Official airflow helm chart6/23/2023 If you can provide description of a reproducible problem with Airflow software, you can openissue at GitHub issues The GitHub discussionsif you look for longer discussion and have more information to share. The #troubleshooting channel on Airflow Slack for quick generaltroubleshooting questions. The Docker Image is managed by the same people who build Airflow, and they are committed to keepit updated whenever new features and capabilities of Airflow are released.įor quick questions with the Official Docker Image there is the #production-docker-image channel in Airflow Slack. However this is just an inspiration.Do not expect to use this docker-compose.yml file for production installation, you need to get familiarwith Docker Compose and its capabilities and build your own production-ready deployment with it ifyou choose Docker Compose for your deployment. You have Running Airflow in Docker where you can see an example of Quick Start whichyou can use to start Airflow quickly for local testing and development. You have instructions: Building the image on how to build and customize your image. You can use your own custom mechanism, custom Kubernetes deployments,custom Docker Compose, custom Helm charts etc., and you should choose it based on your experienceand expectations. There a number of available options ofdeployments of containers. You should choose the right deployment mechanism. However you are responsible in creating apipeline of building your own custom images with your own added dependencies and Providers and need torepeat the customization step and building your own image when new version of Airflow image is released. You are responsible to manage your own customizations and extensions for your custom dependencies.With the Official Airflow Docker Images, upgrades of Airflow and Airflow Providers whichare part of the reference image are handled by the community - you need to make sure to pick upthose changes when released by upgrading the base image. You are responsible for setting up database, creating and managing database schema with airflow db commands,automated startup and recovery, maintenance, cleanup and upgrades of Airflow and the Airflow Providers. You are expected to put together a deployment built of several containers(for example using docker-compose) and to make sure that they are linked together. You are expected to be able to customize or extend Container/Docker images if you want toadd extra dependencies. Users who know how to create deployments using Docker by linking together multiple Docker containers and maintaining such deployments. Users who understand how to install providers and dependencies from PyPI with constraints if they want to extend or customize the image. Users who are familiar with Containers and Docker stack and understand how to build their own container images. You have Installation from PyPIon how to install the software but due to various environments and tools you might want to use, you mightexpect that there will be problems which are specific to your deployment and environment you will have todiagnose and solve. What Apache Airflow Community provides for that method You are responsible for setting up database, creating and managing database schema with airflow db commands,automated startup and recovery, maintenance, cleanup and upgrades of Airflow and Airflow Providers. You should develop and handle the deployment for all components of Airflow. You are expected to install Airflow - all components of it - on your own. Users who are familiar with installing and configuring Python applications, managing Python environments,dependencies and running software with their custom deployment mechanisms. In case of PyPI installation you could also verify integrity and provenance of the packages of the packagesdownloaded from PyPI as described at the installation page, but software you download from PyPI is pre-builtfor you so that you can install it without building, and you do not build the software from sources. The constraintfiles are managed by Apache Airflow release managers to make sure that you can repeatably install Airflow from PyPI with all Providers andrequired dependencies. The only officially supported mechanism of installation is via pip using constraint mechanisms.
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