1. AI Model Inference Hosting on Hetzner Cloud CPX Instances

    Python

    To create infrastructure for AI model inference hosting using Pulumi on Hetzner Cloud CPX instances, we'll be writing a program that provisions the necessary resources. Specifically, we will create instances (servers) where the AI model will be hosted and inference tasks will be run.

    Hetzner Cloud is not directly supported by Pulumi as of my last update, meaning there isn't a dedicated Pulumi provider for Hetzner Cloud. However, it is possible to use Pulumi to interact with Hetzner Cloud through the use of the Pulumi Terraform Bridge, which allows you to use Terraform providers as if they were native Pulumi providers. The Hetzner Cloud provider for Terraform can be used in this manner.

    Here's how you would set up AI model inference hosting:

    1. Server Setup: Provision CPX instances on Hetzner Cloud that will serve as the compute resource for running your AI models.

    2. Networking: Set up networking resources to ensure your servers can communicate as necessary.

    3. Deployment: Configure the instance with the necessary software to run your AI model, which might include your model code, inference server (like TensorFlow Serving), and any other software dependencies.

    Please note that for this response, since Pulumi does not natively support Hetzner as a cloud provider, we will walk through the conceptual steps. The specific details of using the Terraform Provider within Pulumi will be generalized for the sake of explaining the setup.

    Here is a conceptual Pulumi program written in Python:

    import pulumi from pulumi_terraform import TerraformRemoteStateReference # Step 1 - Define the Hetzner Cloud Provider using Terraform bridge # Since Pulumi does not natively support Hetzner, we can interact with it through the Terraform bridge. # This would require you to have Terraform scripts that define your Hetzner CPX instances. # Please refer to the Terraform Registry for Hetzner Cloud provider and use the relevant configurations. hetzner_provider = TerraformRemoteStateReference( 'hetzner', # The configuration will depend on your Terraform setup. # Ensure that your Terraform scripts are set up correctly to provision CPX instances. ) # Step 2 - Define CPX servers # You would retrieve information from the Terraform state and use it within Pulumi. # Assuming `cpux_instances` is a resource from your Terraform configuration. server = hetzner_provider.get_output('cpux_instances') # Step 3 - Define Networking # Again, assuming 'network' is defined in your Terraform configuration. network = hetzner_provider.get_output('network') # Step 3 - Deployment Configuration # After provisioning the CPX instances via Hetzner, you would configure them with necessary tooling. # This is generally done via user data scripts or configuration management tools such as Ansible. # Pulumi can also handle file uploads and command execution, but this is an advanced topic. # Conclusion: # This Pulumi program provides a framework for provisioning and interacting with CPX instances on Hetzner Cloud. # The specifics of the configuration and interaction with Terraform are not covered here and require setting up # Terraform to work with Hetzner Cloud and then referencing it with Pulumi's TerraformRemoteStateReference. # Output the results (IP addresses, hostnames, etc.) so they can be used or referenced. pulumi.export('server_ips', server.apply(lambda s: [instance.ip for instance in s]))

    In this Pulumi program, you would:

    • Define a Terraform bridge provider to interact with Hetzner Cloud.
    • Get the CPX instances output defined in your Terraform scripts.
    • Define additional resources such as networks if they are needed for your application.
    • Utilize a remote state reference to Terraform to include outputs that the Pulumi stack can use, such as IP addresses.

    The actual provisioning and management would be done in Terraform, and Pulumi would then use the Terraform state to perform actions or retrieve information about the infrastructure which is useful for constructing outputs or managing dependent resources.

    Remember, understanding and setting up Terraform configurations is a prerequisite for using the Terraform bridge with Pulumi. The Pulumi website provides detailed documentation on how to use the Terraform bridge. The Terraform Registry would have information on setting up the Hetzner Cloud provider and the relevant details for provisioning CPX instances. Once you have your Terraform code set up, you can reference the state file in Pulumi as shown in the program above.