docs-archive/apache-airflow-providers-google/8.4.0/_sources/logging/gcs.rst.txt

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.. _write-logs-gcp:

Writing logs to Google Cloud Storage
------------------------------------

Remote logging to Google Cloud Storage uses an existing Airflow connection to read or write logs. If you
don't have a connection properly setup, this process will fail.

Follow the steps below to enable Google Cloud Storage logging.

To enable this feature, ``airflow.cfg`` must be configured as in this
example:

.. code-block:: ini

    [logging]
    # Airflow can store logs remotely in AWS S3, Google Cloud Storage or Elastic Search.
    # Users must supply an Airflow connection id that provides access to the storage
    # location. If remote_logging is set to true, see UPDATING.md for additional
    # configuration requirements.
    remote_logging = True
    remote_base_log_folder = gs://my-bucket/path/to/logs

#. By default Application Default Credentials are used to obtain credentials. You can also
   set ``google_key_path`` option in ``[logging]`` section, if you want to use your own service account.
#. Make sure a Google Cloud account have read and write access to the Google Cloud Storage bucket defined above in ``remote_base_log_folder``.
#. Install the ``google`` package, like so: ``pip install 'apache-airflow[google]'``.
#. Restart the Airflow webserver and scheduler, and trigger (or wait for) a new task execution.
#. Verify that logs are showing up for newly executed tasks in the bucket you have defined.
#. Verify that the Google Cloud Storage viewer is working in the UI. Pull up a newly executed task, and verify that you see something like:

.. code-block:: none

  *** Reading remote log from gs://<bucket where logs should be persisted>/example_bash_operator/run_this_last/2017-10-03T00:00:00/16.log.
  [2017-10-03 21:57:50,056] {cli.py:377} INFO - Running on host chrisr-00532
  [2017-10-03 21:57:50,093] {base_task_runner.py:115} INFO - Running: ['bash', '-c', 'airflow tasks run example_bash_operator run_this_last 2017-10-03T00:00:00 --job-id 47 --raw -S DAGS_FOLDER/example_dags/example_bash_operator.py']
  [2017-10-03 21:57:51,264] {base_task_runner.py:98} INFO - Subtask: [2017-10-03 21:57:51,263] {__init__.py:45} INFO - Using executor SequentialExecutor
  [2017-10-03 21:57:51,306] {base_task_runner.py:98} INFO - Subtask: [2017-10-03 21:57:51,306] {models.py:186} INFO - Filling up the DagBag from /airflow/dags/example_dags/example_bash_operator.py

**Note** that the path to the remote log file is listed on the first line.