 .. Licensed to the Apache Software Foundation (ASF) under one
    or more contributor license agreements.  See the NOTICE file
    distributed with this work for additional information
    regarding copyright ownership.  The ASF licenses this file
    to you under the Apache License, Version 2.0 (the
    "License"); you may not use this file except in compliance
    with the License.  You may obtain a copy of the License at

 ..   http://www.apache.org/licenses/LICENSE-2.0

 .. Unless required by applicable law or agreed to in writing,
    software distributed under the License is distributed on an
    "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
    KIND, either express or implied.  See the License for the
    specific language governing permissions and limitations
    under the License.

Production Guide
================

The following are things to consider when using this Helm chart in a production environment.

Database
--------

You will want to use an external database instead of the one deployed with the chart by default.
Both **PostgresSQL** and **MySQL** are supported. Supported versions can be
found on the :doc:`Set up a Database Backend <apache-airflow:howto/set-up-database>` page.

.. code-block:: yaml

  # Don't deploy postgres
  postgresql:
    enabled: false

  # Use an external database
  data:
    metadataConnection:
      user: ...
      pass: ...
      protocol: postgresql  # or 'mysql'
      host: ...
      port: ...
      db: ...

.. _production-guide:pgbouncer:

PgBouncer
---------

If you are using PostgresSQL as your database, you will likely want to enable `PgBouncer <https://www.pgbouncer.org/>`_ as well.
Airflow can open a lot of database connections due to its distributed nature and using a connection pooler can significantly
reduce the number of open connections on the database.

.. code-block:: yaml

  pgbouncer:
    enabled: true

Depending on the size of you Airflow instance, you may want to adjust the following as well (defaults are shown):

.. code-block:: yaml

  pgbouncer:
    # The maximum number of connections to PgBouncer
    maxClientConn: 100
    # The maximum number of server connections to the metadata database from PgBouncer
    metadataPoolSize: 10
    # The maximum number of server connections to the result backend database from PgBouncer
    resultBackendPoolSize: 5

Webserver Secret Key
--------------------

You should set a static webserver secret key when deploying with this chart as it will help ensure
your Airflow components only restart when necessary.

.. warning::
  You should use a different secret key for every instance you run, as this key is used to sign
  session cookies and perform other security related functions!

First, generate a strong secret key:

.. code-block:: bash

    python3 -c 'import secrets; print(secrets.token_hex(16))'

Now add the secret to your values file:

.. code-block:: yaml

    webserverSecretKey: <secret_key>

Alternatively, create a kubernetes Secret and use ``webserverSecretKeySecretName``:

.. code-block:: yaml

    webserverSecretKey: my-webserver-secret
    # where the random key is under `webserver-secret-key` in the k8s Secret

Extending and customizing Airflow Image
---------------------------------------

The Apache Airflow community, releases Docker Images which are ``reference images`` for Apache Airflow.
However, Airflow has more than 60 community managed providers (installable via extras) and some of the
default extras/providers installed are not used by everyone, sometimes others extras/providers
are needed, sometimes (very often actually) you need to add your own custom dependencies,
packages or even custom providers, or add custom tools and binaries that are needed in
your deployment.

In Kubernetes and Docker terms this means that you need another image with your specific requirements.
This is why you should learn how to build your own ``Docker`` (or more properly ``Container``) image.

Typical scenarios where you would like to use your custom image:

* Adding ``apt`` packages
* Adding ``PyPI`` packages
* Adding binary resources necessary for your deployment
* Adding custom tools needed in your deployment

See `Building the image <https://airflow.apache.org/docs/docker-stack/build.html>`_ for more
details on how you can extend and customize the Airflow image.

Managing DAG Files
------------------

See :doc:`manage-dags-files`.

.. _production-guide:knownhosts:

knownHosts
^^^^^^^^^^

If you are using ``dags.gitSync.sshKeySecret``, you should also set ``dags.gitSync.knownHosts``. Here we will show the process
for GitHub, but the same can be done for any provider:

Grab GitHub's public key:

.. code-block:: bash

    ssh-keyscan -t rsa github.com > github_public_key

Next, print the fingerprint for the public key:

.. code-block:: bash

    ssh-keygen -lf github_public_key

Compare that output with `GitHub's SSH key fingerprints <https://docs.github.com/en/github/authenticating-to-github/githubs-ssh-key-fingerprints>`_.

They match, right? Good. Now, add the public key to your values. It'll look something like this:

.. code-block:: yaml

    dags:
      gitSync:
        knownHosts: |
          github.com ssh-rsa AAAA...FAaQ==


Accessing the Airflow UI
------------------------

How you access the Airflow UI will depend on your environment, however the chart does support various options:

Ingress
^^^^^^^

You can create and configure ``Ingress`` objects. See the :ref:`Ingress chart parameters <parameters:ingress>`.
For more information on ``Ingress``, see the
`Kubernetes Ingress documentation <https://kubernetes.io/docs/concepts/services-networking/ingress/>`_.

LoadBalancer Service
^^^^^^^^^^^^^^^^^^^^

You can change the Service type for the webserver to be ``LoadBalancer``, and set any necessary annotations:

.. code-block:: yaml

  webserver:
    service: LoadBalancer
    annotations: {}

For more information on ``LoadBalancer`` Services, see the `Kubernetes LoadBalancer Service Documentation
<https://kubernetes.io/docs/concepts/services-networking/service/#loadbalancer>`_.

Logging
-------

Depending on your choice of executor, task logs may not work out of the box. All logging choices can be found
at :doc:`manage-logs`.

Metrics
-------

The chart can support sending metrics to an existing StatsD instance or provide a Prometheus endpoint.

Prometheus
^^^^^^^^^^

The metrics endpoint is available at ``svc/{{ .Release.Name }}-statsd:9102/metrics``.

External StatsD
^^^^^^^^^^^^^^^

To use an external StatsD instance:

.. code-block:: yaml

  statsd:
    enabled: false
  config:
    metrics:  # or 'scheduler' for Airflow 1
      statsd_on: true
      statsd_host: ...
      statsd_port: ...

Celery Backend
--------------

If you are using ``CeleryExecutor`` or ``CeleryKubernetesExecutor``, you can bring your own Celery backend.

By default, the chart will deploy Redis. However, you can use any supported Celery backend instead:

.. code-block:: yaml

  redis:
    enabled: false
  data:
    brokerUrl: redis://redis-user:password@redis-host:6379/0

For more information about setting up a Celery broker, refer to the
exhaustive `Celery documentation on the topic <http://docs.celeryproject.org/en/latest/getting-started/>`_.