development: Simulates Kubernetes locally before deploying to production.
✅ Multi-Node Simulation: Helps test scalability and failover scenarios.

Would you like help with a specific K3d node setup on your laptop? 🚀

Conclusion

Both K3s and K3d serve different purposes. K3s is great for lightweight production clusters, while K3d is perfect for local development and testing. By understanding their differences, you can choose the right tool for your Kubernetes needs.

What is the Difference Between K3s and K3d