auto:latest-lts spark_version support

Describe the issue

I am trying to deploy a DAB that creates a new job cluster using the policy id for the Job Compute policy. The Job Compute policy sets this value for the spark_version:

"spark_version": {
    "type": "unlimited",
    "defaultValue": "auto:latest-lts"
  },

I want to use the latest-lts spark version for my jobs if possible and not have to specify the exact version in the DAB.

Setting spark_version: "auto:latest-lts" in my DAB does not work and I get the following error: "INVALID_PARAMETER_VALUE: Invalid spark version auto:latest-lts." I would expect the resulting bundle.tf.json that has a line that looks similar to data.databricks_spark_version.latest.id, using the databrick_spark_version Terraform resource in order for this to work correctly.

Omitting the spark_version in my DAB, produces a bundle.tf.json with an empty string: "spark_version": "", and I get a similar error: "INVALID_PARAMETER_VALUE: Invalid spark version ."

Are there plans for the CLI to support this use case?

Configuration

bundle.yml:

bundle:
  name: Test

sync:
  include:
      - src/*.py

variables:
  cluster_policy_id:
    description: "The cluster policy used to create the cluster for the job."

resources:
  jobs:
    Test:
      name: _Test
      job_clusters:
        - job_cluster_key: test-cluster
          new_cluster:
            policy_id: ${var.cluster_policy_id}
            apply_policy_default_values: true
            node_type_id: Standard_D8ads_v5
            num_workers: 4
            spark_version: "auto:latest-lts"
      tasks:
        - task_key: _Test
          job_cluster_key: test-cluster
          notebook_task:
            notebook_path: "./src/test.py"

Steps to reproduce the behavior

Please list the steps required to reproduce the issue, for example:

Run databricks bundle deploy --var "cluster_policy_id=<job compute policy id>"
See error ""INVALID_PARAMETER_VALUE: Invalid spark version auto:latest-lts."

databricks / cli