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28 changes: 28 additions & 0 deletions fdl/index.html
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</span>
</a>

</li>

<li class="md-nav__item">
<a href="#mountsettings" class="md-nav__link">
<span class="md-ellipsis">
MountSettings
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</tr>
</tbody>
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<h2 id="mountsettings">MountSettings</h2>
<table>
<thead>
<tr>
<th>Field</th>
<th>Description</th>
</tr>
</thead>
<tbody>
<tr>
<td><code>storage_provider</code> </br> <em>string</em></td>
<td>Identifier of the storage provider. Optional.</td>
</tr>
<tr>
<td><code>path</code> </br> <em>string</em></td>
<td>Path to the folder that will be mounted. Optional.</td>
</tr>
</tbody>
</table>
<h2 id="replica">Replica</h2>
<table>
<thead>
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<h1 id="mounting-external-storage-on-service-volumes">Mounting external storage on service volumes</h1>
<p>This feature enables the mounting of a folder from a storage provider, such as MinIO or dCache, into the service container. As illustrated in the following diagram, the folder is placed inside the /mnt directory on the container volume, thereby making it accessible to the service. This functionality can be utilized with exposed services, such as those using a Jupyter Notebook, to make the content of the storage bucket accessible directly within the Notebook.</p>
<p>This feature enables the mounting of a folder from a storage provider, such as MinIO or dCache, into the service container. As illustrated in the following diagram, the folder is placed inside the /mnt directory on the container volume, thereby making it accessible to the service.</p>
<p><img alt="mount-diagram" src="../images/mount.png" /></p>
<p>This functionality can be useful with exposed services, such as those using a Jupyter Notebook, to make the content of the storage bucket accessible directly within the Notebook. For instance, if you have a MinIO bucket called <code>notebook</code> you want to access, you would need to add the following parameters to the service definition:</p>
<pre><code class="language-yaml">mount:
storage_provider: minio.default
path: /notebook
</code></pre>
<p>The complete definition of this use case that integrates the expose of a Jupyter Notebook with the access to a mounted bucket would look like the following:</p>
<pre><code class="language-yaml">functions:
oscar:
- oscar-cluster:
name: jupyter
memory: 2Gi
cpu: '1.0'
image: jupyter/base-notebook
script: jupyterscript2.sh
environment:
Variables:
JUPYTER_TOKEN: &quot;root&quot;
JHUB_BASE_URL: &quot;/system/services/jupyter/exposed&quot;
JUPYTER_DIRECTORY: &quot;/mnt&quot;
mount:
storage_provider: minio.default
path: /notebook
expose:
min_scale: 1
max_scale: 1
api_port: 8888
cpu_threshold: 90
rewrite_target: true
</code></pre>
<p><strong>Note</strong>: You can find the files of this example on <a href="https://github.com/grycap/oscar/tree/master/examples/expose_services/jupyter">OSCAR's repository examples</a></p>
<p>As OSCAR has the credentials of the default MinIO instance internally, if you want to use a different one or a different storage provider, you need to set these credentials on the service <a href="/fdl">FDL</a>. Currently, the storage providers supported on this functionality are:</p>
<ul>
<li><a href="/fdl/#minioprovider">MinIO provider</a></li>
<li><a href="/fdl/#webdavprovider">WebDav provider</a></li>
</ul>
<p>Let's explore these with an FDL example:</p>
<pre><code>mount:
storage_provider: minio.default
path: /body-pose-detection-async
</code></pre>
<p>The example above means that OSCAR mounts the <code>body-pose-detection-async</code> bucket of the default MinIO inside the OSCAR services. So, the content of the <code>body-pose-detection-async</code> bucket will be found in <code>/mnt/body-pose-detection-async</code> folder inside the execution of OSCAR services.</p>



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