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.. contents:: :local:
Airflow docker images
=====================
Airflow has two images (build from Dockerfiles):
* CI image (Dockerfile.ci) - used for running tests and local development
* Production image (Dockerfile) - used to run production-ready Airflow installations
Image naming conventions
========================
The images are named as follows:
``apache/airflow:<BRANCH_OR_TAG>-python<PYTHON_MAJOR_MINOR_VERSION>[-ci][-manifest]``
where:
* ``BRANCH_OR_TAG`` - branch or tag used when creating the image. Examples: ``master``, ``v1-10-test``, ``1.10.10``
The ``master`` and ``v1-10-test`` labels are built from branches so they change over time. The ``1.10.*`` and in
the future ``2.*`` labels are build from git tags and they are "fixed" once built.
* ``PYTHON_MAJOR_MINOR_VERSION`` - version of python used to build the image. Examples: ``3.5``, ``3.7``
* The ``-ci`` suffix is added for CI images
* The ``-manifest`` is added for manifest images (see below for explanation of manifest images)
Building docker images
======================
The easiest way to build those images is to use `<BREEZE.rst>`_.
Note! Breeze by default builds production image from local sources. You can change it's behaviour by
providing ``--install-airflow-version`` parameter, where you can specify the
tag/branch used to download Airflow package from in github repository. You can
also change the repository itself by adding ``--dockerhub-user`` and ``--dockerhub-repo`` flag values.
You can build the CI image using this command:
.. code-block:: bash
./breeze build-image
You can build production image using this command:
.. code-block:: bash
./breeze build-image --production-image
By adding ``--python <PYTHON_MAJOR_MINOR_VERSION>`` parameter you can build the
image version for the chosen python version.
The images are build with default extras - different extras for CI and production image and you
can change the extras via the ``--extras`` parameters. You can see default extras used via
``./breeze flags``.
For example if you want to build python 3.7 version of production image with
"all" extras installed you should run this command:
.. code-block:: bash
./breeze build-image --python 3.7 --extras "all" --production-image
The command that builds the CI image is optimized to minimize the time needed to rebuild the image when
the source code of Airflow evolves. This means that if you already have the image locally downloaded and
built, the scripts will determine whether the rebuild is needed in the first place. Then the scripts will
make sure that minimal number of steps are executed to rebuild parts of the image (for example,
PIP dependencies) and will give you an image consistent with the one used during Continuous Integration.
The command that builds the production image is optimised for size of the image.
In Breeze by default, the airflow is installed using local sources of Apache Airflow.
You can also build production images from PIP packages via providing ``--install-airflow-version``
parameter to Breeze:
.. code-block:: bash
./breeze build-image --python 3.7 --extras=gcp --production-image --install-airflow-version=1.10.9
This will build the image using command similar to:
.. code-block:: bash
pip install apache-airflow[sendgrid]==1.10.9 \
--constraint https://raw.githubusercontent.com/apache/airflow/v1-10-test/requirements/requirements-python3.7.txt
The requirement files only appeared in version 1.10.10 of airflow so if you install
an earlier version - both constraint and requirements should point to 1.10.10 version.
You can also build production images from specific Git version via providing ``--install-airflow-reference``
parameter to Breeze:
.. code-block:: bash
pip install https://github.com/apache/airflow/archive/<tag>.tar.gz#egg=apache-airflow \
--constraint https://raw.githubusercontent.com/apache/airflow/<tag>/requirements/requirements-python3.7.txt
Using cache during builds
=========================
Default mechanism used in Breeze for building CI images uses images pulled from DockerHub or
GitHub Image Registry. This is done to speed up local builds and CI builds - instead of 15 minutes
for rebuild of CI images, it takes usually less than 3 minutes when cache is used. For CI builds this is
usually the best strategy - to use default "pull" cache. This is default strategy when
`<BREEZE.rst>`_ builds are performed.
For Production Image - which is far smaller and faster to build, it's better to use local build cache (the
standard mechanism that docker uses. This is the default strategy for production images when
`<BREEZE.rst>`_ builds are performed. The first time you run it, it will take considerably longer time than
if you use the pull mechanism, but then when you do small, incremental changes to local sources,
Dockerfile image= and scripts further rebuilds with local build cache will be considerably faster.
You can also disable build cache altogether. This is the strategy used by the scheduled builds in CI - they
will always rebuild all the images from scratch.
You can change the strategy by providing one of the ``--build-cache-local``, ``--build-cache-pulled`` or
even ``--build-cache-disabled`` flags when you run Breeze commands. For example:
.. code-block:: bash
./breeze build-image --python 3.7 --build-cache-local
Will build the CI image using local build cache (note that it will take quite a long time the first
time you run it).
.. code-block:: bash
./breeze build-image --python 3.7 --production-image --build-cache-pulled
Will build the production image with pulled images as cache.
.. code-block:: bash
./breeze build-image --python 3.7 --production-image --build-cache-disabled
Will build the production image from the scratch.
You can also turn local docker caching by setting ``DOCKER_CACHE`` variable to "local", "pulled",
"disabled" and exporting it.
.. code-block:: bash
export DOCKER_CACHE="local"
or
.. code-block:: bash
export DOCKER_CACHE="disabled"
Choosing image registry
=======================
By default images are pulled and pushed from and to DockerHub registry when you use Breeze's push-image
or build commands.
Our images are named like that:
.. code-block:: bash
apache/airflow:<BRANCH_OR_TAG>[-<PATCH>]-pythonX.Y - for production images
apache/airflow:<BRANCH_OR_TAG>[-<PATCH>]-pythonX.Y-ci - for CI images
apache/airflow:<BRANCH_OR_TAG>[-<PATCH>]-pythonX.Y-build - for production build stage
For example:
.. code-block:: bash
apache/airflow:master-python3.6 - production "latest" image from current master
apache/airflow:master-python3.6-ci - CI "latest" image from current master
apache/airflow:v1-10-test-python2.7-ci - CI "latest" image from current v1-10-test branch
apache/airflow:1.10.10-python3.6 - production image for 1.10.10 release
apache/airflow:1.10.10-1-python3.6 - production image for 1.10.10 with some patches applied
You can see DockerHub images at `<https://hub.docker.com/repository/docker/apache/airflow>`_
By default DockerHub registry is used when you push or pull such images.
However for CI builds we keep the images in GitHub registry as well - this way we can easily push
the images automatically after merge requests and use such images for Pull Requests
as cache - which makes it much it much faster for CI builds (images are available in cache
right after merged request in master finishes it's build), The difference is visible especially if
significant changes are done in the Dockerfile.CI.
The images are named differently (in Docker definition of image names - registry URL is part of the
image name if DockerHub is not used as registry). Also GitHub has its own structure for registries
each project has its own registry naming convention that should be followed. The name of
images for GitHub registry are:
.. code-block:: bash
docker.pkg.github.com/apache/airflow/<BRANCH>-pythonX.Y - for production images
docker.pkg.github.com/apache/airflow/<BRANCH>-pythonX.Y-ci - for CI images
docker.pkg.github.com/apache/airflow/<BRANCH>-pythonX.Y-build - for production build state
Note that we never push or pull TAG images to GitHub registry. It is only used for CI builds
You can see all the current GitHub images at `<https://github.com/apache/airflow/packages>`_
In order to interact with the GitHub images you need to add ``--github-registry`` flag to the pull/push
commands in Breeze. This way the images will be pulled/pushed from/to GitHub rather than from/to
DockerHub. Images are build locally as ``apache/airflow`` images but then they are tagged with the right
GitHub tags for you.
You can read more about the CI configuration and how CI builds are using DockerHub/GitHub images
in `<CI.rst>`_.
Note that you need to be committer and have the right to push to DockerHub and GitHub and you need to
be logged in. Only committers can push images directly.
Technical details of Airflow images
===================================
The CI image is used by Breeze as shell image but it is also used during CI build.
The image is single segment image that contains Airflow installation with "all" dependencies installed.
It is optimised for rebuild speed. It installs PIP dependencies from the current branch first -
so that any changes in setup.py do not trigger reinstalling of all dependencies.
There is a second step of installation that re-installs the dependencies
from the latest sources so that we are sure that latest dependencies are installed.
The production image is a multi-segment image. The first segment "airflow-build-image" contains all the
build essentials and related dependencies that allow to install airflow locally. By default the image is
build from a released version of Airflow from Github, but by providing some extra arguments you can also
build it from local sources. This is particularly useful in CI environment where we are using the image
to run Kubernetes tests. See below for the list of arguments that should be provided to build
production image from the local sources.
The image is primarily optimised for size of the final image, but also for speed of rebuilds - the
'airlfow-build-image' segment uses the same technique as the CI builds for pre-installing PIP dependencies.
It first pre-installs them from the right github branch and only after that final airflow installation is
done from either local sources or remote location (PIP or github repository).
Manually building the images
----------------------------
You can build the default production image with standard ``docker build`` command but they will only build
default versions of the image and will not use the dockerhub versions of images as cache.
CI images
.........
The following build arguments (``--build-arg`` in docker build command) can be used for CI images:
+------------------------------------------+------------------------------------------+------------------------------------------+
| Build argument | Default value | Description |
+==========================================+==========================================+==========================================+
| ``PYTHON_BASE_IMAGE`` | ``python:3.6-slim-buster`` | Base python image |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``AIRFLOW_VERSION`` | ``2.0.0.dev0`` | version of Airflow |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``PYTHON_MAJOR_MINOR_VERSION`` | ``3.6`` | major/minor version of Python (should |
| | | match base image) |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``DEPENDENCIES_EPOCH_NUMBER`` | ``2`` | increasing this number will reinstall |
| | | all apt dependencies |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``PIP_NO_CACHE_DIR`` | ``true`` | if true, then no pip cache will be |
| | | stored |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``PIP_VERSION`` | ``19.0.2`` | version of PIP to use |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``HOME`` | ``/root`` | Home directory of the root user (CI |
| | | image has root user as default) |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``AIRFLOW_HOME`` | ``/root/airflow`` | Airflow’s HOME (that’s where logs and |
| | | sqlite databases are stored) |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``AIRFLOW_SOURCES`` | ``/opt/airflow`` | Mounted sources of Airflow |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``PIP_DEPENDENCIES_EPOCH_NUMBER`` | ``3`` | increasing that number will reinstall |
| | | all PIP dependencies |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``CASS_DRIVER_NO_CYTHON`` | ``1`` | if set to 1 no CYTHON compilation is |
| | | done for cassandra driver (much faster) |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``AIRFLOW_REPO`` | ``apache/airflow`` | the repository from which PIP |
| | | dependencies are pre-installed |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``AIRFLOW_BRANCH`` | ``master`` | the branch from which PIP dependencies |
| | | are pre-installed |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``AIRFLOW_CI_BUILD_EPOCH`` | ``1`` | increasing this value will reinstall PIP |
| | | dependencies from the repository from |
| | | scratch |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``AIRFLOW_EXTRAS`` | ``all`` | extras to install |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``ADDITIONAL_AIRFLOW_EXTRAS`` | | additional extras to install |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``ADDITIONAL_PYTHON_DEPS`` | | additional python dependencies to |
| | | install |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``ADDITIONAL_DEV_DEPS`` | | additional apt dev dependencies to |
| | | install |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``ADDITIONAL_RUNTIME_DEPS`` | | additional apt runtime dependencies to |
| | | install |
+------------------------------------------+------------------------------------------+------------------------------------------+
Here are some examples of how CI images can built manually. CI is always built from local sources.
This builds the CI image in version 3.7 with default extras ("all").
.. code-block:: bash
docker build . -f Dockerfile.ci --build-arg PYTHON_BASE_IMAGE="python:3.7-slim-buster" \
--build-arg PYTHON_MAJOR_MINOR_VERSION=3.7
This builds the CI image in version 3.6 with "gcp" extra only.
.. code-block:: bash
docker build . -f Dockerfile.ci --build-arg PYTHON_BASE_IMAGE="python:3.7-slim-buster" \
--build-arg PYTHON_MAJOR_MINOR_VERSION=3.6 --build-arg AIRFLOW_EXTRAS=gcp
This builds the CI image in version 3.6 with "apache-beam" extra added.
.. code-block:: bash
docker build . -f Dockerfile.ci --build-arg PYTHON_BASE_IMAGE="python:3.7-slim-buster" \
--build-arg PYTHON_MAJOR_MINOR_VERSION=3.6 --build-arg ADDITIONAL_AIRFLOW_EXTRAS="apache-beam"
This builds the CI image in version 3.6 with "mssql" additional package added.
.. code-block:: bash
docker build . -f Dockerfile.ci --build-arg PYTHON_BASE_IMAGE="python:3.7-slim-buster" \
--build-arg PYTHON_MAJOR_MINOR_VERSION=3.6 --build-arg ADDITIONAL_PYTHON_DEPS="mssql"
This builds the CI image in version 3.6 with "gcc" and "g++" additional apt dev dependencies added.
.. code-block::
docker build . -f Dockerfile.ci --build-arg PYTHON_BASE_IMAGE="python:3.7-slim-buster" \
--build-arg PYTHON_MAJOR_MINOR_VERSION=3.6 --build-arg ADDITIONAL_DEV_DEPS="gcc g++"
This builds the CI image in version 3.6 with "jdbc" extra and "default-jre-headless" additional apt runtime dependencies added.
.. code-block::
docker build . -f Dockerfile.ci --build-arg PYTHON_BASE_IMAGE="python:3.7-slim-buster" \
--build-arg PYTHON_MAJOR_MINOR_VERSION=3.6 --build-arg AIRFLOW_EXTRAS=jdbc --build-arg ADDITIONAL_RUNTIME_DEPS="default-jre-headless"
Production images
.................
The following build arguments (``--build-arg`` in docker build command) can be used for production images:
+------------------------------------------+------------------------------------------+------------------------------------------+
| Build argument | Default value | Description |
+==========================================+==========================================+==========================================+
| ``PYTHON_BASE_IMAGE`` | ``python:3.6-slim-buster`` | Base python image |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``PYTHON_MAJOR_MINOR_VERSION`` | ``3.6`` | major/minor version of Python (should |
| | | match base image) |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``AIRFLOW_VERSION`` | ``2.0.0.dev0`` | version of Airflow |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``AIRFLOW_ORG`` | ``apache`` | Github organisation from which Airflow |
| | | is installed (when installed from repo) |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``AIRFLOW_REPO`` | ``apache/airflow`` | the repository from which PIP |
| | | dependencies are pre-installed |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``AIRFLOW_BRANCH`` | ``master`` | the branch from which PIP dependencies |
| | | are pre-installed |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``AIRFLOW_GIT_REFERENCE`` | ``master`` | reference (branch or tag) from Github |
| | | repository from which Airflow is |
| | | installed (when installed from repo) |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``REQUIREMENTS_GIT_REFERENCE`` | ``master`` | reference (branch or tag) from Github |
| | | repository from which requirements are |
| | | downloaded for constraints (when |
| | | installed from repo). |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``AIRFLOW_EXTRAS`` | (see Dockerfile) | Default extras with which airflow is |
| | | installed |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``ADDITIONAL_AIRFLOW_EXTRAS`` | | Optional additional extras with which |
| | | airflow is installed |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``ADDITIONAL_PYTHON_DEPS`` | | Optional python packages to extend |
| | | the image with some extra dependencies |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``ADDITIONAL_DEV_DEPS`` | | additional apt dev dependencies to |
| | | install |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``ADDITIONAL_RUNTIME_DEPS`` | | additional apt runtime dependencies to |
| | | install |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``EMBEDDED_DAGS`` | ``empty`` | Folder containing dags embedded into the |
| | | image in the ${AIRFLOW_HOME}/dags dir |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``AIRFLOW_HOME`` | ``/opt/airflow`` | Airflow’s HOME (that’s where logs and |
| | | sqlite databases are stored) |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``AIRFLOW_UID`` | ``50000`` | Airflow user UID |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``AIRFLOW_GID`` | ``50000`` | Airflow group GID. Note that most files |
| | | created on behalf of airflow user belong |
| | | to the ``root`` group (0) to keep |
| | | OpenShift Guidelines compatibility |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``AIRFLOW_USER_HOME_DIR`` | ``/home/airflow`` | Home directory of the Airflow user |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``PIP_VERSION`` | ``19.0.2`` | version of PIP to use |
+------------------------------------------+------------------------------------------+------------------------------------------+
| ``CASS_DRIVER_BUILD_CONCURRENCY`` | ``8`` | Number of processors to use for |
| | | cassandra PIP install (speeds up |
| | | installing in case cassandra extra is |
| | | used). |
+------------------------------------------+------------------------------------------+------------------------------------------+
There are build arguments that determine the installation mechanism of Apache Airflow for the
production image. There are three types of build:
* From local sources (by default for example when you use ``docker build .``)
* You can build the image from released PyPi airflow package (used to build the official Docker image)
* You can build the image from any version in GitHub repository(this is used mostly for system testing).
+-----------------------------------+-----------------------------------+
| Build argument | What to specify |
+===================================+===================================+
| ``AIRFLOW_INSTALL_SOURCES`` | Should point to the sources of |
| | of Apache Airflow. It can be |
| | either "." for installation from |
| | local sources, "apache-airflow" |
| | for installation from packages |
| | and URL to installation from |
| | GitHub repository (see below) |
| | to install from any GitHub |
| | version |
+-----------------------------------+-----------------------------------+
| ``AIRFLOW_INSTALL_VERSION`` | Optional - might be used for |
| | package installation case to |
| | set Airflow version for example |
| | "==1.10.10" |
+-----------------------------------+-----------------------------------+
| ``CONSTRAINT_REQUIREMENTS`` | Should point to requirements file |
| | in case of installation from |
| | the package or from GitHub URL. |
| | See examples below |
+-----------------------------------+-----------------------------------+
| ``AIRFLOW_WWW`` | In case of Airflow 2.0 it should |
| | be "www", in case of Airflow 1.10 |
| | series it should be "www_rbac". |
| | See examples below |
+-----------------------------------+-----------------------------------+
| ``AIRFLOW_SOURCES_FROM`` | Sources of Airflow. Set it to |
| | "empty" to avoid costly |
| | Docker context copying |
| | in case of installation from |
| | the package or from GitHub URL. |
| | See examples below |
+-----------------------------------+-----------------------------------+
| ``AIRFLOW_SOURCES_TO`` | Target for Airflow sources. Set |
| | to "/empty" to avoid costly |
| | Docker context copying |
| | in case of installation from |
| | the package or from GitHub URL. |
| | See examples below |
+-----------------------------------+-----------------------------------+
This builds production image in version 3.6 with default extras from the local sources (master version
of 2.0 currently):
.. code-block:: bash
docker build .
This builds the production image in version 3.7 with default extras from 1.10.9 tag and
requirements taken from v1-10-test branch in Github.
Note that versions 1.10.9 and below have no requirements so requirements should be taken from head of
the 1.10.10 tag.
.. code-block:: bash
docker build . \
--build-arg PYTHON_BASE_IMAGE="python:3.7-slim-buster" \
--build-arg PYTHON_MAJOR_MINOR_VERSION=3.7 \
--build-arg AIRFLOW_INSTALL_SOURCES="https://github.com/apache/airflow/archive/1.10.10.tar.gz#egg=apache-airflow" \
--build-arg CONSTRAINT_REQUIREMENTS="https://raw.githubusercontent.com/apache/airflow/1.10.10/requirements/requirements-python3.7.txt" \
--build-arg AIRFLOW_BRANCH="v1-10-test" \
--build-arg AIRFLOW_SOURCES_FROM="empty" \
--build-arg AIRFLOW_SOURCES_TO="/empty"
This builds the production image in version 3.7 with default extras from 1.10.10 Pypi package and
requirements taken from 1.10.10 tag in Github and pre-installed pip dependencies from the top
of v1-10-test branch.
.. code-block:: bash
docker build . \
--build-arg PYTHON_BASE_IMAGE="python:3.7-slim-buster" \
--build-arg PYTHON_MAJOR_MINOR_VERSION=3.7 \
--build-arg AIRFLOW_INSTALL_SOURCES="apache-airflow" \
--build-arg AIRFLOW_INSTALL_VERSION="==1.10.10" \
--build-arg AIRFLOW_BRANCH="v1-10-test" \
--build-arg CONSTRAINT_REQUIREMENTS="https://raw.githubusercontent.com/apache/airflow/1.10.10/requirements/requirements-python3.7.txt" \
--build-arg AIRFLOW_SOURCES_FROM="empty" \
--build-arg AIRFLOW_SOURCES_TO="/empty"
This builds the production image in version 3.7 with additional airflow extras from 1.10.10 Pypi package and
additional python dependencies and pre-installed pip dependencies from the top
of v1-10-test branch.
.. code-block:: bash
docker build . \
--build-arg PYTHON_BASE_IMAGE="python:3.7-slim-buster" \
--build-arg PYTHON_MAJOR_MINOR_VERSION=3.7 \
--build-arg AIRFLOW_INSTALL_SOURCES="apache-airflow" \
--build-arg AIRFLOW_INSTALL_VERSION="==1.10.10" \
--build-arg AIRFLOW_BRANCH="v1-10-test" \
--build-arg CONSTRAINT_REQUIREMENTS="https://raw.githubusercontent.com/apache/airflow/1.10.10/requirements/requirements-python3.7.txt" \
--build-arg AIRFLOW_SOURCES_FROM="empty" \
--build-arg AIRFLOW_SOURCES_TO="/empty" \
--build-arg ADDITIONAL_AIRFLOW_EXTRAS="mssql,hdfs"
--build-arg ADDITIONAL_PYTHON_DEPS="sshtunnel oauth2client"
This builds the production image in version 3.7 with additional airflow extras from 1.10.10 Pypi package and
additional apt dev and runtime dependencies.
.. code-block::
docker build . \
--build-arg PYTHON_BASE_IMAGE="python:3.7-slim-buster" \
--build-arg PYTHON_MAJOR_MINOR_VERSION=3.7 \
--build-arg AIRFLOW_INSTALL_SOURCES="apache-airflow" \
--build-arg AIRFLOW_INSTALL_VERSION="==1.10.10" \
--build-arg CONSTRAINT_REQUIREMENTS="https://raw.githubusercontent.com/apache/airflow/1.10.10/requirements/requirements-python3.7.txt" \
--build-arg ENTRYPOINT_FILE="https://raw.githubusercontent.com/apache/airflow/1.10.10/entrypoint.sh" \
--build-arg AIRFLOW_SOURCES_FROM="entrypoint.sh" \
--build-arg AIRFLOW_SOURCES_TO="/entrypoint" \
--build-arg ADDITIONAL_AIRFLOW_EXTRAS="jdbc"
--build-arg ADDITIONAL_DEV_DEPS="gcc g++"
--build-arg ADDITIONAL_RUNTIME_DEPS="default-jre-headless"
Image manifests
---------------
Together with the main CI images we also build and push image manifests. Those manifests are very small images
that contain only results of the docker inspect for the image. This is in order to be able to
determine very quickly if the image in the docker registry has changed a lot since the last time.
Unfortunately docker registry (specifically DockerHub registry) has no anonymous way of querying image
details via API, you need to download the image to inspect it. We overcame it in the way that
always when we build the image we build a very small image manifest and push it to registry together
with the main CI image. The tag for the manifest image is the same as for the image it refers
to with added ``-manifest`` suffix. The manifest image for ``apache/airflow:master-python3.6-ci`` is named
``apache/airflow:master-python3.6-ci-manifest``.
Pulling the Latest Images
-------------------------
Sometimes the image needs to be rebuilt from scratch. This is required, for example,
when there is a security update of the Python version that all the images are based on and new version
of the image is pushed to the repository. In this case it is usually faster to pull the latest
images rather than rebuild them from scratch.
You can do it via the ``--force-pull-images`` flag to force pulling the latest images from the Docker Hub.
For production image:
.. code-block:: bash
./breeze build-image --force-pull-images --production-image
For CI image Breeze automatically uses force pulling in case it determines that your image is very outdated,
however uou can also force it with the same flag.
.. code-block:: bash
./breeze build-image --force-pull-images
Embedded image scripts
======================
Both images have a set of scripts that can be used in the image. Those are:
* /entrypoint - entrypoint script used when entering the image
* /clean-logs - script for periodic log cleaning
Running the CI image
====================
The entrypoint in the CI image contains all the initialisation needed for tests to be immediately executed.
It is copied from ``scripts/ci/in_container/entrypoint_ci.sh``.
The default behaviour is that you are dropped into bash shell. However if RUN_TESTS variable is
set to "true", then tests passed as arguments are executed
The entrypoint performs those operations:
* checks if the environment is ready to test (including database and all integrations). It waits
until all the components are ready to work
* installs older version of Airflow (if older version of Airflow is requested to be installed
via ``INSTALL_AIRFLOW_VERSION`` variable.
* Sets up Kerberos if Kerberos integration is enabled (generates and configures Kerberos token)
* Sets up ssh keys for ssh tests and restarts teh SSH server
* Sets all variables and configurations needed for unit tests to run
* Reads additional variables set in ``files/airflow-breeze-config/variables.env`` by sourcing that file
* In case of CI run sets parallelism to 2 to avoid excessive number of processes to run
* In case of CI run sets default parameters for pytest
* In case of running integration/long_running/quarantined tests - it sets the right pytest flags
* Sets default "tests" target in case the target is not explicitly set as additional argument
* Runs system tests if RUN_SYSTEM_TESTS flag is specified, otherwise runs regular unit and integration tests
Using the PROD image
====================
The PROD image entrypoint works as follows:
* In case the user is not "airflow" (with undefined user id) and the group id of the user is set to 0 (root),
then the user is dynamically added to /etc/passwd at entry using USER_NAME variable to define the user name.
This is in order to accommodate the
`OpenShift Guidelines<https://docs.openshift.com/enterprise/3.0/creating_images/guidelines.html>`_
* If ``AIRFLOW__CORE__SQL_ALCHEMY_CONN`` variable is passed to the container and it is either mysql or postgres
SQL alchemy connection, then the connection is checked and the script waits until the database is reachable.
* If no ``AIRFLOW__CORE__SQL_ALCHEMY_CONN`` variable is set or if it is set to sqlite SQL alchemy connection
then db reset is executed.
* If ``AIRFLOW__CELERY__BROKER_URL`` variable is passed and scheduler, worker of flower command is used then
the connection is checked and the script waits until the Celery broker database is reachable.
* If first argument equals to "bash" - it dropped in bash shell or executes bash command if you specify
extra arguments. For example:
.. code-block:: bash
docker run -it apache/airflow:master-python3.6 bash -c "ls -la"
total 16
drwxr-xr-x 4 airflow root 4096 Jun 5 18:12 .
drwxr-xr-x 1 root root 4096 Jun 5 18:12 ..
drwxr-xr-x 2 airflow root 4096 Jun 5 18:12 dags
drwxr-xr-x 2 airflow root 4096 Jun 5 18:12 logs
* If first argument is equal to "python" - you are dropped in python shell or python commands are executed if
you pass extra parameters. For example:
.. code-block:: bash
> docker run -it apache/airflow:master-python3.6 python -c "print('test')"
test
* If there are any other arguments - they are passed to "airflow" command
.. code-block:: bash
> docker run -it apache/airflow:master-python3.6 --help
usage: airflow [-h]
{celery,config,connections,dags,db,info,kerberos,plugins,pools,roles,rotate_fernet_key,scheduler,sync_perm,tasks,users,variables,version,webserver}
...
positional arguments:
Groups:
celery Start celery components
connections List/Add/Delete connections
dags List and manage DAGs
db Database operations
pools CRUD operations on pools
roles Create/List roles
tasks List and manage tasks
users CRUD operations on users
variables CRUD operations on variables
Commands:
config Show current application configuration
info Show information about current Airflow and environment
kerberos Start a kerberos ticket renewer
plugins Dump information about loaded plugins
rotate_fernet_key Rotate encrypted connection credentials and variables
scheduler Start a scheduler instance
sync_perm Update permissions for existing roles and DAGs
version Show the version
webserver Start a Airflow webserver instance
optional arguments:
-h, --help show this help message and exit
Alpha versions of 1.10.10 production-ready images
=================================================
The production images have been released for the first time in 1.10.10 release of Airflow as "Alpha" quality
ones. Between 1.10.10 the images are being improved and the 1.10.10 images should be patched and
published several times separately in order to test them with the upcoming Helm Chart.
Those images are for development and testing only and should not be used outside of the
development community.
The images were pushed with tags following the pattern: ``apache/airflow:1.10.10.1-alphaN-pythonX.Y``.
Patch level is an increasing number (starting from 1).
Those are alpha-quality releases however they contain the officially released Airflow ``1.10.10`` code.
The main changes in the images are scripts embedded in the images.
The following versions were pushed:
+-------+--------------------------------+----------------------------------------------------------+
| Patch | Tag pattern | Description |
+=======+================================+==========================================================+
| 1 | ``1.10.10.1-alpha1-pythonX.Y`` | Support for parameters added to bash and python commands |
+-------+--------------------------------+----------------------------------------------------------+
| 2 | ``1.10.10-1-alpha2-pythonX.Y`` | Added "/clean-logs" script |
+-------+--------------------------------+----------------------------------------------------------+
The commits used to generate those images are tagged with ``prod-image-1.10.10.1-alphaN`` tags.
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