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Robert Zsoter
Robert Zsoter

Posted on • Originally published at Medium

kubectl-ai WebUI: A Visual Way to Use AI for Kubernetes Troubleshooting

#kubernetes #ai #kubectl #devops

kubectl-ai WebUI: A Visual Interface for AI-Powered Kubernetes Troubleshooting

If you've been experimenting with kubectl-ai for AI-assisted troubleshooting on Kubernetes, you probably know one thing already:

It’s powerful, but strictly CLI-based.

This creates a real barrier for developers, students, or platform engineers who are less comfortable with command-line workflows but still want to benefit from AI-driven explanations, log analysis, issue hunting and YAML generation.

To solve this, I built something new:

A WebUI for kubectl-ai, a browser interface that makes AI-assisted Kubernetes troubleshooting accessible to everyone.

This article explains what it does, why it helps, and how you can try it out.

WebUI for kubectl-ai

What is kubectl-ai

In short, kubectl-ai is an AI-powered plugin for kubectl that transforms natural-language questions into the appropriate Kubernetes commands.

It functions as a CLI extension that brings together:

  • Your active Kubernetes cluster context,
  • AI models (such as OpenAI, Anthropic, and others),
  • Instant command generation and analysis directly from the terminal.

If you are interested in how this works in practice, let me recommend my articles on this subject that are already available on Medium:

It helps you diagnose issues and generate solutions.

Typical kubectl-ai prompts:

"Why is my pod stuck in CrashLoopBackOff?"
"Explain the last 100 lines of logs for service X."
"Generate a correct Ingress for this Deployment."
"Why does my Deployment not scale to 5 replicas?"

It’s extremely useful, especially for debugging.

But…

The CLI-Only Limitation

For many Kubernetes newcomers, the command line is:

  • intimidating

  • error-prone

  • difficult to navigate

  • visually limited

  • slow to learn

I have noticed in my environment that 40–60% of my colleagues working with Kubernetes prefer the visual interface.

That’s why I created a browser-based experience.

Introducing: kubectl-ai WebUI

A browser UI that exposes the same kubectl-ai logic, without requiring the terminal.

No deeper CLI knowledge needed

Just open your browser → type your question → get the answer.

Same capabilities as kubectl-ai CLI

Since kubectl-ai works in the background, it provides the same functionality but on a web interface:

  • Log analysis

  • Error explanations

  • YAML generation

  • Kubernetes troubleshooting

  • Best-practice fixes

  • etc.

Works on top of your existing Kubernetes context

The WebUI simply forwards your prompt to the CLI and displays the result.

Designed for:

  • beginners

  • platform teams

  • DevOps onboarding

  • training rooms

  • troubleshooting sessions

  • classroom labs

Architecture Overview (ASCII)

Architecture overview of webui for kubectl-ai

What happens under the hood:

  • The WebUI sends your prompt to the backend

  • The backend triggers kubectl-ai

  • kubectl-ai queries Kubernetes

  • AI model generates reasoning

  • The response is displayed visually

No terminal interaction needed.

Installation (Quick Start)

Every step for use is documented in detail in the GitHub repository, so please read it.

GitHub repo: k8s-kubectl-ai-web-ui
If you find it useful, feel free to ⭐ it or share your ideas there.

Using the WebUI (Examples)

Troubleshoot a CrashLoopBackOff

"Investigate why payment-service pod is restarting."

Explain log output

"Help me understand the last 20 log lines for checkout-api."

Generate YAML

"Create a working Ingress for my deployment: checkout-api, port 8080."

Diagnose deployment issues

"Why isn't my HPA scaling above 3 replicas?"

Everything happens visually, without needing terminal commands.

Screnshoots:
With ReadOnly mode:
WebUI -
and
With "Enabled cluster changes":
WebUI -

When the WebUI Is Useful

Ideal for:

  • Who are new to Kubernetes

  • Who are not confident or comfortable with the (Linux) shell

  • team onboarding

  • demos and training, Kubernetes courses

  • situations where some teammates prefer UI over CLI

Not ideal for:

  • production environments with very strict RBAC

  • shared clusters with single API key authentication

  • environments where shell access is mandatory for auditing

Features You Can Customize

Inside the project, you can modify:

  • AI provider configuration

  • namespace filters

  • safety rules for commands

  • input sanitization

  • UI wording and layout

The project is intended to be extended (check the README file in the affected folder on the Github).

Why This Project Exists

As a Kubernetes enthusiast and AWS/K8s architect, I’ve seen again and again:

  • people want to use AI for K8s

  • kubectl-ai is great

  • but the CLI stops many people from even trying

This WebUI removes that friction and makes AI-powered troubleshooting available to the entire team, not just the CLI-native power users.

Repository

Full project:k8s-kubectl-ai-web-ui

If you find it useful, feel free to ⭐ it or share your ideas there.

About the Author

I’m Róbert Zsótér, Kubernetes & AWS architect.

If you’re into Kubernetes, EKS, Terraform, and cloud-native security, follow my latest posts here:

Let’s build secure, scalable clusters, together.

Note: Originally published on Medium Kubectl-ai WebUI: Making AI Kubernetes Debugging Browser-Friendly for Al

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