Enforcing IP-based Access for Collaborative AI Research Databases

Question

Pulumi · Accepted Answer

To enforce IP-based access for collaborative AI Research databases, you'd typically look for resources within your cloud provider's services that allow you to define access controls based on IP addresses. A pervasive use case for such a requirement can be restricting access to a database service to only a set of known IP addresses for security reasons.

In the context of Google Cloud, one such resource is Cloud SQL, which is a fully-managed database service that allows you to set up and manage MySQL, PostgreSQL, and SQL Server databases. Google Cloud SQL provides an option to define authorized networks, which can be IP addresses or ranges of IP addresses from which your database instances can be accessed.

In Pulumi, manipulating these settings can be done using the Google Cloud Platform (GCP) provider. I will write a Pulumi program to create a Google Cloud SQL instance and set the network rules to allow access from specific IP addresses.

Here's a program that achieves the described goal:

```python
import pulumi
import pulumi_gcp as gcp

# Create a new Cloud SQL instance:
sql_instance = gcp.sql.DatabaseInstance("sql-instance",
    database_version="POSTGRES_12",
    settings=gcp.sql.DatabaseInstanceSettingsArgs(
        tier="db-f1-micro",
    )
)

# Define the rules to control the IP-based access for the instance:
# Replace "ip-range" with your own IP address or range.
ip_configuration = gcp.sql.DatabaseInstanceIpConfigurationArgs(
    ipv4_enabled=True,
    authorized_networks=[
        gcp.sql.DatabaseInstanceIpConfigurationAuthorizedNetworksArgs(
            value="ip-range", # IP address or range
            name="ai-research-access", # Descriptive name for the access rule
        ),
    ]
)

# Update the IP configuration for the Cloud SQL instance:
sql_instance_ip_config = gcp.sql.DatabaseInstance("sql-instance-ip-config",
    name=sql_instance.name,
    settings=gcp.sql.DatabaseInstanceSettingsArgs(
        ip_configuration=ip_configuration,
    )
)

# Export the instance connection name which is useful when connecting from applications.
pulumi.export('instance_connection_name', sql_instance.connection_name)
```

In the code above:

1. We create a new Cloud SQL instance with a specific database version using `gcp.sql.DatabaseInstance`.
2. We initiate an IP configuration (`gcp.sql.DatabaseInstanceIpConfigurationArgs`) with `ipv4_enabled` set to `True` and list the authorized network we want to grant access to.
3. `sql_instance_ip_config` is the resource handling the new configuration values being associated with the Cloud SQL instance.
4. Finally, we export the connection name for the Cloud SQL instance; this value can be used to identify the database instance when configuring database clients.

Make sure to replace `"ip-range"` with your actual IP address or range that should have access to the database instance. Also, adjust the `tier` and `database_version` according to your specific requirements.

Please note, this program assumes you've already set up Pulumi with Google Cloud credentials and you have the appropriate permissions to create and manage Cloud SQL instances. To run the program, save the code into a file named `__main__.py`, and run `pulumi up` within the directory containing the file. This will start the deployment process within the Pulumi CLI, allowing you to review changes before they're applied.