Quick start with kind¶
This article will show you how to install Airflow using Helm Chart on Kind
Install kind, and create a cluster¶
We recommend testing with Kubernetes 1.20+, example:
kind create cluster --image kindest/node:v1.21.1
Confirm it’s up:
kubectl cluster-info --context kind-kind
Add Airflow Helm Stable Repo¶
helm repo add apache-airflow https://airflow.apache.org
helm repo update
Create namespace¶
export NAMESPACE=example-namespace
kubectl create namespace $NAMESPACE
Install the chart¶
export RELEASE_NAME=example-release
helm install $RELEASE_NAME apache-airflow/airflow --namespace $NAMESPACE
Use the following code to install the chart with Example DAGs:
export NAMESPACE=example-namespace
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:
kubectl get pods --namespace $NAMESPACE
helm list --namespace $NAMESPACE
Run the following command to port-forward the Airflow UI to http://localhost:8080/ to confirm Airflow is working.
kubectl port-forward svc/$RELEASE_NAME-webserver 8080:8080 --namespace $NAMESPACE
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.
The best way to achieve it, is to build your own, custom image.
Adding DAGs to your image¶
Create a project
mkdir my-airflow-project && cd my-airflow-project mkdir dags # put dags here cat <<EOM > Dockerfile FROM apache/airflow COPY . . EOM
Then build the image:
docker build --pull --tag my-dags:0.0.1 .
Load the image into kind:
kind load docker-image my-dags:0.0.1
Upgrade Helm deployment:
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.
Create a project
mkdir my-airflow-project && cd my-airflow-project cat <<EOM > 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
Then build the image:
docker build --pull --tag my-image:0.0.1 .
Load the image into kind:
kind load docker-image my-image:0.0.1
Upgrade Helm deployment:
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.
Create a project
mkdir my-airflow-project && cd my-airflow-project cat <<EOM > Dockerfile FROM apache/airflow RUN pip install --no-cache-dir lxml EOM
Then build the image:
docker build --pull --tag my-image:0.0.1 .
Load the image into kind:
kind load docker-image my-image:0.0.1
Upgrade Helm deployment:
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.