Synapse Workspace for Collaborative AI Development

Question

Pulumi · Accepted Answer

To create a Synapse Workspace for Collaborative AI Development, you would use Azure Synapse Analytics, which is an analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless or provisioned resources—at scale. Azure Synapse brings these worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs.

Here, we'll use `azure-native.synapse.Workspace` for creating the Synapse Workspace. We need to configure several properties for this workspace, such as the SQL admin credentials, workspace name, and allow Azure services to access the workspace. Additionally, we can enable Managed Virtual Network for enhanced security.

For the purpose of AI development, it's also essential to have a collaborative environment. Azure Synapse can integrate with Azure Machine Learning services using linked services, but in this code, we will focus on setting up the base Synapse Workspace.

Now, let's go ahead with the Python Pulumi program to create an Azure Synapse Workspace.

```python
import pulumi
import pulumi_azure_native as azure_native

# Set up the resource group where all resources will reside.
resource_group = azure_native.resources.ResourceGroup('ai_synapse_rg')

# Define the Azure Synapse Workspace
synapse_workspace = azure_native.synapse.Workspace(
    'ai_synapse_workspace',
    resource_group_name=resource_group.name,
    location=resource_group.location,
    sql_administrator_login='sqladminuser',  # Replace with your desired admin username
    sql_administrator_login_password='ComplexPwd#1234',  # Replace with your desired admin password
    identity=azure_native.synapse.WorkspaceIdentityArgs(
        type='SystemAssigned',
    ),
    managed_virtual_network='default'  # Enables Azure Synapse Analytics managed virtual networks
)

# Exporting the Synapse Workspace URL which can be used to access the workspace.
pulumi.export('synapse_workspace_url', synapse_workspace.connectivity_endpoints.apply(
    lambda endpoints: endpoints['web']))

# NOTE: While this code sets up the Synapse Workspace, for full-fledged AI collaboration,
# you will likely need to integrate Azure Machine Learning services, set up linked services,
# datasets, and pipelines within the Synapse Workspace.
```

This program does the following:
- Sets up a new resource group for the Azure Synapse Workspace.
- Creates a new Synapse Workspace with a System-Assigned Managed Identity and the Managed Virtual Network enabled, which is recommended for better security isolation.
- Exports the URL endpoint for the created workspace, which can be used to access and manage the workspace.

To use this code, replace the `sql_administrator_login` and `sql_administrator_login_password` values with your own desired credentials.

For a comprehensive setup, including Azure Machine Learning integration, continue to build upon this workspace by adding linked services, creating datasets, and defining pipelines for data movement and transformation. You might also want to configure Azure Active Directory admin for the workspace, networking rules, etc., using similar Pulumi resources.

You will need to have the appropriate Pulumi and Azure CLI configurations set up to deploy this code successfully. Please make sure you have logged in with the Azure CLI (`az login`) and have selected the appropriate subscription (`az account set --subscription "<subscription_id>"`) before running `pulumi up` to apply this Pulumi program.