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Aladdin

Aladdin

AlayaNeW

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2,703 installs
| (2) | Free
Optimize computing power for AI coding.
Installation
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Aladdin

Aladdin is an AI computing extension suite designed for VS Code and compatible IDEs. It seamlessly connects VKS/CCI cloud resources from the Alaya NeW platform to your local development environment, enabling direct access to remote GPU/NPU resources from within your familiar editor. With Aladdin, developers can efficiently write code, debug applications, run scripts, and train AI models using cloud-based computing power.

The suite consists of two core extensions:

  • Aladdin (Local Extension): Responsible for account authentication, AI data center switching, image repository configuration, Workshop/CCI lifecycle management, and remote extension deployment.
  • Aladdin Remote (Remote Extension): Running Workshop or CCI, provides core computing power capabilities such as GPU Debug, GPU Run, Run Shell, Run Task, session management, log viewing, terminal access, external access, and MCP tools.

🚀 Key Features

1. Local Resource Management

  • Account & Data Center: Supports logging in and out of Aladdin accounts;Switch freely between different AI data centers.
  • Product View Switching: freely switch between VKS and CCI product views.
  • Instance Lifecycle Management: Supports creating, editing, starting, stopping, and deleting Workshop and CCI.
  • Image Management: Configure official Alaya NeW image repositories or custom Harbor registries; View, refresh, copy, and delete image information; Save the current running Workshop or CCI environment as a new image.
  • Remote Deployment: Deploy the Aladdin Remote extension to running Workshop or CCI instances with a single click.
  • Monitoring & Tasks: View training task status, real-time logs, and resource monitoring metrics.

2. Remote Development & Resource Scheduling

  • GPU Debug / Run: Debug or run Python applications directly on remote GPU resources.
  • Run Shell: Execute Shell scripts directly on remote compute resources.
  • Run Task: Submit standard training jobs with full lifecycle management, monitoring, and logging.
  • Quick Access: Supports initiating compute operations directly via the editor context menu, file explorer context menu, or CodeLens.
  • Session & Task Management: Centrally manage development sessions and training tasks.
  • Multi-dimensional Interaction: View and download logs, open remote terminals, and manage external access permissions.
  • MCP Tool Integration: Expose MCP interfaces for large language models and automation tools to query resources, search images, execute jobs, debug programs, and manage tasks.

💻 Supported IDE Vendors

Aladdin fully supports VS Code and mainstream AI editors or remote IDE servers that are compatible with the VS Code Extension API.

IDE Remote Server
VS Code vscode-server
Cursor cursor-server
Trae trae-server
Trae CN trae-cn-server
CodeBuddy codebuddy-server
CodeBuddy CN codebuddy-server-cn
Qoder qoder-server
Qoder CN qoder-cn-server
Antigravity antigravity-ide-server
Devin devin-server
Kiro kiro-server

🛠️ Requirements

Before getting started, ensure the following prerequisites are met:

Item Requirement
IDE Version VS Code 1.93.0 or later (or any compatible IDE listed above)
User Account A valid Alaya NeW account
Cloud Resources Available VKS or CCI computing resources
Image Access Credentials for private image repositories (optional)

⚠️ Note: The local Aladdin extension is not designed to run inside remote IDE environments. All remote execution and debugging capabilities are provided by Aladdin Remote, which must first be installed into a Workshop or CCI instance through the local extension.


📖 Getting Started

Get started with cloud-powered development in just a few steps.

Step 1: Install and Login

  1. Search for and install the Aladdin extension from your local IDE marketplace.
  2. Open the Aladdin view from the Activity Bar.
  3. Log in to your Alaya NeW account, select your target AI Data Center, and choose the product type: VKS or CCI.

Step 2: Configure and Launch Resources

  1. (Optional) Upload private images to your image registry.
  2. Create and start a Workshop or CCI. Once the instance is ready, the system automatically connects to the remote workspace.

Step 3: Start Remote Development

  1. Develop your project inside the remote workspace:
  • Python files: Launch using GPU Debug or GPU Run.
  • Shell scripts: Execute using Run Shell or Run Task.
  1. Use the Development Sessions or Training Tasks panels to:
  • Monitor active sessions and jobs.
  • Track execution progress.
  • View real-time monitoring metrics and logs.
  • Open remote terminals.
  • Manage external access permissions.
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