bitnami-containers/bitnami/airflow-worker

Bitnami package for Apache Airflow Worker

What is Apache Airflow Worker?

Apache Airflow is a tool to express and execute workflows as directed acyclic graphs (DAGs). Airflow workers listen to, and process, queues containing workflow tasks.

Overview of Apache Airflow Worker Trademarks: This software listing is packaged by Bitnami. The respective trademarks mentioned in the offering are owned by the respective companies, and use of them does not imply any affiliation or endorsement.

TL;DR

Docker Compose

curl -LO https://raw.githubusercontent.com/bitnami/containers/main/bitnami/airflow-worker/docker-compose.yml
docker-compose up

You can find the default credentials and available configuration options in the Environment Variables section.

Why use Bitnami Images?

• Bitnami closely tracks upstream source changes and promptly publishes new versions of this image using our automated systems.
• With Bitnami images the latest bug fixes and features are available as soon as possible.
• Bitnami containers, virtual machines and cloud images use the same components and configuration approach - making it easy to switch between formats based on your project needs.
• All our images are based on minideb -a minimalist Debian based container image that gives you a small base container image and the familiarity of a leading Linux distribution- or scratch -an explicitly empty image-.
• All Bitnami images available in Docker Hub are signed with Docker Content Trust (DCT). You can use DOCKER_CONTENT_TRUST=1 to verify the integrity of the images.
• Bitnami container images are released on a regular basis with the latest distribution packages available.

Looking to use Apache Airflow Worker in production? Try VMware Tanzu Application Catalog, the enterprise edition of Bitnami Application Catalog.

Supported tags and respective Dockerfile links

Learn more about the Bitnami tagging policy and the difference between rolling tags and immutable tags in our documentation page.

You can see the equivalence between the different tags by taking a look at the tags-info.yaml file present in the branch folder, i.e bitnami/ASSET/BRANCH/DISTRO/tags-info.yaml.

Subscribe to project updates by watching the bitnami/containers GitHub repo.

Prerequisites

To run this application you need Docker Engine >= 1.10.0. Docker Compose is recommended with a version 1.6.0 or later.

How to use this image

Airflow Worker is a component of an Airflow solution configuring with the CeleryExecutor. Hence, you will need to rest of Airflow components for this image to work. You will need an Airflow Webserver, an Airflow Scheduler, a PostgreSQL database and a Redis(R) server.

Using Docker Compose

The main folder of this repository contains a functional docker-compose.yml file. Run the application using it as shown below:

curl -sSL https://raw.githubusercontent.com/bitnami/containers/main/bitnami/airflow-worker/docker-compose.yml > docker-compose.yml
docker-compose up -d

Using the Docker Command Line

If you want to run the application manually instead of using docker-compose, these are the basic steps you need to run:

1. Create a network

   docker network create airflow-tier
   

2. Create a volume for PostgreSQL persistence and create a PostgreSQL container

   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

   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 Worker web container

   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 Worker scheduler container

   docker run -d --name airflow-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 \
     --net airflow-tier \
     bitnami/airflow-scheduler:latest
   

6. Launch the Apache Airflow Worker worker container

   docker run -d --name airflow-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_QUEUE=new_queue \
     --net airflow-tier \
     bitnami/airflow-worker:latest
   

Access your application at http://your-ip:8080

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 and Redis(R) data

The above examples define docker volumes namely postgresql_data, and redis_data. The Airflow application state will persist as long as these volumes are not removed.

To avoid inadvertent removal of these volumes you can mount host directories as data volumes. 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.

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
  redis:
    image: 'bitnami/redis:latest'
    environment:
      - ALLOW_EMPTY_PASSWORD=yes
    volumes:
      - /path/to/redis-persistence:/bitnami
  airflow-worker:
    image: bitnami/airflow-worker: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_LOAD_EXAMPLES=yes
  airflow-scheduler:
    image: bitnami/airflow-scheduler: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_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)

   docker network create airflow-tier
   

2. Create the PostgreSQL container with host volumes

   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

   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

   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

   docker run -d --name airflow-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 \
     --net airflow-tier \
       bitnami/airflow-scheduler:latest
   

6. Create the Airflow Worker container

   docker run -d --name airflow-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 \
     --net airflow-tier \
     bitnami/airflow-worker:latest
   

Configuration

Installing additional python modules

This container supports the installation of additional python modules at start-up time. In order to do that, you can mount a requirements.txt file with your specific needs under the path /bitnami/python/requirements.txt.

Environment variables

The Airflow Worker instance can be customized by specifying environment variables on the first run. The following environment values are provided to customize Airflow Worker:

Airflow Worker configuration

• AIRFLOW_EXECUTOR: Airflow Worker executor. Default: SequentialExecutor
• AIRFLOW_FERNET_KEY: Airflow Worker Fernet key. No defaults.
• AIRFLOW_SECRET_KEY: Airflow Worker Secret key. No defaults.
• AIRFLOW_WEBSERVER_HOST: Airflow Worker webserver host. Default: airflow
• AIRFLOW_WEBSERVER_PORT_NUMBER: Airflow Worker webserver port. Default: 8080
• AIRFLOW_HOSTNAME_CALLABLE: Method to obtain the hostname. No defaults.
• AIRFLOW_QUEUE: A queue for the worker to pull tasks from. No defaults.

Use an existing database

• AIRFLOW_DATABASE_HOST: Hostname for PostgreSQL server. Default: postgresql
• AIRFLOW_DATABASE_PORT_NUMBER: Port used by PostgreSQL server. Default: 5432
• AIRFLOW_DATABASE_NAME: Database name that Airflow Worker will use to connect with the database. Default: bitnami_airflow
• AIRFLOW_DATABASE_USERNAME: Database user that Airflow Worker will use to connect with the database. Default: bn_airflow
• AIRFLOW_DATABASE_PASSWORD: Database password that Airflow Worker will use to connect with the database. No defaults.
• AIRFLOW_DATABASE_USE_SSL: Set to yes if the database uses SSL. Default: no
• AIRFLOW_REDIS_USE_SSL: Set to yes if Redis(R) uses SSL. Default: no
• REDIS_HOST: Hostname for Redis(R) server. Default: redis
• REDIS_PORT_NUMBER: Port used by Redis(R) server. Default: 6379
• REDIS_USER: User that Airflow Worker will use to connect with Redis(R). No defaults.
• REDIS_PASSWORD: Password that Airflow Worker will use to connect with Redis(R). No defaults.
• REDIS_DATABASE: Database number for Redis(R) server. Default: 1

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

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

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

Notable Changes

1.10.15-debian-10-r18 and 2.0.1-debian-10-r51

• The size of the container image has been decreased.
• The configuration logic is now based on Bash scripts in the rootfs/ folder.

Contributing

We'd love for you to contribute to this Docker image. You can request new features by creating an issue or submitting a pull request with your contribution.

Issues

If you encountered a problem running this container, you can file an issue. For us to provide better support, be sure to fill the issue template.

License

Copyright © 2023 VMware, Inc.

Licensed 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.