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[bitnami/airflow] Release 3.1.7-debian-12-r4 (#91064)

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Signed-off-by: Bitnami Bot <bitnami.bot@broadcom.com>
This commit is contained in:
Bitnami Bot
2026-02-24 13:37:04 +01:00
committed by GitHub
parent 6df835f7e5
commit 432b398d39
2 changed files with 4 additions and 321 deletions
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bitnami/airflow/3/debian-12/Dockerfile
+4 -4
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@@ -7,7 +7,7 @@ ARG DOWNLOADS_URL="downloads.bitnami.com/files/stacksmith"
ARG TARGETARCH
LABEL org.opencontainers.image.base.name="docker.io/bitnami/minideb:bookworm" \
org.opencontainers.image.created="2026-02-19T00:35:50Z" \
org.opencontainers.image.created="2026-02-24T11:51:32Z" \
org.opencontainers.image.description="Application packaged by Broadcom, Inc." \
org.opencontainers.image.documentation="https://github.com/bitnami/containers/tree/main/bitnami/airflow/README.md" \
org.opencontainers.image.source="https://github.com/bitnami/containers/tree/main/bitnami/airflow" \
@@ -31,8 +31,8 @@ RUN --mount=type=secret,id=downloads_url,env=SECRET_DOWNLOADS_URL \
"nss-wrapper-1.1.16-0-linux-${OS_ARCH}-debian-12" \
"ini-file-1.4.9-7-linux-${OS_ARCH}-debian-12" \
"wait-for-port-1.0.10-7-linux-${OS_ARCH}-debian-12" \
"airflow-3.1.7-0-linux-${OS_ARCH}-debian-12" \
"python-3.12.12-16-linux-${OS_ARCH}-debian-12" \
"airflow-3.1.7-1-linux-${OS_ARCH}-debian-12" \
"python-3.12.12-19-linux-${OS_ARCH}-debian-12" \
) ; \
for COMPONENT in "${COMPONENTS[@]}"; do \
if [ ! -f "${COMPONENT}.tar.gz" ]; then \
@@ -59,7 +59,7 @@ RUN /opt/bitnami/scripts/airflow/postunpack.sh
ENV AIRFLOW_HOME="/opt/bitnami/airflow" \
APP_VERSION="3.1.7" \
BITNAMI_APP_NAME="airflow" \
IMAGE_REVISION="3" \
IMAGE_REVISION="4" \
LANG="en_US.UTF-8" \
LANGUAGE="en_US:en" \
LD_LIBRARY_PATH="/opt/bitnami/python/lib:/opt/bitnami/airflow/venv/lib/python3.12/site-packages/numpy.libs:$LD_LIBRARY_PATH" \
bitnami/airflow/README.md
-317
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@@ -37,110 +37,14 @@ If you are looking for our previous generation of images based on Debian Linux,
Learn more about the Bitnami tagging policy and the difference between rolling tags and immutable tags [in our documentation page](https://techdocs.broadcom.com/us/en/vmware-tanzu/application-catalog/tanzu-application-catalog/services/tac-doc/apps-tutorials-understand-rolling-tags-containers-index.html).
## Prerequisites
To run this application you need [Docker Engine](https://www.docker.com/products/docker-engine) >= `1.10.0`. [Docker Compose](https://docs.docker.com/compose/) is recommended with a version `1.6.0` or later.
## How to use this image
Airflow requires access to a PostgreSQL database to store information. We will use the [Bitnami PostgreSQL image](https://github.com/bitnami/containers/tree/main/bitnami/postgresql) for the database requirements. Additionally, if you pretend to use the `CeleryExecutor`, you will also need a [Bitnami Redis(R) server](https://github.com/bitnami/containers/tree/main/bitnami/redis).
### Using the Docker Command Line
1. Create a network
```console
docker network create airflow-tier
```
2. Create a volume for PostgreSQL persistence and create a PostgreSQL container
```console
docker volume create --name postgresql_data
docker run -d --name postgresql \
-e POSTGRESQL_USERNAME=bn_airflow \
-e POSTGRESQL_PASSWORD=bitnami1 \
-e POSTGRESQL_DATABASE=bitnami_airflow \
--net airflow-tier \
--volume postgresql_data:/bitnami/postgresql \
bitnami/postgresql:latest
```
3. Create a volume for Redis(R) persistence and create a Redis(R) container
```console
docker volume create --name redis_data
docker run -d --name redis \
-e ALLOW_EMPTY_PASSWORD=yes \
--net airflow-tier \
--volume redis_data:/bitnami \
bitnami/redis:latest
```
4. Launch the Apache Airflow web container
```console
docker run -d --name airflow -p 8080:8080 \
-e AIRFLOW_FERNET_KEY=46BKJoQYlPPOexq0OhDZnIlNepKFf87WFwLbfzqDDho= \
-e AIRFLOW_SECRET_KEY=a25mQ1FHTUh3MnFRSk5KMEIyVVU2YmN0VGRyYTVXY08= \
-e AIRFLOW_EXECUTOR=CeleryExecutor \
-e AIRFLOW_DATABASE_NAME=bitnami_airflow \
-e AIRFLOW_DATABASE_USERNAME=bn_airflow \
-e AIRFLOW_DATABASE_PASSWORD=bitnami1 \
-e AIRFLOW_LOAD_EXAMPLES=yes \
-e AIRFLOW_PASSWORD=bitnami123 \
-e AIRFLOW_USERNAME=user \
-e AIRFLOW_EMAIL=user@example.com \
--net airflow-tier \
bitnami/airflow:latest
```
5. Launch the Apache Airflow scheduler container
```console
docker run -d --name airflow-scheduler \
-e AIRFLOW_COMPONENT_TYPE=scheduler \
-e AIRFLOW_FERNET_KEY=46BKJoQYlPPOexq0OhDZnIlNepKFf87WFwLbfzqDDho= \
-e AIRFLOW_SECRET_KEY=a25mQ1FHTUh3MnFRSk5KMEIyVVU2YmN0VGRyYTVXY08= \
-e AIRFLOW_EXECUTOR=CeleryExecutor \
-e AIRFLOW_DATABASE_NAME=bitnami_airflow \
-e AIRFLOW_DATABASE_USERNAME=bn_airflow \
-e AIRFLOW_DATABASE_PASSWORD=bitnami1 \
-e AIRFLOW_LOAD_EXAMPLES=yes \
-e AIRFLOW_WEBSERVER_HOST=airflow \
--net airflow-tier \
bitnami/airflow:latest
```
6. Launch the Apache Airflow worker container
```console
docker run -d --name airflow-worker \
-e AIRFLOW_COMPONENT_TYPE=worker \
-e AIRFLOW_FERNET_KEY=46BKJoQYlPPOexq0OhDZnIlNepKFf87WFwLbfzqDDho= \
-e AIRFLOW_SECRET_KEY=a25mQ1FHTUh3MnFRSk5KMEIyVVU2YmN0VGRyYTVXY08= \
-e AIRFLOW_EXECUTOR=CeleryExecutor \
-e AIRFLOW_DATABASE_NAME=bitnami_airflow \
-e AIRFLOW_DATABASE_USERNAME=bn_airflow \
-e AIRFLOW_DATABASE_PASSWORD=bitnami1 \
-e AIRFLOW_WEBSERVER_HOST=airflow \
--net airflow-tier \
bitnami/airflow:latest
```
Access your application at `http://your-ip:8080`
### Using `docker-compose.yaml`
```console
curl -LO https://raw.githubusercontent.com/bitnami/containers/main/bitnami/airflow/docker-compose.yml
docker-compose up
```
Please be aware this file has not undergone internal testing. Consequently, we advise its use exclusively for development or testing purposes. For production-ready deployments, we highly recommend utilizing its associated [Bitnami Helm chart](https://github.com/bitnami/charts/tree/main/bitnami/airflow).
If you detect any issue in the `docker-compose.yaml` file, feel free to report it or contribute with a fix by following our [Contributing Guidelines](https://github.com/bitnami/containers/blob/main/CONTRIBUTING.md).
### Persisting your application
The Bitnami Airflow container relies on the PostgreSQL database & Redis to persist the data. This means that Airflow does not persist anything. To avoid loss of data, you should mount volumes for persistence of [PostgreSQL data](https://github.com/bitnami/containers/blob/main/bitnami/mariadb#persisting-your-database) and [Redis(R) data](https://github.com/bitnami/containers/blob/main/bitnami/redis#persisting-your-database)
@@ -149,146 +53,6 @@ The above examples define docker volumes namely `postgresql_data`, and `redis_da
To avoid inadvertent removal of these volumes you can [mount host directories as data volumes](https://docs.docker.com/engine/tutorials/dockervolumes/). Alternatively you can make use of volume plugins to host the volume data.
#### Mount host directories as data volumes with Docker Compose
The following `docker-compose.yml` template demonstrates the use of host directories as data volumes.
```yaml
version: '2'
services:
postgresql:
image: bitnami/postgresql:latest
environment:
- POSTGRESQL_DATABASE=bitnami_airflow
- POSTGRESQL_USERNAME=bn_airflow
- POSTGRESQL_PASSWORD=bitnami1
volumes:
- /path/to/postgresql-persistence:/bitnami/postgresql
redis:
image: bitnami/redis:latest
environment:
- ALLOW_EMPTY_PASSWORD=yes
volumes:
- /path/to/redis-persistence:/bitnami
airflow-worker:
image: bitnami/airflow:latest
environment:
- AIRFLOW_COMPONENT_TYPE=worker
- AIRFLOW_FERNET_KEY=46BKJoQYlPPOexq0OhDZnIlNepKFf87WFwLbfzqDDho=
- AIRFLOW_SECRET_KEY=a25mQ1FHTUh3MnFRSk5KMEIyVVU2YmN0VGRyYTVXY08=
- AIRFLOW_EXECUTOR=CeleryExecutor
- AIRFLOW_DATABASE_NAME=bitnami_airflow
- AIRFLOW_DATABASE_USERNAME=bn_airflow
- AIRFLOW_DATABASE_PASSWORD=bitnami1
- AIRFLOW_LOAD_EXAMPLES=yes
airflow-scheduler:
image: bitnami/airflow:latest
environment:
- AIRFLOW_COMPONENT_TYPE=scheduler
- AIRFLOW_FERNET_KEY=46BKJoQYlPPOexq0OhDZnIlNepKFf87WFwLbfzqDDho=
- AIRFLOW_SECRET_KEY=a25mQ1FHTUh3MnFRSk5KMEIyVVU2YmN0VGRyYTVXY08=
- AIRFLOW_EXECUTOR=CeleryExecutor
- AIRFLOW_DATABASE_NAME=bitnami_airflow
- AIRFLOW_DATABASE_USERNAME=bn_airflow
- AIRFLOW_DATABASE_PASSWORD=bitnami1
- AIRFLOW_LOAD_EXAMPLES=yes
airflow:
image: bitnami/airflow:latest
environment:
- AIRFLOW_FERNET_KEY=46BKJoQYlPPOexq0OhDZnIlNepKFf87WFwLbfzqDDho=
- AIRFLOW_SECRET_KEY=a25mQ1FHTUh3MnFRSk5KMEIyVVU2YmN0VGRyYTVXY08=
- AIRFLOW_EXECUTOR=CeleryExecutor
- AIRFLOW_DATABASE_NAME=bitnami_airflow
- AIRFLOW_DATABASE_USERNAME=bn_airflow
- AIRFLOW_DATABASE_PASSWORD=bitnami1
- AIRFLOW_PASSWORD=bitnami123
- AIRFLOW_USERNAME=user
- AIRFLOW_EMAIL=user@example.com
ports:
- 8080:8080
```
#### Mount host directories as data volumes using the Docker command line
1. Create a network (if it does not exist)
```console
docker network create airflow-tier
```
2. Create the PostgreSQL container with host volumes
```console
docker run -d --name postgresql \
-e POSTGRESQL_USERNAME=bn_airflow \
-e POSTGRESQL_PASSWORD=bitnami1 \
-e POSTGRESQL_DATABASE=bitnami_airflow \
--net airflow-tier \
--volume /path/to/postgresql-persistence:/bitnami \
bitnami/postgresql:latest
```
3. Create the Redis(R) container with host volumes
```console
docker run -d --name redis \
-e ALLOW_EMPTY_PASSWORD=yes \
--net airflow-tier \
--volume /path/to/redis-persistence:/bitnami \
bitnami/redis:latest
```
4. Create the Airflow container
```console
docker run -d --name airflow -p 8080:8080 \
-e AIRFLOW_FERNET_KEY=46BKJoQYlPPOexq0OhDZnIlNepKFf87WFwLbfzqDDho= \
-e AIRFLOW_SECRET_KEY=a25mQ1FHTUh3MnFRSk5KMEIyVVU2YmN0VGRyYTVXY08= \
-e AIRFLOW_EXECUTOR=CeleryExecutor \
-e AIRFLOW_DATABASE_NAME=bitnami_airflow \
-e AIRFLOW_DATABASE_USERNAME=bn_airflow \
-e AIRFLOW_DATABASE_PASSWORD=bitnami1 \
-e AIRFLOW_LOAD_EXAMPLES=yes \
-e AIRFLOW_PASSWORD=bitnami123 \
-e AIRFLOW_USERNAME=user \
-e AIRFLOW_EMAIL=user@example.com \
--net airflow-tier \
bitnami/airflow:latest
```
5. Create the Airflow Scheduler container
```console
docker run -d --name airflow-scheduler \
-e AIRFLOW_COMPONENT_TYPE=scheduler \
-e AIRFLOW_FERNET_KEY=46BKJoQYlPPOexq0OhDZnIlNepKFf87WFwLbfzqDDho= \
-e AIRFLOW_SECRET_KEY=a25mQ1FHTUh3MnFRSk5KMEIyVVU2YmN0VGRyYTVXY08= \
-e AIRFLOW_EXECUTOR=CeleryExecutor \
-e AIRFLOW_DATABASE_NAME=bitnami_airflow \
-e AIRFLOW_DATABASE_USERNAME=bn_airflow \
-e AIRFLOW_DATABASE_PASSWORD=bitnami1 \
-e AIRFLOW_LOAD_EXAMPLES=yes \
-e AIRFLOW_WEBSERVER_HOST=airflow \
--net airflow-tier \
bitnami/airflow:latest
```
6. Create the Airflow Worker container
```console
docker run -d --name airflow-worker \
-e AIRFLOW_COMPONENT_TYPE=worker \
-e AIRFLOW_FERNET_KEY=46BKJoQYlPPOexq0OhDZnIlNepKFf87WFwLbfzqDDho= \
-e AIRFLOW_SECRET_KEY=a25mQ1FHTUh3MnFRSk5KMEIyVVU2YmN0VGRyYTVXY08= \
-e AIRFLOW_EXECUTOR=CeleryExecutor \
-e AIRFLOW_DATABASE_NAME=bitnami_airflow \
-e AIRFLOW_DATABASE_USERNAME=bn_airflow \
-e AIRFLOW_DATABASE_PASSWORD=bitnami1 \
-e AIRFLOW_WEBSERVER_HOST=airflow \
--net airflow-tier \
bitnami/airflow:latest
```
## Configuration
### Load DAG files
@@ -376,42 +140,6 @@ This container supports the installation of additional python modules at start-u
> In addition to the previous environment variables, all the parameters from the configuration file can be overwritten by using environment variables with this format: `AIRFLOW__{SECTION}__{KEY}`. Note the double underscores.
#### Specifying Environment variables using Docker Compose
```yaml
version: '2'
services:
airflow:
image: bitnami/airflow:latest
environment:
- AIRFLOW_FERNET_KEY=46BKJoQYlPPOexq0OhDZnIlNepKFf87WFwLbfzqDDho=
- AIRFLOW_SECRET_KEY=a25mQ1FHTUh3MnFRSk5KMEIyVVU2YmN0VGRyYTVXY08=
- AIRFLOW_EXECUTOR=CeleryExecutor
- AIRFLOW_DATABASE_NAME=bitnami_airflow
- AIRFLOW_DATABASE_USERNAME=bn_airflow
- AIRFLOW_DATABASE_PASSWORD=bitnami1
- AIRFLOW_PASSWORD=bitnami123
- AIRFLOW_USERNAME=user
- AIRFLOW_EMAIL=user@example.com
```
#### Specifying Environment variables on the Docker command line
```console
docker run -d --name airflow -p 8080:8080 \
-e AIRFLOW_FERNET_KEY=46BKJoQYlPPOexq0OhDZnIlNepKFf87WFwLbfzqDDho= \
-e AIRFLOW_SECRET_KEY=a25mQ1FHTUh3MnFRSk5KMEIyVVU2YmN0VGRyYTVXY08= \
-e AIRFLOW_EXECUTOR=CeleryExecutor \
-e AIRFLOW_DATABASE_NAME=bitnami_airflow \
-e AIRFLOW_DATABASE_USERNAME=bn_airflow \
-e AIRFLOW_DATABASE_PASSWORD=bitnami1 \
-e AIRFLOW_PASSWORD=bitnami123 \
-e AIRFLOW_USERNAME=user \
-e AIRFLOW_EMAIL=user@example.com \
bitnami/airflow:latest
```
#### SMTP Configuration
To configure Airflow to send email using SMTP you can set the following environment variables:
@@ -424,51 +152,6 @@ To configure Airflow to send email using SMTP you can set the following environm
- `AIRFLOW__SMTP__SMTP_PASSWORD`: Password for SMTP. No defaults.
- `AIRFLOW__SMTP__SMTP_MAIL_FROM`: To modify the "from email address". Default: **<airflow@example.com>**
This would be an example of SMTP configuration using a GMail account:
- docker-compose (application part):
```yaml
airflow:
image: bitnami/airflow:latest
environment:
- AIRFLOW_FERNET_KEY=46BKJoQYlPPOexq0OhDZnIlNepKFf87WFwLbfzqDDho=
- AIRFLOW_SECRET_KEY=a25mQ1FHTUh3MnFRSk5KMEIyVVU2YmN0VGRyYTVXY08=
- AIRFLOW_EXECUTOR=CeleryExecutor
- AIRFLOW_DATABASE_NAME=bitnami_airflow
- AIRFLOW_DATABASE_USERNAME=bn_airflow
- AIRFLOW_DATABASE_PASSWORD=bitnami1
- AIRFLOW_PASSWORD=bitnami
- AIRFLOW_USERNAME=user
- AIRFLOW_EMAIL=user@email.com
- AIRFLOW__SMTP__SMTP_HOST=smtp@gmail.com
- AIRFLOW__SMTP__SMTP_USER=your_email@gmail.com
- AIRFLOW__SMTP__SMTP_PASSWORD=your_password
- AIRFLOW__SMTP__SMTP_PORT=587
ports:
- 8080:8080
```
- For manual execution:
```console
docker run -d --name airflow -p 8080:8080 \
-e AIRFLOW_FERNET_KEY=46BKJoQYlPPOexq0OhDZnIlNepKFf87WFwLbfzqDDho= \
-e AIRFLOW_SECRET_KEY=a25mQ1FHTUh3MnFRSk5KMEIyVVU2YmN0VGRyYTVXY08= \
-e AIRFLOW_EXECUTOR=CeleryExecutor \
-e AIRFLOW_DATABASE_NAME=bitnami_airflow \
-e AIRFLOW_DATABASE_USERNAME=bn_airflow \
-e AIRFLOW_DATABASE_PASSWORD=bitnami1 \
-e AIRFLOW_PASSWORD=bitnami123 \
-e AIRFLOW_USERNAME=user \
-e AIRFLOW_EMAIL=user@example.com \
-e AIRFLOW__SMTP__SMTP_HOST=smtp@gmail.com \
-e AIRFLOW__SMTP__SMTP_USER=your_email@gmail.com \
-e AIRFLOW__SMTP__SMTP_PASSWORD=your_password \
-e AIRFLOW__SMTP__SMTP_PORT=587 \
bitnami/airflow:latest
```
### FIPS configuration in Bitnami Secure Images
The Bitnami Apache Airflow Docker image from the [Bitnami Secure Images](https://go-vmware.broadcom.com/contact-us) catalog includes extra features and settings to configure the container with FIPS capabilities. You can configure the next environment variables: