Run the manager and JupyterLab using Docker

Use Docker Compose to run the AI Unlimited manager and JupyterLab, with the AI Unlimited Jupyter Kernel, locally in containers.

Clone the AI Unlimited GitHub repository

Clone the AI Unlimited GitHub repository. The deployments folder in the repository contains template, parameter, and policy files for installing AI Unlimited.

Open a terminal window, and clone the repository.

Set locations for manager and JupyterLab configuration files

tip

Learn about AWS or Azure environment variables.

1. Optionally, set the AI_UNLIMITED_HOME environment variable to the directory in which to store the manager's configuration and data files. Make sure the directory exists, and that appropriate permission is granted. The default location is ./volumes/ai-unlimited.

   Local location	Container location	Usage
   $AI_UNLIMITED_HOME	/etc/td	Stores data and configuration

2. Optionally, set the JUPYTER_HOME environment variable to the directory in which to store JupyterLab's configuration files. The default location is ~/.jupyter.

Provide your cloud service provider credentials to Docker

You can use environment variables to pass your AWS or Azure credentials to Docker Compose.

What does doing this enable?

note

You can provide the credentials two ways:

• Use a YAML file that contains environment varibles for storing your credentials.
• Use a local volume containing your credentials.

See both methods in the Jupyter and AI Unlimited section of Deploy with Docker Compose in the Teradata AI Unlimited GitHub repository.

This QuickStart assumes you are using the first method.

1. Copy these environment variables from your cloud service provider's console.

   AWS

   AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, and AWS_SESSION_TOKEN

   Azure

   ARM_SUBSCRIPTION_ID, ARM_CLIENT_ID, and ARM_CLIENT_SECRET

2. In the Teradata AI Unlimited GitHub repository, open the [AWS or Azure]-credentials-env-vars.yaml file and update the environment variable values.

Start the manager and JupyterLab

1. Go to the directory where ai-unlimited.yaml and jupyter.yaml are located, and start the manager and JupyterLab.

   AWS

   Azure

   The command downloads and starts the manager and JupyterLab containers.

2. To retrieve the Jupyter token, list the currently running containers, and identify the name of the JupyterLab container.

   Then search for occurrences of the string 'Token' in the container's logs.

Verify access

When the manager is ready, you can access it at http://localhost:3000.

When JupyterLab is ready, you can access it at http://localhost:8888, and enter the token.

Next step

In the manager, set up AI Unlimited.