IP Whitelisting for Collaborator Access to Databricks
PythonWhitelisting IP addresses is an important security measure, particularly when you are working with cloud services and want to restrict access to your resources to a set of known IPs. Pulumi enables you to configure your cloud infrastructure in a repeatable and reliable manner with code using its Infrastructure as Code (IaC) approach.
In this example, I'll guide you through setting up IP whitelisting for Databricks using Pulumi with Python. We will achieve this by using
databricks.Cluster
to create a Databricks cluster, and shape its network security settings to include IP whitelisting.Step-by-Step Guide
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Setup Pulumi: Before starting, make sure Pulumi is installed and configured with the appropriate cloud credentials. You can find the instructions on how to do this in the Pulumi Installation Guide.
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Import Databricks Package: We will use the Pulumi Databricks provider to configure our Databricks cluster. Ensure that you have the Pulumi Databricks provider installed.
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Define your IP Whitelist: You will need to have a predefined list of IPs that you want to whitelist for access to the Databricks workspace.
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Create a Databricks Cluster: Using the
databricks.Cluster
resource, we will create a Databricks cluster and specify the network security configurations to restrict access based on the IP whitelist. -
Pulumi Stack Output: Finally, we will export the necessary details of the cluster as Pulumi stack outputs, such as the cluster's URL for users to easily access.
Below is a complete Pulumi program that sets up IP whitelisting on a Databricks cluster. Remember to replace the placeholders with your actual IP addresses and other relevant details.
import pulumi import pulumi_databricks as databricks # Define the IP address range you want to whitelist. # In a real-world scenario, these would be the static IPs of your company's outward-facing gateway, # office network, or a specific set of allowed devices. whitelisted_ips = [ "192.168.1.1", # Replace with actual IPs or CIDR blocks "192.168.1.2", # Add more IPs as needed ] # Create a new Databricks cluster databricks_cluster = databricks.Cluster("restricted-access-cluster", # Specify the node type and other configurations for the cluster. node_type_id="Standard_D3_v2", spark_version="5.3.x-scala2.11", # Define the autoscale settings for the cluster. autoscale=databricks.ClusterAutoscaleArgs( min_workers=1, max_workers=5, ), # Specify a network security group configuration and whitelist the IP addresses. # You would need to extend the databricks provider to support network security # configurations if it's supported by the Databricks API. network_security_group_rules=[{ "name": f"Whitelist-{ip}", "source_address_prefix": ip, "destination_port_range": "443", # Databricks clusters typically communicate over HTTPS. "access": "Allow", "protocol": "Tcp", "direction": "Inbound" } for ip in whitelisted_ips] ) # Output the cluster URL pulumi.export("cluster_url", databricks_cluster.event_store)
Note: This program assumes that Databricks's API and Pulumi provider support network security configurations via the
network_security_group_rules
property. This property is a hypothetical example to illustrate how the code would look if such support existed. You need to replace it with the actual implementation provided by Databricks and available in Pulumi.Important Considerations
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The security of a Databricks cluster typically depends on multiple factors, such as authentication, network security groups, and integration with a company's identity provider.
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It's crucial to monitor the permissions and network configuration continuously as changing business needs might require updates to access policies. With Pulumi's IaC approach, you can easily maintain and version your infrastructure configurations.
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The specifics of implementing IP whitelisting can depend on the precise networking capabilities exposed by the Databricks API and made available through the Pulumi Databricks provider. You might have to work with additional Databricks networking resources or other Pulumi providers to set up network security fully.
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If Databricks does not directly support IP whitelisting through their API, you might need to set up network security at the cloud provider level, using resources like security groups in AWS or network security groups in Azure.
Understand that the exact details and resources you'll need to use will depend on the capabilities of the Databricks platform at the time of writing your Pulumi program. Always check the latest Pulumi Databricks provider documentation to see detailed information about the currently supported resources and properties.
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