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Azure

Polaris LLM uses the standard Polaris Azure GPU Terraform module with LLM-specific configurations. This enables safe and efficient language model deployment on secure hardware.

Accessing the Module​

The module is available on the Terraform Registry:

Terraform Registry - Fr0ntierX/polaris-gpu/azure

module "polaris_azure_gpu_module" {
  source = "../"

  subscription_id = "YOUR-SUBSCRIPTION-ID"
  name            = "polaris-llm"
  location        = "eastus2"
  zone            = "2"

  admin_username        = "azureuser"
  admin_password_or_key = "MY_PASSWORD"
  authentication_type   = "password"

  virtual_network_name           = "my-precreated-vnet"
  virtual_network_resource_group = "my-network-rg"
  subnet_name                    = "my-subnet"
  
  custom_workload = {
    image_address = "example.azurecr.io/custom-workload:latest"
    port          = 11434
    registry = {
      login_server = "example.azurecr.io"
      username     = "registry_user"
      password     = "registry_password"
    }
  }

  polaris_proxy_enable_input_encryption = true
  polaris_proxy_enable_output_encryption = true
}

LLM-Specific Features​

FeatureDescription
Framework SupportPre-configured options for vLLM, Ollama
Model SecurityProtected loading and serving of proprietary models
Prompt ProtectionSecure handling of potentially sensitive prompts
Response FilteringOptions for secure post-processing of generated content

Learn More​

For detailed configuration options and usage examples, refer to: