Hi! I have a custom model registered on unity catalog that I am able load and use for prediction. However, I am unable to deploy same model using the Model Serving UI. Databricks runtime used for model training and deployment is 15.4 ML.

Thanks in advance.

Code Snippet

# Define conda environment or pip requirements
conda_env = {
    'name': 'mlflow-env',
    'channels': ['defaults'],
    'dependencies': [
        'python=3.11.11',
        'pip',
        {
            'pip': [
                'pyspark==3.5.0',
                'mlflow==2.19.0'
            ]
        }
    ]
}

# set model alias
model_alias = 'macro_vars'

# Log model to MLflow
with mlflow.start_run(run_name=f"{model_alias}_run") as run:
    
    # Fit pipeline to training data
    pipeline_model = pipeline.fit(filtered_data)
    
    # Transform data using pipeline
    transformed_data = pipeline_model.transform(filtered_data)
    
    # Train logistic regression model
    lr_model = LogisticRegression(featuresCol='features', labelCol='CO_flag', maxIter=100)
    lr_model_fit = lr_model.fit(transformed_data)
    
    # Make predictions using trained model
    predictions = lr_model_fit.transform(transformed_data)
    
    # Log Model
    signature = infer_signature(transformed_data.select('features'), predictions.select('prediction'))
    
    mlflow.spark.log_model(
        spark_model=lr_model_fit,
        artifact_path=model_alias,
        signature=signature,
        conda_env=conda_env
    )
    
    # Register model
    catalog_name = "czcl"
    schema_name = "czcl_gold"
    model_name = "czcl_model"
    registered_name = f"{catalog_name}.{schema_name}.{model_name}"
    model_uri = f"runs:/{run.info.run_id}/{model_alias}"

    result = mlflow.register_model(model_uri, registered_name)
    client = mlflow.MlflowClient()
    client.set_registered_model_alias(name=registered_name, alias=model_alias, version=result.version)

Error Message:

[wgkkr] 2025-05-22 23:10:44.182 INFO : Initializing .........
[wgkkr] WARNING:root:mlflow-server
[wgkkr] [2025-05-22 23:10:44 +0000] [10] [INFO] Starting gunicorn 23.0.0
[wgkkr] [2025-05-22 23:10:44 +0000] [10] [INFO] Listening at: http://0.0.0.0:8080 (10)
[wgkkr] [2025-05-22 23:10:44 +0000] [10] [INFO] Using worker: sync
[wgkkr] [2025-05-22 23:10:44 +0000] [11] [INFO] Booting worker with pid: 11
[wgkkr] JAVA_HOME is not set
[wgkkr] [2025-05-22 23:10:50 +0000] An error occurred while loading the model: [JAVA_GATEWAY_EXITED] Java gateway process exited before sending its port number.
[wgkkr] [2025-05-22 23:10:50 +0000] Traceback (most recent call last):
[wgkkr] [2025-05-22 23:10:50 +0000]   File "/opt/conda/envs/mlflow-env/lib/python3.11/site-packages/mlflowserving/scoring_server/__init__.py", line 212, in get_model_option_or_exit
[wgkkr] [2025-05-22 23:10:50 +0000]     self.model = self.model_future.result()
[wgkkr] [2025-05-22 23:10:50 +0000]                  ^^^^^^^^^^^^^^^^^^^^^^^^^^
[wgkkr] [2025-05-22 23:10:50 +0000]   File "/opt/conda/envs/mlflow-env/lib/python3.11/concurrent/futures/_base.py", line 449, in result
[wgkkr] [2025-05-22 23:10:50 +0000]     return self.__get_result()
[wgkkr] [2025-05-22 23:10:50 +0000]            ^^^^^^^^^^^^^^^^^^^
[wgkkr] [2025-05-22 23:10:50 +0000]   File "/opt/conda/envs/mlflow-env/lib/python3.11/concurrent/futures/_base.py", line 401, in __get_result
[wgkkr] [2025-05-22 23:10:50 +0000]     raise self._exception
[wgkkr] [2025-05-22 23:10:50 +0000]   File "/opt/conda/envs/mlflow-env/lib/python3.11/concurrent/futures/thread.py", line 58, in run
[wgkkr] [2025-05-22 23:10:50 +0000]     result = self.fn(*self.args, **self.kwargs)
[wgkkr] [2025-05-22 23:10:50 +0000]              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[wgkkr] [2025-05-22 23:10:50 +0000]   File "/opt/conda/envs/mlflow-env/lib/python3.11/site-packages/mlflowserving/scoring_server/__init__.py", line 132, in _load_model_closure