Show prominent warning for deprecations in docs

docs/apache-airflow-providers-google/operators/cloud/automl.rst

@@ -41,10 +41,11 @@ To create a Google AutoML dataset you can use
 :class:`~airflow.providers.google.cloud.operators.automl.AutoMLCreateDatasetOperator`.
 The operator returns dataset id in :ref:`XCom <concepts:xcom>` under ``dataset_id`` key.
 
-This operator is deprecated when running for text, video and vision prediction and will be removed soon.
-All the functionality of legacy AutoML Natural Language, Vision, Video Intelligence and new features are
-available on the Vertex AI platform. Please use
-:class:`~airflow.providers.google.cloud.operators.vertex_ai.dataset.CreateDatasetOperator`
+.. warning::
+    This operator is deprecated when running for text, video and vision prediction and will be removed soon.
+    All the functionality of legacy AutoML Natural Language, Vision, Video Intelligence and new features are
+    available on the Vertex AI platform. Please use
+    :class:`~airflow.providers.google.cloud.operators.vertex_ai.dataset.CreateDatasetOperator`
 
 .. exampleinclude:: /../../providers/tests/system/google/cloud/automl/example_automl_dataset.py
     :language: python
@@ -64,10 +65,11 @@ After creating a dataset you can use it to import some data using
 To update dataset you can use
 :class:`~airflow.providers.google.cloud.operators.automl.AutoMLTablesUpdateDatasetOperator`.
 
-This operator is deprecated when running for text, video and vision prediction and will be removed soon.
-All the functionality of legacy AutoML Natural Language, Vision, Video Intelligence and new features are
-available on the Vertex AI platform. Please use
-:class:`~airflow.providers.google.cloud.operators.vertex_ai.dataset.UpdateDatasetOperator`
+.. warning::
+    This operator is deprecated when running for text, video and vision prediction and will be removed soon.
+    All the functionality of legacy AutoML Natural Language, Vision, Video Intelligence and new features are
+    available on the Vertex AI platform. Please use
+    :class:`~airflow.providers.google.cloud.operators.vertex_ai.dataset.UpdateDatasetOperator`
 
 .. exampleinclude:: /../../providers/tests/system/google/cloud/vertex_ai/example_vertex_ai_dataset.py
     :language: python
@@ -102,14 +104,15 @@ To create a Google AutoML model you can use
 The operator will wait for the operation to complete. Additionally the operator
 returns the id of model in :ref:`XCom <concepts:xcom>` under ``model_id`` key.
 
-This operator is deprecated when running for text, video and vision prediction and will be removed soon.
-All the functionality of legacy AutoML Natural Language, Vision, Video Intelligence and new features are
-available on the Vertex AI platform. Please use
-:class:`~airflow.providers.google.cloud.operators.vertex_ai.generative_model.SupervisedFineTuningTrainOperator`,
-:class:`~airflow.providers.google.cloud.operators.vertex_ai.auto_ml.CreateAutoMLImageTrainingJobOperator` or
-:class:`~airflow.providers.google.cloud.operators.vertex_ai.auto_ml.CreateAutoMLVideoTrainingJobOperator`.
+.. warning::
+    This operator is deprecated when running for text, video and vision prediction and will be removed soon.
+    All the functionality of legacy AutoML Natural Language, Vision, Video Intelligence and new features are
+    available on the Vertex AI platform. Please use
+    :class:`~airflow.providers.google.cloud.operators.vertex_ai.generative_model.SupervisedFineTuningTrainOperator`,
+    :class:`~airflow.providers.google.cloud.operators.vertex_ai.auto_ml.CreateAutoMLImageTrainingJobOperator` or
+    :class:`~airflow.providers.google.cloud.operators.vertex_ai.auto_ml.CreateAutoMLVideoTrainingJobOperator`.
 
-You can find example on how to use VertexAI operators for AutoML Vision classification here:
+    You can find example on how to use VertexAI operators for AutoML Vision classification here:
 
 .. exampleinclude:: /../../providers/tests/system/google/cloud/automl/example_automl_vision_classification.py
     :language: python

docs/apache-airflow-providers-google/operators/cloud/datapipeline.rst

@@ -33,7 +33,8 @@ Prerequisite Tasks
 Creating a Data Pipeline
 ^^^^^^^^^^^^^^^^^^^^^^^^
 
-This operator is deprecated. Please use :class:`~airflow.providers.google.cloud.operators.dataflow.DataflowCreatePipelineOperator`.
+.. warning::
+   This operator is deprecated. Please use :class:`~airflow.providers.google.cloud.operators.dataflow.DataflowCreatePipelineOperator`.
 
 To create a new Data Pipelines instance using a request body and parent name, use :class:`~airflow.providers.google.cloud.operators.datapipeline.CreateDataPipelineOperator`.
 The operator accesses Google Cloud's Data Pipelines API and calls upon the
@@ -60,7 +61,8 @@ Here is an example of how you can create a Data Pipelines instance by running th
 Running a Data Pipeline
 ^^^^^^^^^^^^^^^^^^^^^^^
 
-This operator is deprecated. Please use :class:`~airflow.providers.google.cloud.operators.dataflow.DataflowRunPipelineOperator`.
+.. warning::
+   This operator is deprecated. Please use :class:`~airflow.providers.google.cloud.operators.dataflow.DataflowRunPipelineOperator`.
 
 To run a Data Pipelines instance, use :class:`~airflow.providers.google.cloud.operators.datapipeline.RunDataPipelineOperator`.
 The operator accesses Google Cloud's Data Pipelines API and calls upon the

docs/apache-airflow-providers-google/operators/cloud/mlengine.rst

@@ -45,9 +45,10 @@ This creates a virtual machine that can run code specified in the trainer file,
 contains the main application code. A job can be initiated with the
 :class:`~airflow.providers.google.cloud.operators.mlengine.MLEngineStartTrainingJobOperator`.
 
-This operator is deprecated. Please, use
-:class:`~airflow.providers.google.cloud.operators.vertex_ai.custom_job.CreateCustomPythonPackageTrainingJobOperator`
-instead.
+.. warning::
+    This operator is deprecated. Please, use
+    :class:`~airflow.providers.google.cloud.operators.vertex_ai.custom_job.CreateCustomPythonPackageTrainingJobOperator`
+    instead.
 
 .. exampleinclude:: /../../providers/tests/system/google/cloud/ml_engine/example_mlengine.py
     :language: python
@@ -64,10 +65,11 @@ A model is a container that can hold multiple model versions. A new model can be
 The ``model`` field should be defined with a dictionary containing the information about the model.
 ``name`` is a required field in this dictionary.
 
-This operator is deprecated. The model is created as a result of running Vertex AI operators that create training jobs
-of any types. For example, you can use
-:class:`~airflow.providers.google.cloud.operators.vertex_ai.custom_job.CreateCustomPythonPackageTrainingJobOperator`.
-The result of running this operator will be ready-to-use model saved in Model Registry.
+.. warning::
+    This operator is deprecated. The model is created as a result of running Vertex AI operators that create training jobs
+    of any types. For example, you can use
+    :class:`~airflow.providers.google.cloud.operators.vertex_ai.custom_job.CreateCustomPythonPackageTrainingJobOperator`.
+    The result of running this operator will be ready-to-use model saved in Model Registry.
 
 .. exampleinclude:: /../../providers/tests/system/google/cloud/ml_engine/example_mlengine.py
     :language: python
@@ -83,9 +85,10 @@ The :class:`~airflow.providers.google.cloud.operators.mlengine.MLEngineGetModelO
 can be used to obtain a model previously created. To obtain the correct model, ``model_name``
 must be defined in the operator.
 
-This operator is deprecated. Please, use
-:class:`~airflow.providers.google.cloud.operators.vertex_ai.model_service.GetModelOperator`
-instead.
+.. warning::
+    This operator is deprecated. Please, use
+    :class:`~airflow.providers.google.cloud.operators.vertex_ai.model_service.GetModelOperator`
+    instead.
 
 .. exampleinclude:: /../../providers/tests/system/google/cloud/ml_engine/example_mlengine.py
     :language: python
@@ -114,11 +117,12 @@ The model must be specified by ``model_name``, and the ``version`` parameter sho
 all the information about the version. Within the ``version`` parameter's dictionary, the ``name`` field is
 required.
 
-This operator is deprecated. Please, use
-:class:`~airflow.providers.google.cloud.operators.vertex_ai.custom_job.CreateCustomPythonPackageTrainingJobOperator`
-instead. In this case, the new version of specific model could be created by specifying existing model id in
-``parent_model`` parameter when running Training Job. This will ensure that new version of model will be trained except
-of creating new model.
+.. warning::
+    This operator is deprecated. Please, use
+    :class:`~airflow.providers.google.cloud.operators.vertex_ai.custom_job.CreateCustomPythonPackageTrainingJobOperator`
+    instead. In this case, the new version of specific model could be created by specifying existing model id in
+    ``parent_model`` parameter when running Training Job. This will ensure that new version of model will be trained except
+    of creating new model.
 
 .. exampleinclude:: /../../providers/tests/system/google/cloud/ml_engine/example_mlengine.py
     :language: python
@@ -144,12 +148,13 @@ By default, the model code will run using the default model version. You can set
 :class:`~airflow.providers.google.cloud.operators.mlengine.MLEngineSetDefaultVersionOperator`
 by specifying the ``model_name`` and ``version_name`` parameters.
 
-This operator is deprecated. Please, use
-:class:`~airflow.providers.google.cloud.operators.vertex_ai.model_service.SetDefaultVersionOnModelOperator`
-instead. The desired model version to be set as default could be passed with the model ID in ``model_id`` parameter
-in format ``projects/{project}/locations/{location}/models/{model_id}@{version_id}`` or
-``projects/{project}/locations/{location}/models/{model_id}@{version_alias}``. By default, the first model version
-created will be marked as default.
+.. warning::
+    This operator is deprecated. Please, use
+    :class:`~airflow.providers.google.cloud.operators.vertex_ai.model_service.SetDefaultVersionOnModelOperator`
+    instead. The desired model version to be set as default could be passed with the model ID in ``model_id`` parameter
+    in format ``projects/{project}/locations/{location}/models/{model_id}@{version_id}`` or
+    ``projects/{project}/locations/{location}/models/{model_id}@{version_alias}``. By default, the first model version
+    created will be marked as default.
 
 .. exampleinclude:: /../../providers/tests/system/google/cloud/ml_engine/example_mlengine.py
     :language: python
@@ -161,10 +166,11 @@ To list the model versions available, use the
 :class:`~airflow.providers.google.cloud.operators.mlengine.MLEngineListVersionsOperator`
 while specifying the ``model_name`` parameter.
 
-This operator is deprecated. Please, use
-:class:`~airflow.providers.google.cloud.operators.vertex_ai.model_service.ListModelVersionsOperator`
-instead. You can pass the name of the desired model in ``model_id`` parameter. If the model ID is passed
-with version aliases, the operator will output all the versions available for this model.
+.. warning::
+    This operator is deprecated. Please, use
+    :class:`~airflow.providers.google.cloud.operators.vertex_ai.model_service.ListModelVersionsOperator`
+    instead. You can pass the name of the desired model in ``model_id`` parameter. If the model ID is passed
+    with version aliases, the operator will output all the versions available for this model.
 
 .. exampleinclude:: /../../providers/tests/system/google/cloud/ml_engine/example_mlengine.py
     :language: python
@@ -181,9 +187,10 @@ A Google Cloud AI Platform prediction job can be started with the
 For specifying the model origin, you need to provide either the ``model_name``, ``uri``, or ``model_name`` and
 ``version_name``. If you do not provide the ``version_name``, the operator will use the default model version.
 
-This operator is deprecated. Please, use
-:class:`~airflow.providers.google.cloud.operators.vertex_ai.batch_prediction_job.CreateBatchPredictionJobOperator`
-instead.
+.. warning::
+    This operator is deprecated. Please, use
+    :class:`~airflow.providers.google.cloud.operators.vertex_ai.batch_prediction_job.CreateBatchPredictionJobOperator`
+    instead.
 
 .. exampleinclude:: /../../providers/tests/system/google/cloud/ml_engine/example_mlengine.py
     :language: python
@@ -200,9 +207,10 @@ A model version can be deleted with the
 :class:`~airflow.providers.google.cloud.operators.mlengine.MLEngineDeleteVersionOperator` by
 the ``version_name`` and ``model_name`` parameters.
 
-This operator is deprecated. Please, use
-:class:`~airflow.providers.google.cloud.operators.vertex_ai.model_service.DeleteModelVersionOperator`
-instead. The default version could not be deleted on the model.
+.. warning::
+    This operator is deprecated. Please, use
+    :class:`~airflow.providers.google.cloud.operators.vertex_ai.model_service.DeleteModelVersionOperator`
+    instead. The default version could not be deleted on the model.
 
 .. exampleinclude:: /../../providers/tests/system/google/cloud/ml_engine/example_mlengine.py
     :language: python
@@ -214,9 +222,10 @@ You can also delete a model with the
 :class:`~airflow.providers.google.cloud.operators.mlengine.MLEngineDeleteModelOperator`
 by providing the ``model_name`` parameter.
 
-This operator is deprecated. Please, use
-:class:`~airflow.providers.google.cloud.operators.vertex_ai.model_service.DeleteModelOperator`
-instead.
+.. warning::
+    This operator is deprecated. Please, use
+    :class:`~airflow.providers.google.cloud.operators.vertex_ai.model_service.DeleteModelOperator`
+    instead.
 
 .. exampleinclude:: /../../providers/tests/system/google/cloud/ml_engine/example_mlengine.py
     :language: python

docs/apache-airflow/administration-and-deployment/production-deployment.rst

@@ -47,7 +47,7 @@ Once that is done, you can run -
 
 ``migrate`` keeps track of migrations already applied, so it's safe to run as often as you need.
 
-.. note::
+.. warning::
 
     Prior to Airflow version 2.7.0, ``airflow db upgrade`` was used to apply migrations,
     however, it has been deprecated in favor of ``airflow db migrate``.

docs/apache-airflow/installation/setting-up-the-database.rst

@@ -26,7 +26,7 @@ Usually, you need to run ``airflow db migrate`` in order to create the database
 or migrate to the latest version if it does. You should make sure that Airflow components are
 not running while the database migration is being executed.
 
-.. note::
+.. warning::
 
     Prior to Airflow version 2.7.0, ``airflow db upgrade`` was used to apply migrations,
     however, it has been deprecated in favor of ``airflow db migrate``.

docs/apache-airflow/installation/upgrading.rst

@@ -81,7 +81,7 @@ Sample usage for Airflow version 2.7.0 or greater:
    ``airflow db migrate -s --from-version "2.4.3" -n "2.7.3"``
    ``airflow db migrate --show-sql-only --from-version "2.4.3" --to-version "2.7.3"``
 
-.. note::
+.. warning::
     ``airflow db upgrade`` has been replaced by ``airflow db migrate`` since Airflow version 2.7.0
     and former has been deprecated.