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Clarify that logging credentials differ from google_cloud_default (#28084)
Users sometimes confuse the ``google_cloud_default`` credentials with
logging credentials for google cloud logging integration.
This change clarifies this a bit, explicitly specifying that those
are different.
Copy file name to clipboardExpand all lines: docs/apache-airflow-providers-google/logging/gcs.rst
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#. By default Application Default Credentials are used to obtain credentials. You can also
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set ``google_key_path`` option in ``[logging]`` section, if you want to use your own service account.
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#. Make sure a Google Cloud account have read and write access to the Google Cloud Storage bucket defined above in ``remote_base_log_folder``.
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#. Make sure with those credentials, you can read and write access to the Google Cloud Storage bucket defined above in ``remote_base_log_folder``.
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#. Install the ``google`` package, like so: ``pip install 'apache-airflow[google]'``.
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#. Restart the Airflow webserver and scheduler, and trigger (or wait for) a new task execution.
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#. Verify that logs are showing up for newly executed tasks in the bucket you have defined.
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[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
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**Note** that the path to the remote log file is listed on the first line.
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The value of field ``remote_logging`` must always be set to ``True`` for this feature to work.
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Turning this option off will result in data not being sent to GCS.
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The ``remote_base_log_folder`` option contains the URL that specifies the type of handler to be used.
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For integration with GCS, this option should start with ``gs://``.
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The path section of the URL specifies the bucket and prefix for the log objects in GCS ``gs://my-bucket/path/to/logs`` writes
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logs in ``my-bucket`` with ``path/to/logs`` prefix.
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You can set ``google_key_path`` option in the ``[logging]`` section to specify the path to `the service
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