Add more information on impact of using a cluster policy in databricks_cluster resource (#2313)

To emphasize the problems like in #2310

Author: alexott

docs/resources/cluster.md

@@ -38,7 +38,7 @@ resource "databricks_cluster" "shared_autoscaling" {
 * `node_type_id` - (Required - optional if `instance_pool_id` is given) Any supported [databricks_node_type](../data-sources/node_type.md) id. If `instance_pool_id` is specified, this field is not needed.
 * `instance_pool_id` (Optional - required if `node_type_id` is not given) - To reduce cluster start time, you can attach a cluster to a [predefined pool of idle instances](instance_pool.md). When attached to a pool, a cluster allocates its driver and worker nodes from the pool. If the pool does not have sufficient idle resources to accommodate the cluster’s request, it expands by allocating new instances from the instance provider. When an attached cluster changes its state to `TERMINATED`, the instances it used are returned to the pool and reused by a different cluster.
 * `driver_instance_pool_id` (Optional) - similar to `instance_pool_id`, but for driver node. If omitted, and `instance_pool_id` is specified, then the driver will be allocated from that pool.
-* `policy_id` - (Optional) Identifier of [Cluster Policy](cluster_policy.md) to validate cluster and preset certain defaults. *The primary use for cluster policies is to allow users to create policy-scoped clusters via UI rather than sharing configuration for API-created clusters.* For example, when you specify `policy_id` of [external metastore](https://docs.databricks.com/administration-guide/clusters/policies.html#external-metastore-policy) policy, you still have to fill in relevant keys for `spark_conf`.
+* `policy_id` - (Optional) Identifier of [Cluster Policy](cluster_policy.md) to validate cluster and preset certain defaults. *The primary use for cluster policies is to allow users to create policy-scoped clusters via UI rather than sharing configuration for API-created clusters.* For example, when you specify `policy_id` of [external metastore](https://docs.databricks.com/administration-guide/clusters/policies.html#external-metastore-policy) policy, you still have to fill in relevant keys for `spark_conf`.  If relevant fields aren't filled in, then it will cause the configuration drift detected on each plan/apply, and Terraform will try to apply the detected changes.
 * `apply_policy_default_values` - (Optional) Whether to use policy default values for missing cluster attributes.
 * `autotermination_minutes` - (Optional) Automatically terminate the cluster after being inactive for this time in minutes. If specified, the threshold must be between 10 and 10000 minutes. You can also set this value to 0 to explicitly disable automatic termination. Defaults to `60`.  *We highly recommend having this setting present for Interactive/BI clusters.*
 * `enable_elastic_disk` - (Optional) If you don’t want to allocate a fixed number of EBS volumes at cluster creation time, use autoscaling local storage. With autoscaling local storage, Databricks monitors the amount of free disk space available on your cluster’s Spark workers. If a worker begins to run too low on disk, Databricks automatically attaches a new EBS volume to the worker before it runs out of disk space. EBS volumes are attached up to a limit of 5 TB of total disk space per instance (including the instance’s local storage). To scale down EBS usage, make sure you have `autotermination_minutes` and `autoscale` attributes set. More documentation available at [cluster configuration page](https://docs.databricks.com/clusters/configure.html#autoscaling-local-storage-1).