CI/CD for LLM Deployment with GitLab Runner

To set up CI/CD for a Large Language Model (LLM) Deployment with GitLab Runner using Pulumi, you will need to define a stack that configures the necessary infrastructure. This typically involves:

1. Setting up a GitLab Runner that performs the CI/CD jobs.
2. Configuring a project environment for deploying your LLM.
3. Managing the project and related settings in GitLab.

I'll provide you with a Pulumi program that outlines how to:

• Create a GitLab Runner.
• Configure a project in GitLab.
• This example won't cover the specifics of deploying a Large Language Model as this is highly specific to the model being deployed and the infrastructure it requires.

Here's a step-by-step explanation of the Pulumi program for setting up CI/CD with GitLab Runner:

1. First, we import the necessary libraries, particularly the gitlab package to create GitLab resources.
2. Then we define a GitLab Runner using the gitlab.Runner resource. You will need a GitLab registration token, which should be kept as a secret.
3. Additionally, we create a new GitLab project using the gitlab.Project resource.
4. After setting up the GitLab Runner and project, we can enable the runner for our project using gitlab.ProjectRunnerEnablement.

Please make sure you've configured Pulumi to use the GitLab provider and have the necessary permissions to create and manage these resources.

Below is the Python program you would use:

import pulumi
import pulumi_gitlab as gitlab

# Set up the GitLab Runner
# Replace '<YOUR REGISTRATION TOKEN HERE>' with your GitLab runner registration token.
runner = gitlab.Runner("runner",
                       description="GitLab Runner for LLM Deployment",
                       tags=["llm", "deployment"],
                       locked=False,
                       run_untagged=True,
                       active=True,
                       registration_token=pulumi.Config("gitlab").require_secret("runner_registration_token"))

# Create a new GitLab project for your LLM deployment
# The namespace_id should be set to the GitLab group ID or user namespace ID under which you want the project to be created.
project = gitlab.Project("llm-deployment-project",
                         name="llm-deployment",
                         description="Project for LLM Deployment",
                         visibility_level="private",
                         tags=["llm", "ai", "deployment"],
                         namespace_id=gitlab.Namespace.get("llm-deployment-ns", "<NAMESPACE_ID>").id)

# Enable the GitLab Runner for the LLM Deployment project
project_runner_enablement = gitlab.ProjectRunnerEnablement("llm-project-runner-enablement",
                                                           project=project.id,
                                                           runner_id=runner.id)

# Export the project's web URL so you can easily access it
pulumi.export("project_web_url", project.web_url)

In the above Pulumi program:

• Replace '<YOUR REGISTRATION TOKEN HERE>' with the GitLab runner registration token you obtain from your GitLab instance.
• namespace_id should be set to the ID of the GitLab group or user namespace where you want the project to be created. This can be retrieved from GitLab.
• Tags like ["llm", "deployment"] help categorize the runner for easy identification and selection in CI/CD jobs.

This setup will get you started with a simple CI/CD pipeline. For deploying an actual LLM, you would need to write appropriate .gitlab-ci.yml definitions that specify the build, test, and deployment stages for your model which would utilize this GitLab Runner.

The pulumi.Config object is used to manage secrets and configuration in a safe manner. It allows you to access configuration values set via the pulumi config CLI and mark certain values as secrets, which will be encrypted and only decrypted when necessary. The "gitlab" passed into it specifies that it's fetching values related to the GitLab configuration.

Remember to replace placeholders like <NAMESPACE_ID> with actual values from your GitLab account.

Once you run this Pulumi program, it will set up the resources in GitLab, and you'll have a GitLab Runner ready to process jobs, along with a new GitLab project that this runner is enabled for.