1. Adjusting Quotas for Data-Intensive AI Model Training


    When training data-intensive AI models, you may encounter limitations set by the cloud provider's quotas on resources such as compute instances, storage, and specific AI services. To manage these cloud provider quotas, Pulumi offers resources that interact with the cloud provider's service quota mechanisms.

    For AWS, Pulumi provides a ServiceQuota resource which allows you to look up the information of a service quota and to change its value. Managing quotas is crucial when dealing with large-scale training tasks as you might need to increase the number of virtual CPUs (vCPUs) available for your EC2 instances, or adjust the limits of AI-related services provided by AWS.

    Below, I'll show you a Pulumi Python program that adjusts AWS service quotas. This program will import the required ServiceQuota resource from the pulumi_aws package, specify which service quota to change, and set the new desired value.

    For this hypothetical scenario, let's assume that we want to increase the number of vCPUs for p2.xlarge EC2 instances, used commonly for machine learning tasks due to their GPU capabilities.

    First, we import Pulumi and Pulumi AWS SDK. We then instantiate the ServiceQuota resource with the desired values. You'll usually find the quotaCode and serviceCode in the AWS documentation or by using AWS CLI or Boto3 library to list all quotas for a given service.

    Here's how you can set this up with Pulumi:

    import pulumi import pulumi_aws as aws # Instantiate a ServiceQuota resource to increase the quota for p2.xlarge instances # Assume 'L-34B43A08' is the quota code for the number of vCPUs you can launch in EC2 # and 'ec2' is the service code for AWS EC2. # The value is the desired new quota value. # You should replace these strings with the correct `quotaCode` and `serviceCode` # from the quota you need to adjust for your particular use case. vcpu_quota = aws.servicequotas.ServiceQuota("vcpu-quota", quota_code="L-34B43A08", service_code="ec2", value=100 # New quota value; set this to whatever you need ) # Export the quota setting value so that you can confirm it has been set pulumi.export("new_vcpu_quota", vcpu_quota.value)

    In the program above, the quota_code and service_code must correspond to the actual service and quota you intend to change. The value is what you would like to increase the quota to.

    After running this Pulumi program, Pulumi will make the necessary API calls to AWS to update your service quota. It is important to note that not all service quotas can be adjusted, and some may require AWS to approve the increase. You may want to initiate the request programmatically but handle the approval process manually, according to AWS's policies and response times.

    Please remember that changes to service quotas can result in increased costs, so it is essential to monitor usage and spend closely after making adjustments. Always follow best practices for cost governance on the cloud.