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<blockquote>
<div></div></blockquote>
<div class="section" id="production-deployment">
<h1>Production Deployment<a class="headerlink" href="#production-deployment" title="Permalink to this headline"></a></h1>
<p>It is time to deploy your DAG in production. To do this, first, you need to make sure that the Airflow is itself production-ready.
Let's see what precautions you need to take.</p>
<div class="section" id="database-backend">
<h2>Database backend<a class="headerlink" href="#database-backend" title="Permalink to this headline"></a></h2>
<p>Airflow comes with an <code class="docutils literal notranslate"><span class="pre">SQLite</span></code> backend by default. This allows the user to run Airflow without any external database.
However, such a setup is meant to be used for testing purposes only; running the default setup in production can lead to data loss in multiple scenarios.
If you want to run production-grade Airflow, make sure you <a class="reference internal" href="howto/initialize-database.html"><span class="doc">configure the backend</span></a> to be an external database such as PostgreSQL or MySQL.</p>
<p>You can change the backend using the following config</p>
<div class="highlight-ini notranslate"><div class="highlight"><pre><span></span><span class="k">[core]</span>
<span class="na">sql_alchemy_conn</span> <span class="o">=</span> <span class="s">my_conn_string</span>
</pre></div>
</div>
<p>Once you have changed the backend, airflow needs to create all the tables required for operation.
Create an empty DB and give airflow's user the permission to <code class="docutils literal notranslate"><span class="pre">CREATE/ALTER</span></code> it.
Once that is done, you can run -</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>airflow db upgrade
</pre></div>
</div>
<p><code class="docutils literal notranslate"><span class="pre">upgrade</span></code> keeps track of migrations already applied, so it's safe to run as often as you need.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Do not use <code class="docutils literal notranslate"><span class="pre">airflow</span> <span class="pre">db</span> <span class="pre">init</span></code> as it can create a lot of default connections, charts, etc. which are not required in production DB.</p>
</div>
</div>
<div class="section" id="multi-node-cluster">
<h2>Multi-Node Cluster<a class="headerlink" href="#multi-node-cluster" title="Permalink to this headline"></a></h2>
<p>Airflow uses <a class="reference internal" href="_api/airflow/executors/sequential_executor/index.html#airflow.executors.sequential_executor.SequentialExecutor" title="airflow.executors.sequential_executor.SequentialExecutor"><code class="xref py py-class docutils literal notranslate"><span class="pre">airflow.executors.sequential_executor.SequentialExecutor</span></code></a> by default. However, by its nature, the user is limited to executing at most
one task at a time. <code class="docutils literal notranslate"><span class="pre">Sequential</span> <span class="pre">Executor</span></code> also pauses the scheduler when it runs a task, hence not recommended in a production setup.
You should use the <a class="reference internal" href="_api/airflow/executors/local_executor/index.html#airflow.executors.local_executor.LocalExecutor" title="airflow.executors.local_executor.LocalExecutor"><code class="xref py py-class docutils literal notranslate"><span class="pre">Local</span> <span class="pre">executor</span></code></a> for a single machine.
For a multi-node setup, you should use the <a class="reference internal" href="executor/kubernetes.html"><span class="doc">Kubernetes executor</span></a> or the <a class="reference internal" href="executor/celery.html"><span class="doc">Celery executor</span></a>.</p>
<p>Once you have configured the executor, it is necessary to make sure that every node in the cluster contains the same configuration and dags.
Airflow sends simple instructions such as &quot;execute task X of dag Y&quot;, but does not send any dag files or configuration. You can use a simple cronjob or
any other mechanism to sync DAGs and configs across your nodes, e.g., checkout DAGs from git repo every 5 minutes on all nodes.</p>
</div>
<div class="section" id="logging">
<h2>Logging<a class="headerlink" href="#logging" title="Permalink to this headline"></a></h2>
<p>If you are using disposable nodes in your cluster, configure the log storage to be a distributed file system (DFS) such as <code class="docutils literal notranslate"><span class="pre">S3</span></code> and <code class="docutils literal notranslate"><span class="pre">GCS</span></code>, or external services such as
Stackdriver Logging, Elasticsearch or Amazon CloudWatch.
This way, the logs are available even after the node goes down or gets replaced. See <a class="reference internal" href="logging-monitoring/logging-tasks.html"><span class="doc">Logging for Tasks</span></a> for configurations.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>The logs only appear in your DFS after the task has finished. You can view the logs while the task is running in UI itself.</p>
</div>
</div>
<div class="section" id="configuration">
<h2>Configuration<a class="headerlink" href="#configuration" title="Permalink to this headline"></a></h2>
<p>Airflow comes bundled with a default <code class="docutils literal notranslate"><span class="pre">airflow.cfg</span></code> configuration file.
You should use environment variables for configurations that change across deployments
e.g. metadata DB, password, etc. You can accomplish this using the format <span class="target" id="index-0"></span><a class="reference internal" href="cli-and-env-variables-ref.html#envvar-AIRFLOW__-SECTION-__-KEY"><code class="xref std std-envvar docutils literal notranslate"><span class="pre">AIRFLOW__{SECTION}__{KEY}</span></code></a></p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span><span class="nv">AIRFLOW__CORE__SQL_ALCHEMY_CONN</span><span class="o">=</span>my_conn_id
<span class="nv">AIRFLOW__WEBSERVER__BASE_URL</span><span class="o">=</span>http://host:port
</pre></div>
</div>
<p>Some configurations such as the Airflow Backend connection URI can be derived from bash commands as well:</p>
<div class="highlight-ini notranslate"><div class="highlight"><pre><span></span><span class="na">sql_alchemy_conn_cmd</span> <span class="o">=</span> <span class="s">bash_command_to_run</span>
</pre></div>
</div>
</div>
<div class="section" id="scheduler-uptime">
<h2>Scheduler Uptime<a class="headerlink" href="#scheduler-uptime" title="Permalink to this headline"></a></h2>
<p>Airflow users have for a long time been affected by a
<a class="reference external" href="https://issues.apache.org/jira/browse/AIRFLOW-401">core Airflow bug</a>
that causes the scheduler to hang without a trace.</p>
<p>Until fully resolved, you can mitigate this issue via a few short-term workarounds:</p>
<ul class="simple">
<li><p>Set a reasonable run_duration setting in your <code class="docutils literal notranslate"><span class="pre">airflow.cfg</span></code>. <a class="reference external" href="https://github.com/astronomer/airflow-chart/blob/63bc503c67e2cd599df0b6f831d470d09bad7ee7/templates/configmap.yaml#L44">Example config</a>.</p></li>
<li><p>Add an <code class="docutils literal notranslate"><span class="pre">exec</span></code> style health check to your helm charts on the scheduler deployment to fail if the scheduler has not heartbeat in a while. <a class="reference external" href="https://github.com/astronomer/helm.astronomer.io/pull/200/files">Example health check definition</a>.</p></li>
</ul>
</div>
<div class="section" id="production-container-images">
<h2>Production Container Images<a class="headerlink" href="#production-container-images" title="Permalink to this headline"></a></h2>
<div class="section" id="customizing-or-extending-the-production-image">
<h3>Customizing or extending the Production Image<a class="headerlink" href="#customizing-or-extending-the-production-image" title="Permalink to this headline"></a></h3>
<p>Before you dive-deeply in the way how the Airflow Image is build, named and why we are doing it the
way we do, you might want to know very quickly how you can extend or customize the existing image
for Apache Airflow. This chapter gives you a short answer to those questions.</p>
<p>The docker image provided (as convenience binary package) in the
<a class="reference external" href="https://hub.docker.com/repository/docker/apache/airflow">Apache Airflow DockerHub</a> is a bare image
that has not many external dependencies and extras installed. Apache Airflow has many extras
that can be installed alongside the &quot;core&quot; airflow image and they often require some additional
dependencies. The Apache Airflow image provided as convenience package is optimized for size, so
it provides just a bare minimal set of the extras and dependencies installed and in most cases
you want to either extend or customize the image.</p>
<p>Airflow Summit 2020's <a class="reference external" href="https://youtu.be/wDr3Y7q2XoI">Production Docker Image</a> talk provides more
details about the context, architecture and customization/extension methods for the Production Image.</p>
<div class="section" id="extending-the-image">
<h4>Extending the image<a class="headerlink" href="#extending-the-image" title="Permalink to this headline"></a></h4>
<p>Extending the image is easiest if you just need to add some dependencies that do not require
compiling. The compilation framework of Linux (so called <code class="docutils literal notranslate"><span class="pre">build-essential</span></code>) is pretty big, and
for the production images, size is really important factor to optimize for, so our Production Image
does not contain <code class="docutils literal notranslate"><span class="pre">build-essential</span></code>. If you need compiler like gcc or g++ or make/cmake etc. - those
are not found in the image and it is recommended that you follow the &quot;customize&quot; route instead.</p>
<p>How to extend the image - it is something you are most likely familiar with - simply
build a new image using Dockerfile's <code class="docutils literal notranslate"><span class="pre">FROM</span></code> directive and add whatever you need. Then you can add your
Debian dependencies with <code class="docutils literal notranslate"><span class="pre">apt</span></code> or PyPI dependencies with <code class="docutils literal notranslate"><span class="pre">pip</span> <span class="pre">install</span></code> or any other stuff you need.</p>
<p>You should be aware, about a few things:</p>
<ul class="simple">
<li><p>The production image of airflow uses &quot;airflow&quot; user, so if you want to add some of the tools
as <code class="docutils literal notranslate"><span class="pre">root</span></code> user, you need to switch to it with <code class="docutils literal notranslate"><span class="pre">USER</span></code> directive of the Dockerfile. Also you
should remember about following the
<a class="reference external" href="https://docs.docker.com/develop/develop-images/dockerfile_best-practices/">best practises of Dockerfiles</a>
to make sure your image is lean and small.</p></li>
</ul>
<div class="highlight-dockerfile notranslate"><div class="highlight"><pre><span></span><span class="k">FROM</span> <span class="s">apache/airflow:1.10.14</span>
<span class="k">USER</span><span class="s"> root</span>
<span class="k">RUN</span> apt-get update <span class="se">\</span>
<span class="o">&amp;&amp;</span> apt-get install -y --no-install-recommends <span class="se">\</span>
my-awesome-apt-dependency-to-add <span class="se">\</span>
<span class="o">&amp;&amp;</span> apt-get autoremove -yqq --purge <span class="se">\</span>
<span class="o">&amp;&amp;</span> apt-get clean <span class="se">\</span>
<span class="o">&amp;&amp;</span> rm -rf /var/lib/apt/lists/*
<span class="k">USER</span><span class="s"> airflow</span>
</pre></div>
</div>
<ul class="simple">
<li><p>PyPI dependencies in Apache Airflow are installed in the user library, of the &quot;airflow&quot; user, so
you need to install them with the <code class="docutils literal notranslate"><span class="pre">--user</span></code> flag and WITHOUT switching to airflow user. Note also
that using --no-cache-dir is a good idea that can help to make your image smaller.</p></li>
</ul>
<div class="highlight-dockerfile notranslate"><div class="highlight"><pre><span></span><span class="k">FROM</span> <span class="s">apache/airflow:1.10.14</span>
<span class="k">RUN</span> pip install --no-cache-dir --user my-awesome-pip-dependency-to-add
</pre></div>
</div>
<ul class="simple">
<li><p>If your apt, or PyPI dependencies require some of the build-essentials, then your best choice is
to follow the &quot;Customize the image&quot; route. However it requires to checkout sources of Apache Airflow,
so you might still want to choose to add build essentials to your image, even if your image will
be significantly bigger.</p></li>
</ul>
<div class="highlight-dockerfile notranslate"><div class="highlight"><pre><span></span><span class="k">FROM</span> <span class="s">apache/airflow:1.10.14</span>
<span class="k">USER</span><span class="s"> root</span>
<span class="k">RUN</span> apt-get update <span class="se">\</span>
<span class="o">&amp;&amp;</span> apt-get install -y --no-install-recommends <span class="se">\</span>
build-essential my-awesome-apt-dependency-to-add <span class="se">\</span>
<span class="o">&amp;&amp;</span> apt-get autoremove -yqq --purge <span class="se">\</span>
<span class="o">&amp;&amp;</span> apt-get clean <span class="se">\</span>
<span class="o">&amp;&amp;</span> rm -rf /var/lib/apt/lists/*
<span class="k">USER</span><span class="s"> airflow</span>
<span class="k">RUN</span> pip install --no-cache-dir --user my-awesome-pip-dependency-to-add
</pre></div>
</div>
<ul class="simple">
<li><p>You can also embed your dags in the image by simply adding them with COPY directive of Airflow.
The DAGs in production image are in /opt/airflow/dags folder.</p></li>
</ul>
</div>
<div class="section" id="customizing-the-image">
<h4>Customizing the image<a class="headerlink" href="#customizing-the-image" title="Permalink to this headline"></a></h4>
<p>Customizing the image is an alternative way of adding your own dependencies to the image - better
suited to prepare optimized production images.</p>
<p>The advantage of this method is that it produces optimized image even if you need some compile-time
dependencies that are not needed in the final image. You need to use Airflow Sources to build such images
from the <a class="reference external" href="https://downloads.apache.org/airflow/">official distribution folder of Apache Airflow</a> for the
released versions, or checked out from the GitHub project if you happen to do it from git sources.</p>
<p>The easiest way to build the image image is to use <code class="docutils literal notranslate"><span class="pre">breeze</span></code> script, but you can also build such customized
image by running appropriately crafted docker build in which you specify all the <code class="docutils literal notranslate"><span class="pre">build-args</span></code>
that you need to add to customize it. You can read about all the args and ways you can build the image
in the <a class="reference external" href="#production-image-build-arguments">#production-image-build-arguments</a> chapter below.</p>
<p>Here just a few examples are presented which should give you general understanding of what you can customize.</p>
<p>This builds the production image in version 3.7 with additional airflow extras from 1.10.14 PyPI package and
additional apt dev and runtime dependencies.</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>docker build . <span class="se">\</span>
--build-arg <span class="nv">PYTHON_BASE_IMAGE</span><span class="o">=</span><span class="s2">&quot;python:3.7-slim-buster&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">PYTHON_MAJOR_MINOR_VERSION</span><span class="o">=</span><span class="m">3</span>.7 <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_INSTALLATION_METHOD</span><span class="o">=</span><span class="s2">&quot;apache-airflow&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_VERSION</span><span class="o">=</span><span class="s2">&quot;1.10.14&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_INSTALL_VERSION</span><span class="o">=</span><span class="s2">&quot;==1.10.14&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_CONSTRAINTS_REFERENCE</span><span class="o">=</span><span class="s2">&quot;constraints-1-10&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_SOURCES_FROM</span><span class="o">=</span><span class="s2">&quot;empty&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_SOURCES_TO</span><span class="o">=</span><span class="s2">&quot;/empty&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">ADDITIONAL_AIRFLOW_EXTRAS</span><span class="o">=</span><span class="s2">&quot;jdbc&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">ADDITIONAL_PYTHON_DEPS</span><span class="o">=</span><span class="s2">&quot;pandas&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">ADDITIONAL_DEV_APT_DEPS</span><span class="o">=</span><span class="s2">&quot;gcc g++&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">ADDITIONAL_RUNTIME_APT_DEPS</span><span class="o">=</span><span class="s2">&quot;default-jre-headless&quot;</span> <span class="se">\</span>
--tag my-image
</pre></div>
</div>
<p>the same image can be built using <code class="docutils literal notranslate"><span class="pre">breeze</span></code> (it supports auto-completion of the options):</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>./breeze build-image <span class="se">\</span>
--production-image --python <span class="m">3</span>.7 --install-airflow-version<span class="o">=</span><span class="m">1</span>.10.14 <span class="se">\</span>
--additional-extras<span class="o">=</span>jdbc --additional-python-deps<span class="o">=</span><span class="s2">&quot;pandas&quot;</span> <span class="se">\</span>
--additional-dev-apt-deps<span class="o">=</span><span class="s2">&quot;gcc g++&quot;</span> --additional-runtime-apt-deps<span class="o">=</span><span class="s2">&quot;default-jre-headless&quot;</span>
</pre></div>
</div>
<p>You can customize more aspects of the image - such as additional commands executed before apt dependencies
are installed, or adding extra sources to install your dependencies from. You can see all the arguments
described below but here is an example of rather complex command to customize the image
based on example in <a class="reference external" href="https://github.com/apache/airflow/issues/8605#issuecomment-690065621">this comment</a>:</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>docker build . -f Dockerfile <span class="se">\</span>
--build-arg <span class="nv">PYTHON_BASE_IMAGE</span><span class="o">=</span><span class="s2">&quot;python:3.7-slim-buster&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">PYTHON_MAJOR_MINOR_VERSION</span><span class="o">=</span><span class="m">3</span>.7 <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_INSTALLATION_METHOD</span><span class="o">=</span><span class="s2">&quot;apache-airflow&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_VERSION</span><span class="o">=</span><span class="s2">&quot;1.10.14&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_INSTALL_VERSION</span><span class="o">=</span><span class="s2">&quot;==1.10.14&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_CONSTRAINTS_REFERENCE</span><span class="o">=</span><span class="s2">&quot;constraints-1-10&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_SOURCES_FROM</span><span class="o">=</span><span class="s2">&quot;empty&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_SOURCES_TO</span><span class="o">=</span><span class="s2">&quot;/empty&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">ADDITIONAL_AIRFLOW_EXTRAS</span><span class="o">=</span><span class="s2">&quot;slack&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">ADDITIONAL_PYTHON_DEPS</span><span class="o">=</span><span class="s2">&quot;apache-airflow-backport-providers-odbc \</span>
<span class="s2"> apache-airflow-backport-providers-odbc \</span>
<span class="s2"> azure-storage-blob \</span>
<span class="s2"> sshtunnel \</span>
<span class="s2"> google-api-python-client \</span>
<span class="s2"> oauth2client \</span>
<span class="s2"> beautifulsoup4 \</span>
<span class="s2"> dateparser \</span>
<span class="s2"> rocketchat_API \</span>
<span class="s2"> typeform&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">ADDITIONAL_DEV_APT_DEPS</span><span class="o">=</span><span class="s2">&quot;msodbcsql17 unixodbc-dev g++&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">ADDITIONAL_DEV_APT_COMMAND</span><span class="o">=</span><span class="s2">&quot;curl https://packages.microsoft.com/keys/microsoft.asc | apt-key add --no-tty - &amp;&amp; curl https://packages.microsoft.com/config/debian/10/prod.list &gt; /etc/apt/sources.list.d/mssql-release.list&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">ADDITIONAL_DEV_ENV_VARS</span><span class="o">=</span><span class="s2">&quot;ACCEPT_EULA=Y&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">ADDITIONAL_RUNTIME_APT_COMMAND</span><span class="o">=</span><span class="s2">&quot;curl https://packages.microsoft.com/keys/microsoft.asc | apt-key add --no-tty - &amp;&amp; curl https://packages.microsoft.com/config/debian/10/prod.list &gt; /etc/apt/sources.list.d/mssql-release.list&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">ADDITIONAL_RUNTIME_APT_DEPS</span><span class="o">=</span><span class="s2">&quot;msodbcsql17 unixodbc git procps vim&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">ADDITIONAL_RUNTIME_ENV_VARS</span><span class="o">=</span><span class="s2">&quot;ACCEPT_EULA=Y&quot;</span> <span class="se">\</span>
--tag my-image
</pre></div>
</div>
</div>
<div class="section" id="customizing-images-in-high-security-restricted-environments">
<h4>Customizing images in high security restricted environments<a class="headerlink" href="#customizing-images-in-high-security-restricted-environments" title="Permalink to this headline"></a></h4>
<p>You can also make sure your image is only build using local constraint file and locally downloaded
wheel files. This is often useful in Enterprise environments where the binary files are verified and
vetted by the security teams.</p>
<p>This builds below builds the production image in version 3.7 with packages and constraints used from the local
<code class="docutils literal notranslate"><span class="pre">docker-context-files</span></code> rather than installed from PyPI or GitHub. It also disables MySQL client
installation as it is using external installation method.</p>
<p>Note that as a prerequisite - you need to have downloaded wheel files. In the example below we
first download such constraint file locally and then use <code class="docutils literal notranslate"><span class="pre">pip</span> <span class="pre">download</span></code> to get the .whl files needed
but in most likely scenario, those wheel files should be copied from an internal repository of such .whl
files. Note that <code class="docutils literal notranslate"><span class="pre">AIRFLOW_INSTALL_VERSION</span></code> is only there for reference, the apache airflow .whl file
in the right version is part of the .whl files downloaded.</p>
<p>Note that 'pip download' will only works on Linux host as some of the packages need to be compiled from
sources and you cannot install them providing <code class="docutils literal notranslate"><span class="pre">--platform</span></code> switch. They also need to be downloaded using
the same python version as the target image.</p>
<p>The <code class="docutils literal notranslate"><span class="pre">pip</span> <span class="pre">download</span></code> might happen in a separate environment. The files can be committed to a separate
binary repository and vetted/verified by the security team and used subsequently to build images
of Airflow when needed on an air-gaped system.</p>
<p>Preparing the constraint files and wheel files:</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>rm docker-context-files/*.whl docker-context-files/*.txt
curl -Lo <span class="s2">&quot;docker-context-files/constraints-1-10.txt&quot;</span> <span class="se">\</span>
https://raw.githubusercontent.com/apache/airflow/constraints-1-10/constraints-3.7.txt
pip download --dest docker-context-files <span class="se">\</span>
--constraint docker-context-files/constraints-1-10.txt <span class="se">\</span>
apache-airflow<span class="o">[</span>async,aws,azure,celery,dask,elasticsearch,gcp,kubernetes,mysql,postgres,redis,slack,ssh,statsd,virtualenv<span class="o">]==</span><span class="m">1</span>.10.14
</pre></div>
</div>
<p>Building the image (after copying the files downloaded to the &quot;docker-context-files&quot; directory:</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>./breeze build-image <span class="se">\</span>
--production-image --python <span class="m">3</span>.7 --install-airflow-version<span class="o">=</span><span class="m">1</span>.10.14 <span class="se">\</span>
--disable-mysql-client-installation --disable-pip-cache --install-from-local-files-when-building <span class="se">\</span>
--constraints-location<span class="o">=</span><span class="s2">&quot;/docker-context-files/constraints-1-10.txt&quot;</span>
</pre></div>
</div>
<p>or</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>docker build . <span class="se">\</span>
--build-arg <span class="nv">PYTHON_BASE_IMAGE</span><span class="o">=</span><span class="s2">&quot;python:3.7-slim-buster&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">PYTHON_MAJOR_MINOR_VERSION</span><span class="o">=</span><span class="m">3</span>.7 <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_INSTALLATION_METHOD</span><span class="o">=</span><span class="s2">&quot;apache-airflow&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_VERSION</span><span class="o">=</span><span class="s2">&quot;1.10.14&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_INSTALL_VERSION</span><span class="o">=</span><span class="s2">&quot;==1.10.14&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_CONSTRAINTS_REFERENCE</span><span class="o">=</span><span class="s2">&quot;constraints-1-10&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_SOURCES_FROM</span><span class="o">=</span><span class="s2">&quot;empty&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_SOURCES_TO</span><span class="o">=</span><span class="s2">&quot;/empty&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">INSTALL_MYSQL_CLIENT</span><span class="o">=</span><span class="s2">&quot;false&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_PRE_CACHED_PIP_PACKAGES</span><span class="o">=</span><span class="s2">&quot;false&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">INSTALL_FROM_DOCKER_CONTEXT_FILES</span><span class="o">=</span><span class="s2">&quot;true&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_CONSTRAINTS_LOCATION</span><span class="o">=</span><span class="s2">&quot;/docker-context-files/constraints-1-10.txt&quot;</span>
</pre></div>
</div>
</div>
<div class="section" id="customizing-extending-the-image-together">
<h4>Customizing &amp; extending the image together<a class="headerlink" href="#customizing-extending-the-image-together" title="Permalink to this headline"></a></h4>
<p>You can combine both - customizing &amp; extending the image. You can build the image first using
<code class="docutils literal notranslate"><span class="pre">customize</span></code> method (either with docker command or with <code class="docutils literal notranslate"><span class="pre">breeze</span></code> and then you can <code class="docutils literal notranslate"><span class="pre">extend</span></code>
the resulting image using <code class="docutils literal notranslate"><span class="pre">FROM</span></code> any dependencies you want.</p>
</div>
<div class="section" id="customizing-pypi-installation">
<h4>Customizing PYPI installation<a class="headerlink" href="#customizing-pypi-installation" title="Permalink to this headline"></a></h4>
<p>You can customize PYPI sources used during image build by adding a docker-context-files/.pypirc file
This .pypirc will never be committed to the repository and will not be present in the final production image.
It is added and used only in the build segment of the image so it is never copied to the final image.</p>
</div>
</div>
<div class="section" id="external-sources-for-dependencies">
<h3>External sources for dependencies<a class="headerlink" href="#external-sources-for-dependencies" title="Permalink to this headline"></a></h3>
<p>In corporate environments, there is often the need to build your Container images using
other than default sources of dependencies. The docker file uses standard sources (such as
Debian apt repositories or PyPI repository. However, in corporate environments, the dependencies
are often only possible to be installed from internal, vetted repositories that are reviewed and
approved by the internal security teams. In those cases, you might need to use those different
sources.</p>
<p>This is rather easy if you extend the image - you simply write your extension commands
using the right sources - either by adding/replacing the sources in apt configuration or
specifying the source repository in pip install command.</p>
<p>It's a bit more involved in the case of customizing the image. We do not have yet (but we are working
on it) a capability of changing the sources via build args. However, since the builds use
Dockerfile that is a source file, you can rather easily simply modify the file manually and
specify different sources to be used by either of the commands.</p>
</div>
<div class="section" id="comparing-extending-and-customizing-the-image">
<h3>Comparing extending and customizing the image<a class="headerlink" href="#comparing-extending-and-customizing-the-image" title="Permalink to this headline"></a></h3>
<p>Here is the comparison of the two types of building images.</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 54%" />
<col style="width: 22%" />
<col style="width: 24%" />
</colgroup>
<thead>
<tr class="row-odd"><th class="head"></th>
<th class="head"><p>Extending the image</p></th>
<th class="head"><p>Customizing the image</p></th>
</tr>
</thead>
<tbody>
<tr class="row-even"><td><p>Produces optimized image</p></td>
<td><p>No</p></td>
<td><p>Yes</p></td>
</tr>
<tr class="row-odd"><td><p>Use Airflow Dockerfile sources to build the image</p></td>
<td><p>No</p></td>
<td><p>Yes</p></td>
</tr>
<tr class="row-even"><td><p>Requires Airflow sources</p></td>
<td><p>No</p></td>
<td><p>Yes</p></td>
</tr>
<tr class="row-odd"><td><p>You can build it with Breeze</p></td>
<td><p>No</p></td>
<td><p>Yes</p></td>
</tr>
<tr class="row-even"><td><p>Allows to use non-default sources for dependencies</p></td>
<td><p>Yes</p></td>
<td><p>No [1]</p></td>
</tr>
</tbody>
</table>
<dl class="simple">
<dt>[1] When you combine customizing and extending the image, you can use external sources</dt><dd><p>in the &quot;extend&quot; part. There are plans to add functionality to add external sources
option to image customization. You can also modify Dockerfile manually if you want to
use non-default sources for dependencies.</p>
</dd>
</dl>
</div>
<div class="section" id="using-the-production-image">
<h3>Using the production image<a class="headerlink" href="#using-the-production-image" title="Permalink to this headline"></a></h3>
<p>The PROD image entrypoint works as follows:</p>
<ul class="simple">
<li><p>In case the user is not &quot;airflow&quot; (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
<a class="reference external" href="https://docs.openshift.com/enterprise/3.0/creating_images/guidelines.html">OpenShift Guidelines</a></p></li>
<li><p>The <code class="docutils literal notranslate"><span class="pre">AIRFLOW_HOME</span></code> is set by default to <code class="docutils literal notranslate"><span class="pre">/opt/airflow/</span></code> - this means that DAGs
are in default in the <code class="docutils literal notranslate"><span class="pre">/opt/airflow/dags</span></code> folder and logs are in the <code class="docutils literal notranslate"><span class="pre">/opt/airflow/logs</span></code></p></li>
<li><p>The working directory is <code class="docutils literal notranslate"><span class="pre">/opt/airflow</span></code> by default.</p></li>
<li><p>If <code class="docutils literal notranslate"><span class="pre">AIRFLOW__CORE__SQL_ALCHEMY_CONN</span></code> 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 <code class="docutils literal notranslate"><span class="pre">AIRFLOW__CORE__SQL_ALCHEMY_CONN_CMD</span></code> variable is passed to the container, it is evaluated as a
command to execute and result of this evaluation is used as <code class="docutils literal notranslate"><span class="pre">AIRFLOW__CORE__SQL_ALCHEMY_CONN</span></code>. The
<code class="docutils literal notranslate"><span class="pre">_CMD</span></code> variable takes precedence over the <code class="docutils literal notranslate"><span class="pre">AIRFLOW__CORE__SQL_ALCHEMY_CONN</span></code> variable.</p></li>
<li><p>If no <code class="docutils literal notranslate"><span class="pre">AIRFLOW__CORE__SQL_ALCHEMY_CONN</span></code> variable is set then SQLite database is created in
${AIRFLOW_HOME}/airflow.db and db reset is executed.</p></li>
<li><p>If first argument equals to &quot;bash&quot; - you are dropped to a bash shell or you can executes bash command
if you specify extra arguments. For example:</p></li>
</ul>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>docker run -it apache/airflow:master-python3.6 bash -c <span class="s2">&quot;ls -la&quot;</span>
total <span class="m">16</span>
drwxr-xr-x <span class="m">4</span> airflow root <span class="m">4096</span> Jun <span class="m">5</span> <span class="m">18</span>:12 .
drwxr-xr-x <span class="m">1</span> root root <span class="m">4096</span> Jun <span class="m">5</span> <span class="m">18</span>:12 ..
drwxr-xr-x <span class="m">2</span> airflow root <span class="m">4096</span> Jun <span class="m">5</span> <span class="m">18</span>:12 dags
drwxr-xr-x <span class="m">2</span> airflow root <span class="m">4096</span> Jun <span class="m">5</span> <span class="m">18</span>:12 logs
</pre></div>
</div>
<ul class="simple">
<li><p>If first argument is equal to &quot;python&quot; - you are dropped in python shell or python commands are executed if
you pass extra parameters. For example:</p></li>
</ul>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>&gt; docker run -it apache/airflow:master-python3.6 python -c <span class="s2">&quot;print(&#39;test&#39;)&quot;</span>
<span class="nb">test</span>
</pre></div>
</div>
<ul class="simple">
<li><p>If first argument equals to &quot;airflow&quot; - the rest of the arguments is treated as an airflow command
to execute. Example:</p></li>
</ul>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>docker run -it apache/airflow:master-python3.6 airflow webserver
</pre></div>
</div>
<ul class="simple">
<li><p>If there are any other arguments - they are simply passed to the &quot;airflow&quot; command</p></li>
</ul>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>&gt; docker run -it apache/airflow:master-python3.6 version
<span class="m">2</span>.0.0.dev0
</pre></div>
</div>
<ul class="simple">
<li><p>If <code class="docutils literal notranslate"><span class="pre">AIRFLOW__CELERY__BROKER_URL</span></code> variable is passed and airflow command with
scheduler, worker of flower command is used, then the script checks the broker connection
and waits until the Celery broker database is reachable.
If <code class="docutils literal notranslate"><span class="pre">AIRFLOW__CELERY__BROKER_URL_CMD</span></code> variable is passed to the container, it is evaluated as a
command to execute and result of this evaluation is used as <code class="docutils literal notranslate"><span class="pre">AIRFLOW__CELERY__BROKER_URL</span></code>. The
<code class="docutils literal notranslate"><span class="pre">_CMD</span></code> variable takes precedence over the <code class="docutils literal notranslate"><span class="pre">AIRFLOW__CELERY__BROKER_URL</span></code> variable.</p></li>
</ul>
</div>
<div class="section" id="id1">
<h3>Production image build arguments<a class="headerlink" href="#id1" title="Permalink to this headline"></a></h3>
<p>The following build arguments (<code class="docutils literal notranslate"><span class="pre">--build-arg</span></code> in docker build command) can be used for production images:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 33%" />
<col style="width: 33%" />
<col style="width: 33%" />
</colgroup>
<thead>
<tr class="row-odd"><th class="head"><p>Build argument</p></th>
<th class="head"><p>Default value</p></th>
<th class="head"><p>Description</p></th>
</tr>
</thead>
<tbody>
<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">PYTHON_BASE_IMAGE</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">python:3.6-slim-buster</span></code></p></td>
<td><p>Base python image.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">PYTHON_MAJOR_MINOR_VERSION</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">3.6</span></code></p></td>
<td><p>major/minor version of Python (should
match base image).</p></td>
</tr>
<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">AIRFLOW_VERSION</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">2.0.0.dev0</span></code></p></td>
<td><p>version of Airflow.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">AIRFLOW_REPO</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">apache/airflow</span></code></p></td>
<td><p>the repository from which PIP
dependencies are pre-installed.</p></td>
</tr>
<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">AIRFLOW_BRANCH</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">master</span></code></p></td>
<td><p>the branch from which PIP dependencies
are pre-installed initially.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">AIRFLOW_CONSTRAINTS_LOCATION</span></code></p></td>
<td></td>
<td><p>If not empty, it will override the
source of the constraints with the
specified URL or file. Note that the
file has to be in docker context so
it's best to place such file in
one of the folders included in
.dockerignore.</p></td>
</tr>
<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">AIRFLOW_CONSTRAINTS_REFERENCE</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">constraints-master</span></code></p></td>
<td><p>Reference (branch or tag) from GitHub
where constraints file is taken from
It can be <code class="docutils literal notranslate"><span class="pre">constraints-master</span></code> but
also can be <code class="docutils literal notranslate"><span class="pre">constraints-1-10</span></code> for
1.10.* installation. In case of building
specific version you want to point it
to specific tag, for example
<code class="docutils literal notranslate"><span class="pre">constraints-1.10.14</span></code>.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">INSTALL_PROVIDERS_FROM_SOURCES</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">false</span></code></p></td>
<td><p>If set to <code class="docutils literal notranslate"><span class="pre">true</span></code> and image is built
from sources, all provider packages are
installed from sources rather than from
packages. It has no effect when
installing from PyPI or GitHub repo.</p></td>
</tr>
<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">AIRFLOW_EXTRAS</span></code></p></td>
<td><p>(see Dockerfile)</p></td>
<td><p>Default extras with which airflow is
installed.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">INSTALL_FROM_PYPI</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">true</span></code></p></td>
<td><p>If set to true, Airflow is installed
from PyPI. if you want to install
Airflow from self-build package
you can set it to false, put package in
<code class="docutils literal notranslate"><span class="pre">docker-context-files</span></code> and set
<code class="docutils literal notranslate"><span class="pre">INSTALL_FROM_DOCKER_CONTEXT_FILES</span></code> to
<code class="docutils literal notranslate"><span class="pre">true</span></code>. For this you have to also keep
<code class="docutils literal notranslate"><span class="pre">AIRFLOW_PRE_CACHED_PIP_PACKAGES</span></code> flag
set to <code class="docutils literal notranslate"><span class="pre">false</span></code>.</p></td>
</tr>
<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">AIRFLOW_PRE_CACHED_PIP_PACKAGES</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">false</span></code></p></td>
<td><p>Allows to pre-cache airflow PIP packages
from the GitHub of Apache Airflow
This allows to optimize iterations for
Image builds and speeds up CI builds.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">INSTALL_FROM_DOCKER_CONTEXT_FILES</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">false</span></code></p></td>
<td><p>If set to true, Airflow, providers and
all dependencies are installed from
from locally built/downloaded
.whl and .tar.gz files placed in the
<code class="docutils literal notranslate"><span class="pre">docker-context-files</span></code>. In certain
corporate environments, this is required
to install airflow from such pre-vetted
packages rather than from PyPI. For this
to work, also set <code class="docutils literal notranslate"><span class="pre">INSTALL_FROM_PYPI</span></code>
to false.</p></td>
</tr>
<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">ADDITIONAL_AIRFLOW_EXTRAS</span></code></p></td>
<td></td>
<td><p>Optional additional extras with which
airflow is installed.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">ADDITIONAL_PYTHON_DEPS</span></code></p></td>
<td></td>
<td><p>Optional python packages to extend
the image with some extra dependencies.</p></td>
</tr>
<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">DEV_APT_COMMAND</span></code></p></td>
<td><p>(see Dockerfile)</p></td>
<td><p>Dev apt command executed before dev deps
are installed in the Build image.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">ADDITIONAL_DEV_APT_COMMAND</span></code></p></td>
<td></td>
<td><p>Additional Dev apt command executed
before dev dep are installed
in the Build image. Should start with
<code class="docutils literal notranslate"><span class="pre">&amp;&amp;</span></code>.</p></td>
</tr>
<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">DEV_APT_DEPS</span></code></p></td>
<td><p>(see Dockerfile)</p></td>
<td><p>Dev APT dependencies installed
in the Build image.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">ADDITIONAL_DEV_APT_DEPS</span></code></p></td>
<td></td>
<td><p>Additional apt dev dependencies
installed in the Build image.</p></td>
</tr>
<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">ADDITIONAL_DEV_APT_ENV</span></code></p></td>
<td></td>
<td><p>Additional env variables defined
when installing dev deps.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">RUNTIME_APT_COMMAND</span></code></p></td>
<td><p>(see Dockerfile)</p></td>
<td><p>Runtime apt command executed before deps
are installed in the Main image.</p></td>
</tr>
<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">ADDITIONAL_RUNTIME_APT_COMMAND</span></code></p></td>
<td></td>
<td><p>Additional Runtime apt command executed
before runtime dep are installed
in the Main image. Should start with
<code class="docutils literal notranslate"><span class="pre">&amp;&amp;</span></code>.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">RUNTIME_APT_DEPS</span></code></p></td>
<td><p>(see Dockerfile)</p></td>
<td><p>Runtime APT dependencies installed
in the Main image.</p></td>
</tr>
<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">ADDITIONAL_RUNTIME_APT_DEPS</span></code></p></td>
<td></td>
<td><p>Additional apt runtime dependencies
installed in the Main image.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">ADDITIONAL_RUNTIME_APT_ENV</span></code></p></td>
<td></td>
<td><p>Additional env variables defined
when installing runtime deps.</p></td>
</tr>
<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">AIRFLOW_HOME</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">/opt/airflow</span></code></p></td>
<td><p>Airflow’s HOME (that’s where logs and
sqlite databases are stored).</p></td>
</tr>
<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">AIRFLOW_UID</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">50000</span></code></p></td>
<td><p>Airflow user UID.</p></td>
</tr>
<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">AIRFLOW_GID</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">50000</span></code></p></td>
<td><p>Airflow group GID. Note that most files
created on behalf of airflow user belong
to the <code class="docutils literal notranslate"><span class="pre">root</span></code> group (0) to keep
OpenShift Guidelines compatibility.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">AIRFLOW_USER_HOME_DIR</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">/home/airflow</span></code></p></td>
<td><p>Home directory of the Airflow user.</p></td>
</tr>
<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">CASS_DRIVER_BUILD_CONCURRENCY</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">8</span></code></p></td>
<td><p>Number of processors to use for
cassandra PIP install (speeds up
installing in case cassandra extra is
used).</p></td>
</tr>
<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">INSTALL_MYSQL_CLIENT</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">true</span></code></p></td>
<td><p>Whether MySQL client should be installed
The mysql extra is removed from extras
if the client is not installed.</p></td>
</tr>
</tbody>
</table>
<p>There are build arguments that determine the installation mechanism of Apache Airflow for the
production image. There are three types of build:</p>
<ul class="simple">
<li><p>From local sources (by default for example when you use <code class="docutils literal notranslate"><span class="pre">docker</span> <span class="pre">build</span> <span class="pre">.</span></code>)</p></li>
<li><p>You can build the image from released PyPi airflow package (used to build the official Docker image)</p></li>
<li><p>You can build the image from any version in GitHub repository(this is used mostly for system testing).</p></li>
</ul>
<table class="docutils align-default">
<colgroup>
<col style="width: 25%" />
<col style="width: 17%" />
<col style="width: 58%" />
</colgroup>
<thead>
<tr class="row-odd"><th class="head"><p>Build argument</p></th>
<th class="head"><p>Default</p></th>
<th class="head"><p>What to specify</p></th>
</tr>
</thead>
<tbody>
<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">AIRFLOW_INSTALLATION_METHOD</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">apache-airflow</span></code></p></td>
<td><p>Should point to the installation method of Apache Airflow. It can be
<code class="docutils literal notranslate"><span class="pre">apache-airflow</span></code> for installation from packages and URL to installation from
GitHub repository tag or branch or &quot;.&quot; to install from sources.
Note that installing from local sources requires appropriate values of the
<code class="docutils literal notranslate"><span class="pre">AIRFLOW_SOURCES_FROM</span></code> and <code class="docutils literal notranslate"><span class="pre">AIRFLOW_SOURCES_TO</span></code> variables as described below.
Only used when <code class="docutils literal notranslate"><span class="pre">INSTALL_FROM_PYPI</span></code> is set to <code class="docutils literal notranslate"><span class="pre">true</span></code>.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">AIRFLOW_INSTALL_VERSION</span></code></p></td>
<td></td>
<td><p>Optional - might be used for package installation of different Airflow version
for example&quot;==1.10.14&quot;. For consistency, you should also set``AIRFLOW_VERSION``
to the same value AIRFLOW_VERSION is embedded as label in the image created.</p></td>
</tr>
<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">AIRFLOW_CONSTRAINTS_REFERENCE</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">constraints-master</span></code></p></td>
<td><p>Reference (branch or tag) from GitHub where constraints file is taken from.
It can be <code class="docutils literal notranslate"><span class="pre">constraints-master</span></code> but also can be``constraints-1-10`` for
1.10.* installations. In case of building specific version
you want to point it to specific tag, for example <code class="docutils literal notranslate"><span class="pre">constraints-1.10.14</span></code></p></td>
</tr>
<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">AIRFLOW_WWW</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">www</span></code></p></td>
<td><p>In case of Airflow 2.0 it should be &quot;www&quot;, in case of Airflow 1.10
series it should be &quot;www_rbac&quot;.</p></td>
</tr>
<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">AIRFLOW_SOURCES_FROM</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">empty</span></code></p></td>
<td><p>Sources of Airflow. Set it to &quot;.&quot; when you install airflow from
local sources.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">AIRFLOW_SOURCES_TO</span></code></p></td>
<td><p><code class="docutils literal notranslate"><span class="pre">/empty</span></code></p></td>
<td><p>Target for Airflow sources. Set to &quot;/opt/airflow&quot; when
you want to install airflow from local sources.</p></td>
</tr>
</tbody>
</table>
<p>This builds production image in version 3.6 with default extras from the local sources (master version
of 2.0 currently):</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>docker build .
</pre></div>
</div>
<p>This builds the production image in version 3.7 with default extras from 1.10.14 tag and
constraints taken from constraints-1-10-12 branch in GitHub.</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>docker build . <span class="se">\</span>
--build-arg <span class="nv">PYTHON_BASE_IMAGE</span><span class="o">=</span><span class="s2">&quot;python:3.7-slim-buster&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">PYTHON_MAJOR_MINOR_VERSION</span><span class="o">=</span><span class="m">3</span>.7 <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_INSTALLATION_METHOD</span><span class="o">=</span><span class="s2">&quot;https://github.com/apache/airflow/archive/1.10.14.tar.gz#egg=apache-airflow&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_CONSTRAINTS_REFERENCE</span><span class="o">=</span><span class="s2">&quot;constraints-1-10&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_BRANCH</span><span class="o">=</span><span class="s2">&quot;v1-10-test&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_SOURCES_FROM</span><span class="o">=</span><span class="s2">&quot;empty&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_SOURCES_TO</span><span class="o">=</span><span class="s2">&quot;/empty&quot;</span>
</pre></div>
</div>
<p>This builds the production image in version 3.7 with default extras from 1.10.14 PyPI package and
constraints taken from 1.10.14 tag in GitHub and pre-installed pip dependencies from the top
of v1-10-test branch.</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>docker build . <span class="se">\</span>
--build-arg <span class="nv">PYTHON_BASE_IMAGE</span><span class="o">=</span><span class="s2">&quot;python:3.7-slim-buster&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">PYTHON_MAJOR_MINOR_VERSION</span><span class="o">=</span><span class="m">3</span>.7 <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_INSTALLATION_METHOD</span><span class="o">=</span><span class="s2">&quot;apache-airflow&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_VERSION</span><span class="o">=</span><span class="s2">&quot;1.10.14&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_INSTALL_VERSION</span><span class="o">=</span><span class="s2">&quot;==1.10.14&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_BRANCH</span><span class="o">=</span><span class="s2">&quot;v1-10-test&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_CONSTRAINTS_REFERENCE</span><span class="o">=</span><span class="s2">&quot;constraints-1.10.14&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_SOURCES_FROM</span><span class="o">=</span><span class="s2">&quot;empty&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_SOURCES_TO</span><span class="o">=</span><span class="s2">&quot;/empty&quot;</span>
</pre></div>
</div>
<p>This builds the production image in version 3.7 with additional airflow extras from 1.10.14 PyPI package and
additional python dependencies and pre-installed pip dependencies from 1.10.14 tagged constraints.</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>docker build . <span class="se">\</span>
--build-arg <span class="nv">PYTHON_BASE_IMAGE</span><span class="o">=</span><span class="s2">&quot;python:3.7-slim-buster&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">PYTHON_MAJOR_MINOR_VERSION</span><span class="o">=</span><span class="m">3</span>.7 <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_INSTALLATION_METHOD</span><span class="o">=</span><span class="s2">&quot;apache-airflow&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_VERSION</span><span class="o">=</span><span class="s2">&quot;1.10.14&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_INSTALL_VERSION</span><span class="o">=</span><span class="s2">&quot;==1.10.14&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_BRANCH</span><span class="o">=</span><span class="s2">&quot;v1-10-test&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_CONSTRAINTS_REFERENCE</span><span class="o">=</span><span class="s2">&quot;constraints-1.10.14&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_SOURCES_FROM</span><span class="o">=</span><span class="s2">&quot;empty&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_SOURCES_TO</span><span class="o">=</span><span class="s2">&quot;/empty&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">ADDITIONAL_AIRFLOW_EXTRAS</span><span class="o">=</span><span class="s2">&quot;mssql,hdfs&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">ADDITIONAL_PYTHON_DEPS</span><span class="o">=</span><span class="s2">&quot;sshtunnel oauth2client&quot;</span>
</pre></div>
</div>
<p>This builds the production image in version 3.7 with additional airflow extras from 1.10.14 PyPI package and
additional apt dev and runtime dependencies.</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>docker build . <span class="se">\</span>
--build-arg <span class="nv">PYTHON_BASE_IMAGE</span><span class="o">=</span><span class="s2">&quot;python:3.7-slim-buster&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">PYTHON_MAJOR_MINOR_VERSION</span><span class="o">=</span><span class="m">3</span>.7 <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_INSTALLATION_METHOD</span><span class="o">=</span><span class="s2">&quot;apache-airflow&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_VERSION</span><span class="o">=</span><span class="s2">&quot;1.10.14&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_INSTALL_VERSION</span><span class="o">=</span><span class="s2">&quot;==1.10.14&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_CONSTRAINTS_REFERENCE</span><span class="o">=</span><span class="s2">&quot;constraints-1-10&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_SOURCES_FROM</span><span class="o">=</span><span class="s2">&quot;empty&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">AIRFLOW_SOURCES_TO</span><span class="o">=</span><span class="s2">&quot;/empty&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">ADDITIONAL_AIRFLOW_EXTRAS</span><span class="o">=</span><span class="s2">&quot;jdbc&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">ADDITIONAL_DEV_APT_DEPS</span><span class="o">=</span><span class="s2">&quot;gcc g++&quot;</span> <span class="se">\</span>
--build-arg <span class="nv">ADDITIONAL_RUNTIME_APT_DEPS</span><span class="o">=</span><span class="s2">&quot;default-jre-headless&quot;</span>
</pre></div>
</div>
</div>
<div class="section" id="more-details-about-the-images">
<h3>More details about the images<a class="headerlink" href="#more-details-about-the-images" title="Permalink to this headline"></a></h3>
<p>You can read more details about the images - the context, their parameters and internal structure in the
<a class="reference external" href="https://github.com/apache/airflow/blob/master/IMAGES.rst">IMAGES.rst</a> document.</p>
</div>
</div>
<div class="section" id="kerberos-authenticated-workers">
<span id="production-deployment-kerberos"></span><h2>Kerberos-authenticated workers<a class="headerlink" href="#kerberos-authenticated-workers" title="Permalink to this headline"></a></h2>
<p>Apache Airflow has a built-in mechanism for authenticating the operation with a KDC (Key Distribution Center).
Airflow has a separate command <code class="docutils literal notranslate"><span class="pre">airflow</span> <span class="pre">kerberos</span></code> that acts as token refresher. It uses the pre-configured
Kerberos Keytab to authenticate in the KDC to obtain a valid token, and then refreshing valid token
at regular intervals within the current token expiry window.</p>
<p>Each request for refresh uses a configured principal, and only keytab valid for the principal specified
is capable of retrieving the authentication token.</p>
<p>The best practice to implement proper security mechanism in this case is to make sure that worker
workloads have no access to the Keytab but only have access to the periodically refreshed, temporary
authentication tokens. This can be achieved in docker environment by running the <code class="docutils literal notranslate"><span class="pre">airflow</span> <span class="pre">kerberos</span></code>
command and the worker command in separate containers - where only the <code class="docutils literal notranslate"><span class="pre">airflow</span> <span class="pre">kerberos</span></code> token has
access to the Keytab file (preferably configured as secret resource). Those two containers should share
a volume where the temporary token should be written by the <code class="docutils literal notranslate"><span class="pre">airflow</span> <span class="pre">kerberos</span></code> and read by the workers.</p>
<p>In the Kubernetes environment, this can be realized by the concept of side-car, where both Kerberos
token refresher and worker are part of the same Pod. Only the Kerberos side-car has access to
Keytab secret and both containers in the same Pod share the volume, where temporary token is written by
the side-care container and read by the worker container.</p>
<p>This concept is implemented in the development version of the Helm Chart that is part of Airflow source code.</p>
</div>
<div class="section" id="secured-server-and-service-access-on-google-cloud">
<h2>Secured Server and Service Access on Google Cloud<a class="headerlink" href="#secured-server-and-service-access-on-google-cloud" title="Permalink to this headline"></a></h2>
<p>This section describes techniques and solutions for securely accessing servers and services when your Airflow environment is deployed on Google Cloud, or you connect to Google services, or you are connecting to the Google API.</p>
<div class="section" id="iam-and-service-accounts">
<h3>IAM and Service Accounts<a class="headerlink" href="#iam-and-service-accounts" title="Permalink to this headline"></a></h3>
<p>You should do not rely on internal network segmentation or firewalling as our primary security mechanisms. To protect your organization's data, every request you make should contain sender identity. In the case of Google Cloud, the identity is provided by <a class="reference external" href="https://cloud.google.com/iam/docs/service-accounts">the IAM and Service account</a>. Each Compute Engine instance has an associated service account identity. It provides cryptographic credentials that your workload can use to prove its identity when making calls to Google APIs or third-party services. Each instance has access only to short-lived credentials. If you use Google-managed service account keys, then the private key is always held in escrow and is never directly accessible.</p>
<p>If you are using Kubernetes Engine, you can use <a class="reference external" href="https://cloud.google.com/kubernetes-engine/docs/how-to/workload-identity">Workload Identity</a> to assign an identity to individual pods.</p>
<p>For more information about service accounts in the Airflow, see <a class="reference external" href="/docs/apache-airflow-providers-google/stable/connections/gcp.html#howto-connection-gcp" title="(in apache-airflow-providers-google vmaster)"><span>Google Cloud Connection</span></a></p>
</div>
<div class="section" id="impersonate-service-accounts">
<h3>Impersonate Service Accounts<a class="headerlink" href="#impersonate-service-accounts" title="Permalink to this headline"></a></h3>
<p>If you need access to other service accounts, you can <a class="reference external" href="/docs/apache-airflow-providers-google/stable/connections/gcp.html#howto-connection-gcp-impersonation" title="(in apache-airflow-providers-google vmaster)"><span class="xref std std-ref">impersonate other service accounts</span></a> to exchange the token with the default identity to another service account. Thus, the account keys are still managed by Google and cannot be read by your workload.</p>
<p>It is not recommended to generate service account keys and store them in the metadata database or the secrets backend. Even with the use of the backend secret, the service account key is available for your workload.</p>
</div>
<div class="section" id="access-to-compute-engine-instance">
<h3>Access to Compute Engine Instance<a class="headerlink" href="#access-to-compute-engine-instance" title="Permalink to this headline"></a></h3>
<p>If you want to establish an SSH connection to the Compute Engine instance, you must have the network address of this instance and credentials to access it. To simplify this task, you can use <a class="reference external" href="/docs/apache-airflow-providers-google/stable/_api/airflow/providers/google/cloud/hooks/compute/index.html#airflow.providers.google.cloud.hooks.compute.ComputeEngineHook" title="(in apache-airflow-providers-google vmaster)"><code class="xref py py-class docutils literal notranslate"><span class="pre">ComputeEngineHook</span></code></a> instead of <a class="reference external" href="/docs/apache-airflow-providers-ssh/stable/_api/airflow/providers/ssh/hooks/ssh/index.html#airflow.providers.ssh.hooks.ssh.SSHHook" title="(in apache-airflow-providers-ssh vmaster)"><code class="xref py py-class docutils literal notranslate"><span class="pre">SSHHook</span></code></a></p>
<p>The <a class="reference external" href="/docs/apache-airflow-providers-google/stable/_api/airflow/providers/google/cloud/hooks/compute/index.html#airflow.providers.google.cloud.hooks.compute.ComputeEngineHook" title="(in apache-airflow-providers-google vmaster)"><code class="xref py py-class docutils literal notranslate"><span class="pre">ComputeEngineHook</span></code></a> support authorization with Google OS Login service. It is an extremely robust way to manage Linux access properly as it stores short-lived ssh keys in the metadata service, offers PAM modules for access and sudo privilege checking and offers nsswitch user lookup into the metadata service as well.</p>
<p>It also solves the discovery problem that arises as your infrastructure grows. You can use the instance name instead of the network address.</p>
</div>
<div class="section" id="access-to-amazon-web-service">
<h3>Access to Amazon Web Service<a class="headerlink" href="#access-to-amazon-web-service" title="Permalink to this headline"></a></h3>
<p>Thanks to <a class="reference external" href="https://docs.aws.amazon.com/IAM/latest/UserGuide/id_roles_providers_oidc.html">Web Identity Federation</a>, you can exchange the Google Cloud Platform identity to the Amazon Web Service identity, which effectively means access to Amazon Web Service platform. For more information, see: <a class="reference external" href="/docs/apache-airflow-providers-amazon/stable/connections/aws.html#howto-connection-aws-gcp-federation" title="(in apache-airflow-providers-amazon vmaster)"><span>Google Cloud to AWS authentication using Web Identity Federation</span></a></p>
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<li><a class="reference internal" href="#impersonate-service-accounts">Impersonate Service Accounts</a></li>
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