pierrejeambrun commented on code in PR #60818:
URL: https://github.com/apache/airflow/pull/60818#discussion_r2829116260
##########
airflow-core/docs/administration-and-deployment/logging-monitoring/advanced-logging-configuration.rst:
##########
@@ -68,9 +68,11 @@ Follow the steps below to enable custom logging config class:
.. code-block:: python
from copy import deepcopy
- from airflow.config_templates.airflow_local_settings import
DEFAULT_LOGGING_CONFIG
- LOGGING_CONFIG = deepcopy(DEFAULT_LOGGING_CONFIG)
+ # Airflow 3.x and later uses structlog for logging configuration.
+ # The legacy DEFAULT_LOGGING_CONFIG dict is no longer respected.
+ # See the migration note below for details.
+ # Example: To customize logging, use structlog configuration as described
in the Airflow documentation.
Review Comment:
Doesn't seem related to the PR
##########
airflow-core/docs/core-concepts/backfill.rst:
##########
@@ -47,6 +47,24 @@ Run ordering
You can run your backfill in reverse, i.e. latest runs first. The CLI option
is ``--run-backwards``.
+Running backfills on paused DAGs
+---------------------------------
+
+Airflow allows backfills to run on paused DAGs. This is useful when:
+
+* You need to reprocess historical data without activating the regular DAG
schedule
+* The data source is not available for regular runs
+* You want to avoid unnecessary computation and logs from scheduled triggers
+
+When you create a backfill on a paused DAG, only the backfill runs will
execute—the DAG remains paused and will not be triggered by its regular
schedule.
+
+**Via UI**: When creating a backfill for a paused DAG, you can:
+
+- **Check "Unpause on trigger"**: This will unpause the DAG before running the
backfill (and regular schedules will resume)
+- **Uncheck "Unpause on trigger"** (default): The backfill will run but the
DAG stays paused
Review Comment:
Did you manually test this, are the backfill runs succeeding now ?
##########
airflow-core/docs/administration-and-deployment/logging-monitoring/advanced-logging-configuration.rst:
##########
@@ -117,25 +119,11 @@ Example of custom logging for the
``SQLExecuteQueryOperator`` and the ``HttpHook
from copy import deepcopy
from pydantic.utils import deep_update
- from airflow.config_templates.airflow_local_settings import
DEFAULT_LOGGING_CONFIG
- LOGGING_CONFIG = deep_update(
- deepcopy(DEFAULT_LOGGING_CONFIG),
- {
- "loggers": {
-
"airflow.task.operators.airflow.providers.common.sql.operators.sql.SQLExecuteQueryOperator":
{
- "handlers": ["task"],
- "level": "DEBUG",
- "propagate": True,
- },
-
"airflow.task.hooks.airflow.providers.http.hooks.http.HttpHook": {
- "handlers": ["task"],
- "level": "WARNING",
- "propagate": False,
- },
- }
- },
- )
+ # Airflow 3.x and later uses structlog for logging configuration.
+ # The legacy DEFAULT_LOGGING_CONFIG dict is no longer respected.
+ # See the migration note below for details.
+ # Example: To customize logging, use structlog configuration as
described in the Airflow documentation.
Review Comment:
Same
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