# AI use cases for Aliangboard (aliang-one/aliangboard)

Repo: [aliang-one/aliangboard](https://github.com/aliang-one/aliangboard) | Use cases: 3 | Page: https://dedupedai.com/use-cases/aliang-one-aliangboard/

AliangBoard is an open-source Kubernetes management panel with a Vue 3 frontend, a Node API gateway, an Agent workbench and an MCP server that lets LLMs read, write and operate your clusters.

This file holds every use case of this repo. Each one starts with a "## " heading and ends with its URL.

- Deploy a Kubernetes web panel into your cluster: https://dedupedai.com/use-cases/aliang-one-aliangboard/deploy-k8s-panel-in-cluster/
- Ask an agent to read logs and roll back releases: https://dedupedai.com/use-cases/aliang-one-aliangboard/operate-cluster-from-claude-code/
- Try the panel locally with Docker: https://dedupedai.com/use-cases/aliang-one-aliangboard/run-panel-locally-with-docker/

## How to deploy a Kubernetes web panel into your cluster with Aliangboard

Repo: [aliang-one/aliangboard](https://github.com/aliang-one/aliangboard) | Difficulty: Intermediate | Time: 30 minutes | Basis: From the README

Apply one manifest to get a multi-cluster panel with exec, port-forward and debug containers.

**Who it is for:** A platform engineer who wants a lightweight UI for a small team's clusters.

**The problem:** kubectl alone is slow for browsing workloads, logs and events.

**The outcome:** A web panel on a NodePort covering the full resource lifecycle.

### Steps

1. Run `kubectl apply -f https://raw.githubusercontent.com/aliang-one/aliangboard/main/deployment.yaml`
2. Find the port with `kubectl -n aliangboard get svc aliangboard`
3. Open the panel on the NodePort and sign in
4. Browse namespaces and workloads

### Prompt to paste into your agent

```text
Deploy aliang-one/aliangboard with `kubectl apply -f https://raw.githubusercontent.com/aliang-one/aliangboard/main/deployment.yaml`, read the NodePort, and confirm the panel lists the cluster's namespaces.
```

### Caveat

The panel gets whatever RBAC the manifest grants, so read the permissions before applying to production.

Risk, remote script: The manifest is applied straight from GitHub, so review deployment.yaml before granting it cluster access.

Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/

URL: https://dedupedai.com/use-cases/aliang-one-aliangboard/deploy-k8s-panel-in-cluster/

## How to ask an agent to read logs and roll back releases with Aliangboard

Repo: [aliang-one/aliangboard](https://github.com/aliang-one/aliangboard) | Difficulty: Advanced | Time: 30 minutes | Basis: From the README

Connect the built-in MCP server so an LLM can read pod logs, debug containers or roll back in plain language.

**Who it is for:** An on-call engineer who wants to triage a failing deployment by asking questions.

**The problem:** Remembering kubectl incantations under pressure slows incident response.

**The outcome:** Natural-language cluster operations through your MCP client.

### Steps

1. Run AliangBoard and create an access token
2. Add it with `claude mcp add --transport http aliangboard {HOST}/mcp` and an Authorization header
3. Ask the agent to show logs for a failing pod
4. Approve any write action carefully

### Prompt to paste into your agent

```text
Through the aliangboard MCP server, find pods in <namespace> that are not Ready, show their last 50 log lines, and propose a fix. Do not change resources without my confirmation.
```

### Caveat

The MCP server can write and operate the cluster, so scope its token before connecting an agent.

Risk, credentials: The bearer token lets the agent read and write cluster resources.

Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/

URL: https://dedupedai.com/use-cases/aliang-one-aliangboard/operate-cluster-from-claude-code/

## How to try the panel locally with Docker with Aliangboard

Repo: [aliang-one/aliangboard](https://github.com/aliang-one/aliangboard) | Difficulty: Intermediate | Time: 15 minutes | Basis: From the README

Run the published image with a persistent volume to evaluate the panel before installing in-cluster.

**Who it is for:** A developer comparing Kubernetes dashboards.

**The problem:** Installing a dashboard into a real cluster just to evaluate it is heavy.

**The outcome:** A local panel on port 8787 that keeps its data between restarts.

### Steps

1. Pull with `docker pull ghcr.io/aliang-one/aliangboard:latest`
2. Run the container with -p 8787:8787 and the aliangboard-data volume
3. Open localhost:8787 and add a cluster
4. Explore the namespace and workload overviews

### Prompt to paste into your agent

```text
Run ghcr.io/aliang-one/aliangboard:latest on port 8787 with a data volume, add <kubeconfig context>, and confirm the namespace overview loads.
```

### Caveat

The public demo is shared with other visitors, so never put real cluster details into it.

Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/

URL: https://dedupedai.com/use-cases/aliang-one-aliangboard/run-panel-locally-with-docker/