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bitnami/airflow-worker

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By VMware

Updated 4 months ago

🛑 DEPRECATED Bitnami container image for Apache Airflow Worker

Image
Data Science
Integration & Delivery
Machine Learning & AI
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Bitnami package for Apache Airflow Worker

🛑 Deprecation Notice

The Apache Airflow Worker container is no longer maintained upstream and is now deprecated. This image will no longer be released in our catalog, but already released container images will persist in the registries.

After some months, this repository will be removed in favor of bitnami/airflow-worker-archived where all existing images can be found.

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 run --name airflow-worker bitnami/airflow-worker:latest

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 Notation. Check this post to know how 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 commercial edition of the Bitnami 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 the Docker Command Line
  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

Using docker-compose.yaml
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.

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.

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

Customizable environment variables

NameDescriptionDefault Value
AIRFLOW_EXECUTORAirflow executor.SequentialExecutor
AIRFLOW_RAW_FERNET_KEYAirflow raw/unencoded Fernet keynil
AIRFLOW_FERNET_KEYAirflow Fernet keynil
AIRFLOW_SECRET_KEYAirflow Secret keynil
AIRFLOW_FORCE_OVERWRITE_CONF_FILEForce the airflow.cfg config file generation.no
AIRFLOW_WEBSERVER_HOSTAirflow webserver host127.0.0.1
AIRFLOW_WEBSERVER_PORT_NUMBERAirflow webserver port.8080
AIRFLOW_HOSTNAME_CALLABLEMethod to obtain the hostname.nil
AIRFLOW_QUEUEA queue for the worker to pull tasks from.nil
AIRFLOW_DATABASE_HOSTHostname for PostgreSQL server.postgresql
AIRFLOW_DATABASE_PORT_NUMBERPort used by PostgreSQL server.5432
AIRFLOW_DATABASE_NAMEDatabase name that Airflow will use to connect with the database.bitnami_airflow
AIRFLOW_DATABASE_USERNAMEDatabase user that Airflow will use to connect with the database.bn_airflow
AIRFLOW_DATABASE_PASSWORDDatabase password that Airflow will use to connect with the database.nil
AIRFLOW_DATABASE_USE_SSLSet to yes if the database is using SSL.no
AIRFLOW_REDIS_USE_SSLSet to yes if Redis(R) uses SSL.no
REDIS_HOSTHostname for Redis(R) server.redis
REDIS_PORT_NUMBERPort used by Redis(R) server.6379
REDIS_USERUser that Airflow will use to connect with Redis(R).nil
REDIS_PASSWORDPassword that Airflow will use to connect with Redis(R).nil
REDIS_DATABASEName of the Redis(R) database.1

Read-only environment variables

NameDescriptionValue
AIRFLOW_BASE_DIRAirflow installation directory.${BITNAMI_ROOT_DIR}/airflow
AIRFLOW_HOMEAirflow home directory.${AIRFLOW_BASE_DIR}
AIRFLOW_BIN_DIRAirflow directory for binary executables.${AIRFLOW_BASE_DIR}/venv/bin
AIRFLOW_LOGS_DIRAirflow logs directory.${AIRFLOW_BASE_DIR}/logs
AIRFLOW_LOG_FILEAirflow logs directory.${AIRFLOW_LOGS_DIR}/airflow-worker.log
AIRFLOW_CONF_FILEAirflow configuration file.${AIRFLOW_BASE_DIR}/airflow.cfg
AIRFLOW_TMP_DIRAirflow directory temporary files.${AIRFLOW_BASE_DIR}/tmp
AIRFLOW_PID_FILEPath to the Airflow PID file.${AIRFLOW_TMP_DIR}/airflow-worker.pid
AIRFLOW_DAGS_DIRAirflow data to be persisted.${AIRFLOW_BASE_DIR}/dags
AIRFLOW_DAEMON_USERAirflow system user.airflow
AIRFLOW_DAEMON_GROUPAirflow system group.airflow

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

Starting January 16, 2024
  • The docker-compose.yaml file has been removed, as it was solely intended for internal testing purposes.
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 © 2024 Broadcom. The term "Broadcom" refers to Broadcom Inc. and/or its subsidiaries.

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.

Docker Pull Command

docker pull bitnami/airflow-worker
Bitnami