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How to try the panel locally with Docker with Aliangboard

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

Short answer: Pull with docker pull ghcr.io/aliang-one/aliangboard:latest; then run the container with -p 8787:8787 and the aliangboard-data volume; open localhost:8787 and add a cluster. All steps.

Who it is forA developer comparing Kubernetes dashboards.

The problemInstalling a dashboard into a real cluster just to evaluate it is heavy.

The outcomeA local panel on port 8787 that keeps its data between restarts.

What you need first

  • A Kubernetes cluster and kubectl, or Docker
  • An MCP client such as Claude Code for agent access

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 for your agent

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.

Use this in your AI agent

Ask your agent

Using the Deduped MCP, get the setup steps for aliang-one/aliangboard and "Try the panel locally with Docker"

Add Deduped to Claude Code once

claude mcp add --transport http deduped https://dedupedai.com/mcp

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