View logs on the dashboard

By default, ZenML uses a logging handler to capture the logs that occur during the execution of a step. Users are free to use the default python logging module or print statements, and ZenML's logging handler will catch these logs and store them.

import logging

from zenml import step

def my_step() -> None:
    logging.warning("`Hello`")  # You can use the regular `logging` module.
    print("World.")  # You can utilize `print` statements as well. 

These logs are stored within the respective artifact store of your stack. This means that you can only view these logs in the dashboard if the deployed ZenML server has direct access to the underlying artifact store. There are two cases in which this will be true:

  • In case of a local ZenML server (via zenml up), both local and remote artifact stores may be accessible, depending on configuration of the client.

  • In case of a deployed ZenML server, logs for runs on a local artifact store will not be accessible. Logs for runs using a remote artifact store may be accessible, if the artifact store has been configured with a service connector. Please read this chapter of the production guide to learn how to configure a remote artifact store with a service connector.

If configured correctly, the logs are displayed in the dashboard as follows:

If you do not want to store the logs for your pipeline (for example due to performance reduction or storage limits), you can follow these instructions.

Last updated