70 lines
3.9 KiB
Markdown
70 lines
3.9 KiB
Markdown
---
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layout: default
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title: Managing ML models in OpenSearch Dashboards
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nav_order: 120
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redirect_from:
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- /ml-commons-plugin/ml-dashbaord/
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---
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The ML dashboard was taken out of experimental status and released as Generally Available in OpenSearch 2.9.
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{: .note}
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Administrators of machine learning (ML) clusters can use OpenSearch Dashboards to manage and check the status of ML models running inside a cluster. This can help ML developers provision nodes to ensure their models run efficiently.
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As of OpenSearch 2.6, you can only upload models using the API. For more information about how to upload a model to your cluster, see [Upload model to OpenSearch]({{site.url}}{{site.baseurl}}/ml-commons-plugin/model-serving-framework#upload-model-to-opensearch).
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## Enabling ML in Dashboards
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In OpenSearch 2.6, ML functionality is disabled by default. To enable it, you need to edit the configuration in `opensearch_dashboards.yml` and then restart your cluster.
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To enable the feature:
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1. In your OpenSearch cluster, navigate to your Dashboards home directory; for example, in Docker, `/usr/share/opensearch-dashboards`.
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2. Open your local copy of the Dashboards configuration file `opensearch_dashboards.yml`. If you don't have a copy, get one from GitHub: [`opensearch_dashboards.yml`](https://github.com/opensearch-project/OpenSearch-Dashboards/blob/main/config/opensearch_dashboards.yml).
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3. Add the setting `ml_commons_dashboards.enabled:` to `opensearch_dashboards.yml`. Then, set it to `ml_commons_dashboards.enabled: true` and save the configuration file.
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4. Restart the Dashboards container.
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5. Verify that the feature configuration settings were created and configured properly by launching OpenSearch Dashboards. The Machine Learning section should appear under **OpenSearch plugins**.
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## Accessing ML functionality in Dashboards
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To access ML functionality in OpenSearch Dashboards,select **OpenSearch plugins** > **Machine Learning**.
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<img src="{{site.url}}{{site.baseurl}}/images/ml/ml-dashboard/ml-dashboard.png" alt="Machine Learning section in OpenSearch dashboards">
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In the Machine Learning section, you now have access to the **Deployed models** dashboard.
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## Deployed models dashboard
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The deployed models dashboard gives admins the ability to check the status of any models stored inside your OpenSearch cluster.
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<img src="{{site.url}}{{site.baseurl}}/images/ml/ml-dashboard/deployed-models.png" alt="The deployed models view.">
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The dashboard includes the following information about the model:
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- **Name**: The name of the model given upon upload.
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- **Status**: The number of nodes for which the model responds.
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- When all nodes are responsive, the status is **Green**.
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- When some nodes are responsive,the status is **Yellow**.
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- When all nodes are unresponsive,the status is **Red**.
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- **Model ID**: The model ID.
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- **Action**: What actions you can take with the model.
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As of OpenSearch 2.6, the only action available is **View Status Details**, shown in the following image.
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<img src="{{site.url}}{{site.baseurl}}/images/ml/ml-dashboard/view-status-details.png" alt="You can view status details under actions.">
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When selected, the Status Details panel appears.
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The panel provides the following details inside the panel:
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- **Model ID**
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- **Model status by node**: The number of nodes for which the model is responsive.
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A list of nodes gives you a view of each node the model is running on, including each node’s **Node ID** and status, as shown in the following image. This is useful if you want to use the node's **Node ID** to determine why a node is unresponsive.
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<img src="{{site.url}}{{site.baseurl}}/images/ml/ml-dashboard/model-node-details.png" alt="The status of each node running the model.">
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## Next steps
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For more information about how to manage ML models in OpenSearch, see [Using custom models within OpenSearch]({{site.url}}{{site.baseurl}}/ml-commons-plugin/model-serving-framework/).
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