1. Civo Block Storage for High-Performance AI Datasets


    Civo is a cloud provider focusing on simplicity and speed, offering Kubernetes services but notably not block storage services that can directly be provisioned using Pulumi. However, if one needs to work with high-performance AI datasets on block storage, they can look into other cloud providers that offer these services and can be managed using Pulumi, such as AWS, Google Cloud (GCP), or Azure.

    For this scenario, we could use the BlockStorage resource from a provider such as Vultr, which does offer block storage services and has a Pulumi package available. Below, I am providing a Pulumi Python program that provisions a Vultr block storage instance that could be used to store high-performance AI datasets.

    In the Pulumi program below, we start by importing the required packages and then instantiate a BlockStorage resource. To keep things simple, I am hardcoding the region and block storage size, which you might want to adjust based on your actual requirements and possibly parameterize through the Pulumi configuration system for more flexibility. Additionally, I am assuming you've set up Pulumi with your Vultr API token and have the necessary permissions.

    Here's a Pulumi program using the Vultr provider:

    import pulumi import pulumi_vultr as vultr # Create a block storage instance with 100 GB capacity in the Amsterdam region high_performance_storage = vultr.BlockStorage( "highPerformanceStorage", region="ams", # This should be replaced with the region you wish to use size_gb=100, # The size of the block storage in GB block_type="high_performance" # Indicating that we want high-performance block storage ) # Export the block storage ID so we can easily locate it pulumi.export("block_storage_id", high_performance_storage.id)

    In this program:

    • pulumi_vultr is being used as the provider, which is Pulumi's interface to manage Vultr resources.
    • We are creating a BlockStorage instance called highPerformanceStorage that is set to be located in the Amsterdam region with a size of 100 GB. The type is set to high_performance, indicating that it will be suitable for AI datasets that require high I/O performance.
    • Finally, we export the block storage ID using pulumi.export, which will allow you to easily retrieve the block storage's ID once it is provisioned. This can be helpful for future operations such as attaching it to instances or further management tasks.

    Remember that to apply these changes, you'll need to run pulumi up within the directory of your Pulumi program, and Pulumi will perform the provisioning for you based on the code. Make sure you have the necessary permissions in your cloud provider account and that you've set the proper credentials for Pulumi to use.