Hi everyone,

I’m deploying a custom model using mlflow.pyfunc.PythonModel in Databricks Model Serving. Inside my wrapper code, I configured logging as follows:

logging.basicConfig(
    stream=sys.stdout,
    level=logging.INFO,
    format='%(asctime)s [%(levelname)s] %(name)s: %(message)s',
    force=True
)
logger = logging.getLogger()

However, in the Model Serving service logs I can only see logger.warning() and logger.error() messages.

I would like to understand:

• What is the default logging level for Model Serving endpoints?
• Is there a supported way to enable INFO level logs?
• If configurable, how can I ensure that all INFO logs (including those from modules used inside the wrapped mlflow.pyfunc.PythonModel) are visible?

Any guidance or documentation reference would be greatly appreciated.

Thanks in advance!