---
layout: default
navsection: userguide
title: Federated Multi-Cluster Workflows
...
{% comment %}
Copyright (C) The Arvados Authors. All rights reserved.

SPDX-License-Identifier: CC-BY-SA-3.0
{% endcomment %}

To support running analysis on geographically dispersed data (avoiding expensive data transfers by sending the computation to the data), and "hybrid cloud" configurations where an on-premise cluster can expand its capabilities by delegating work to a cloud-hosted cluster, Arvados supports federated workflows.  In a federated workflow, different steps of a workflow may execute on different clusters.  Arvados manages data transfer and delegation of credentials, so that all that is required is adding "arv:ClusterTarget":cwl-extensions.html#clustertarget hints to your existing workflow.

!(full-width)federated-workflow.svg!

For more information, visit the "architecture":{{site.baseurl}}/architecture/federation.html and "admin":{{site.baseurl}}/admin/federation.html sections about Arvados federation.

h2. Get the example files

The tutorial files are located in the "documentation section of the Arvados source repository:":https://github.com/curoverse/arvados/tree/master/doc/user/cwl/federated

<notextile>
<pre><code>~$ <span class="userinput">git clone https://github.com/curoverse/arvados</span>
~$ <span class="userinput">cd arvados/doc/user/cwl/federated</span>
</code></pre>
</notextile>

h2. Federated scatter/gather example

In this following example, an analysis task is executed on three different clusters with different data, then the results are combined to produce the final output.

{% codeblock as yaml %}
{% include 'federated_cwl' %}
{% endcodeblock %}

Example input document:

{% codeblock as yaml %}
{% include 'shards_yml' %}
{% endcodeblock %}