databricks.ClusterPolicy

This resource creates a cluster policy, which limits the ability to create clusters based on a set of rules. The policy rules limit the attributes or attribute values available for cluster creation. cluster policies have ACLs that limit their use to specific users and groups. Only admin users can create, edit, and delete policies. Admin users also have access to all policies.

Cluster policies let you:

• Limit users to create clusters with prescribed settings.
• Simplify the user interface and enable more users to create their own clusters (by fixing and hiding some values).
• Control cost by limiting per cluster maximum cost (by setting limits on attributes whose values contribute to hourly price).

Cluster policy permissions limit which policies a user can select in the Policy drop-down when the user creates a cluster:

• If no policies have been created in the workspace, the Policy drop-down does not display.
• A user who has cluster create permission can select the Free form policy and create fully-configurable clusters.
• A user who has both cluster create permission and access to cluster policies can select the Free form policy and policies they have access to.
• A user that has access to only cluster policies, can select the policies they have access to.

Related Resources

The following resources are often used in the same context:

• Dynamic Passthrough Clusters for a Group guide.
• End to end workspace management guide.
• databricks.getClusters data to retrieve a list of databricks.Cluster ids.
• databricks.Cluster to create Databricks Clusters.
• databricks.getCurrentUser data to retrieve information about databricks.User or databricks_service_principal, that is calling Databricks REST API.
• databricks.GlobalInitScript to manage global init scripts, which are run on all databricks.Cluster and databricks_job.
• databricks.InstancePool to manage instance pools to reduce cluster start and auto-scaling times by maintaining a set of idle, ready-to-use instances.
• databricks.InstanceProfile to manage AWS EC2 instance profiles that users can launch databricks.Cluster and access data, like databricks_mount.
• databricks.IpAccessList to allow access from predefined IP ranges.
• databricks.Library to install a library on databricks_cluster.
• databricks.getNodeType data to get the smallest node type for databricks.Cluster that fits search criteria, like amount of RAM or number of cores.
• databricks.Permissions to manage access control in Databricks workspace.
• databricks.getSparkVersion data to get Databricks Runtime (DBR) version that could be used for spark_version parameter in databricks.Cluster and other resources.
• databricks.UserInstanceProfile to attach databricks.InstanceProfile (AWS) to databricks_user.
• databricks.WorkspaceConf to manage workspace configuration for expert usage.

Create ClusterPolicy Resource

new ClusterPolicy(name: string, args: ClusterPolicyArgs, opts?: CustomResourceOptions);

@overload
def ClusterPolicy(resource_name: str,
                  opts: Optional[ResourceOptions] = None,
                  definition: Optional[str] = None,
                  max_clusters_per_user: Optional[int] = None,
                  name: Optional[str] = None)
@overload
def ClusterPolicy(resource_name: str,
                  args: ClusterPolicyArgs,
                  opts: Optional[ResourceOptions] = None)

func NewClusterPolicy(ctx *Context, name string, args ClusterPolicyArgs, opts ...ResourceOption) (*ClusterPolicy, error)

public ClusterPolicy(string name, ClusterPolicyArgs args, CustomResourceOptions? opts = null)

public ClusterPolicy(String name, ClusterPolicyArgs args)
public ClusterPolicy(String name, ClusterPolicyArgs args, CustomResourceOptions options)

type: databricks:ClusterPolicy
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.

ClusterPolicy Resource Properties

To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.

Inputs

The ClusterPolicy resource accepts the following input properties:

Outputs

All input properties are implicitly available as output properties. Additionally, the ClusterPolicy resource produces the following output properties:

Look up Existing ClusterPolicy Resource

Get an existing ClusterPolicy resource’s state with the given name, ID, and optional extra properties used to qualify the lookup.

public static get(name: string, id: Input<ID>, state?: ClusterPolicyState, opts?: CustomResourceOptions): ClusterPolicy

@staticmethod
def get(resource_name: str,
        id: str,
        opts: Optional[ResourceOptions] = None,
        definition: Optional[str] = None,
        max_clusters_per_user: Optional[int] = None,
        name: Optional[str] = None,
        policy_id: Optional[str] = None) -> ClusterPolicy

func GetClusterPolicy(ctx *Context, name string, id IDInput, state *ClusterPolicyState, opts ...ResourceOption) (*ClusterPolicy, error)

public static ClusterPolicy Get(string name, Input<string> id, ClusterPolicyState? state, CustomResourceOptions? opts = null)

public static ClusterPolicy get(String name, Output<String> id, ClusterPolicyState state, CustomResourceOptions options)

Resource lookup is not supported in YAML

Import

The resource cluster policy can be imported using the policy idbash

 $ pulumi import databricks:index/clusterPolicy:ClusterPolicy this <cluster-policy-id>

Package Details

Repository

databricks pulumi/pulumi-databricks

License

Apache-2.0

Notes

This Pulumi package is based on the databricks Terraform Provider.