.. 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.
Quick start with kind
=====================
This article will show you how to install Airflow using Helm Chart on `Kind `__.
Run Airflow on Kind cluster
---------------------------
Install kind and create a cluster
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
We recommend testing with Kubernetes 1.30+, example:
.. code-block:: bash
kind create cluster --image kindest/node:v1.30.13
Confirm it's up:
.. code-block:: bash
kubectl cluster-info --context kind-kind
Add Airflow Helm Stable Repo
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.. code-block:: bash
helm repo add apache-airflow https://airflow.apache.org
helm repo update
Create namespace
^^^^^^^^^^^^^^^^
.. code-block:: bash
export NAMESPACE=example-namespace
kubectl create namespace $NAMESPACE
.. note::
Same exported ``NAMESPACE`` variable will be used in the next instructions.
Install the chart
^^^^^^^^^^^^^^^^^
.. code-block:: bash
export RELEASE_NAME=example-release
helm install $RELEASE_NAME apache-airflow/airflow --namespace $NAMESPACE
.. note::
Same exported ``RELEASE_NAME`` variable will be used in the next instructions.
Use the following code to install the chart with example Dags:
.. code-block:: bash
helm install $RELEASE_NAME apache-airflow/airflow \
--namespace $NAMESPACE \
--set-string "env[0].name=AIRFLOW__CORE__LOAD_EXAMPLES" \
--set-string "env[0].value=True"
It may take a few minutes. Confirm the pods are up:
.. code-block:: bash
kubectl get pods --namespace $NAMESPACE
helm list --namespace $NAMESPACE
Run the following command to port-forward the Airflow UI to http://localhost:8080/ to confirm
Airflow is working.
.. code-block:: bash
kubectl port-forward svc/$RELEASE_NAME-api-server 8080:8080 --namespace $NAMESPACE
.. _quick-start:extending-airflow-image:
Extending Airflow Image
-----------------------
The Apache Airflow community, releases Docker Images which are ``reference images`` for Apache Airflow.
However, when you try it out you want to add your own Dags, custom dependencies, packages, or even custom providers.
.. note::
Creating custom images means that you need to maintain also a level of automation as you need to re-create the images
when either the packages you want to install or Airflow is upgraded. Do not forget about keeping these scripts.
Also keep in mind, that in cases when you run pure Python tasks, you can use the
`Python Virtualenv functions `_
which will dynamically source and install python dependencies during runtime. Virtualenvs can also be cached.
The best way to achieve it, is to build your own, custom image.
Adding Dags to your image
^^^^^^^^^^^^^^^^^^^^^^^^^
1. Create a project:
.. code-block:: bash
mkdir my-airflow-project && cd my-airflow-project
mkdir dags # put dags here
cat < Dockerfile
FROM apache/airflow
COPY . .
EOM
2. Then build the image:
.. code-block:: bash
docker build --pull --tag my-dags:0.0.1 .
3. Load the image into kind:
.. code-block:: bash
kind load docker-image my-dags:0.0.1
4. Upgrade Helm deployment:
.. code-block:: bash
helm upgrade $RELEASE_NAME apache-airflow/airflow --namespace $NAMESPACE \
--set images.airflow.repository=my-dags \
--set images.airflow.tag=0.0.1
Adding ``apt`` packages to your image
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Example below adds ``vim`` apt package.
1. Create a project:
.. code-block:: bash
mkdir my-airflow-project && cd my-airflow-project
cat < Dockerfile
FROM apache/airflow
USER root
RUN apt-get update \
&& apt-get install -y --no-install-recommends vim \
&& apt-get autoremove -yqq --purge \
&& apt-get clean \
&& rm -rf /var/lib/apt/lists/*
USER airflow
EOM
2. Then build the image:
.. code-block:: bash
docker build --pull --tag my-image:0.0.1 .
3. Load the image into kind:
.. code-block:: bash
kind load docker-image my-image:0.0.1
4. Upgrade Helm deployment:
.. code-block:: bash
helm upgrade $RELEASE_NAME apache-airflow/airflow --namespace $NAMESPACE \
--set images.airflow.repository=my-image \
--set images.airflow.tag=0.0.1
Adding ``PyPI`` packages to your image
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Example below adds ``lxml`` PyPI package.
1. Create a project:
.. code-block:: bash
mkdir my-airflow-project && cd my-airflow-project
cat < Dockerfile
FROM apache/airflow
RUN pip install --no-cache-dir lxml
EOM
2. Then build the image:
.. code-block:: bash
docker build --pull --tag my-image:0.0.1 .
3. Load the image into kind:
.. code-block:: bash
kind load docker-image my-image:0.0.1
4. Upgrade Helm deployment:
.. code-block:: bash
helm upgrade $RELEASE_NAME apache-airflow/airflow --namespace $NAMESPACE \
--set images.airflow.repository=my-image \
--set images.airflow.tag=0.0.1
Further extending and customizing the image
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
See `Building the image `_ for more
details on how you can extend and customize the Airflow image.