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Published on 8 May 2025

How to Deploy a Kubernetes Cluster on Hyperstack UI: A Quick Guide

TABLE OF CONTENTS

updated

Updated: 30 May 2025

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summary
In our latest tutorial, we explore how to deploy a Kubernetes cluster using the Hyperstack web-based Console. From selecting GPU-optimised flavours to configuring your master and worker nodes, this step-by-step guide walks you through the entire setup—no command line required. You’ll learn how to choose the right environment, operating system image, Kubernetes version, and SSH key for secure access. 

We’ve officially launched Kubernetes cluster deployment via the Hyperstack web-based Console, making it easier than ever to get started with container orchestration. Now, you can deploy and manage fully optimised clusters for AI and cloud-native workloads in just a few clicks. With built-in GPU support and high-speed networking, your infrastructure is ready to handle even the most demanding tasks in minutes.

Our latest step-by-step guide walks you through the entire process of launching a Kubernetes cluster using the Hyperstack UI.

How to Deploy a Kubernetes Cluster on Hyperstack Console

To get started with our on-demand Kubernetes cluster, follow these instructions to get your Kubernetes cluster running through the Hyperstack Console:

Step 1: Begin Deployment

Head over to the Kubernetes section in your Hyperstack Console and click on "Deploy a New Cluster" to get started.

Screenshot 2025-05-30 122616

Step 2: Pick a Worker Node Flavour 

Choose a flavour that suits your workload’s needs. Hyperstack provides a range of GPU-powered node configurations ideal for Kubernetes setups targeting ML and AI workloads.

Screenshot 2025-05-30 123356

If you’re unsure, check out Flavours documentation to help you decide.

Step 3: Select Your Environment

Pick an existing environment for the cluster. If you haven’t set one up yet, you’ll need to create one first by following the steps here

Screenshot 2025-05-30 122739

Step 4: Set the Number of Worker Nodes

Specify the number of worker nodes your cluster should have; a range of 1 to 20 nodes is supported.

Screenshot 2025-05-30 122814

Step 5: Choose the OS Image

Select a compatible operating system image for Kubernetes. We recommend using: Ubuntu Server 22.04 LTS R535 CUDA 12.2

Screenshot 2025-05-30 122836

Step 6: Choose a Master Node Flavour

Pick a CPU-only flavour for your master node as it handles the control plane and won’t be billed based on resources. The supported options include:

  • n1-cpu-small
  • n1-cpu-medium
  • n1-cpu-large

Screenshot 2025-05-30 122904

Step 7: Select Kubernetes Version

Choose the version of Kubernetes you want to deploy. We recommend: v1.27.8

Screenshot 2025-05-30 122952

Step 8: Attach an SSH Key

Select an SSH key for secure access. Don’t have one? You can create a new key by following this guide.

Screenshot 2025-05-30 121627

Step 9: Deploy Your Cluster

Review your configuration, then hit Deploy to launch a Kubernetes cluster through our web console. 

Note: The cluster setup process typically takes 5 to 20 minutes, depending on the number of worker nodes and the number of clusters being deployed simultaneously.

Conclusion

Deploying a Kubernetes cluster on Hyperstack via the web-based UI is simple, fast, and built for performance. Whether you're running AI, ML or GPU-intensive workloads, Hyperstack’s intuitive console, GPU-optimised flavours, and high-speed networking make it easy to get started. With support for the latest Kubernetes versions and full SSH access, you’re fully equipped to manage containerised applications at scale.

Ready to launch your first Kubernetes cluster? Log in to the Hyperstack Console and start deploying in minutes.

Explore Related Kubernetes Resources

FAQs

What’s the minimum number of worker nodes I can deploy in a Hyperstack cluster?

You can deploy as few as 1 worker node. Hyperstack supports anywhere from 1 to 20 worker nodes per cluster, depending on your workload requirements.

Can I use GPU-powered instances for worker nodes?

Yes! Hyperstack offers GPU-optimised Kubernetes node flavours, making it ideal for machine learning, AI and other compute-heavy applications.

Which OS image is recommended for Kubernetes deployments?

We recommend using Ubuntu Server 22.04 LTS R535 CUDA 12.2, which is tested and optimised for Kubernetes and AI workloads.

Do I need a separate SSH key for my cluster?

Yes, you’ll need to select an existing SSH key or create a new one to securely access your cluster. You can follow the SSH key setup instructions provided in the Console.

Which Kubernetes version should I choose for my deployment?

While you can choose from multiple supported versions, we recommend using Kubernetes v1.27.8 for optimal stability and compatibility.

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