## The Elyra JupyterLab interface The Elyra extensions add multiple interfaces to the [JupyterLab GUI](https://jupyterlab.readthedocs.io/en/stable/user/interface.html). These interfaces are used to create and manage [pipelines](pipelines.md) and to create and manage metadata. Many of these tasks can also be accomplished using the [Elyra command line interface](command-line-interface.md). ### Launcher Elyra adds a new category to the JupyterLab launcher, providing access to the [Visual Pipeline Editor](#visual-pipeline-editor), the [Python editor](enhanced-script-support.html#python-script-execution-support), the [R editor](enhanced-script-support.html#r-script-execution-support), and the [Elyra documentation](https://elyra.readthedocs.io/en/latest/). ![Elyra category in JupyterLab launcher](../images/user_guide/jupyterlab-interface/launcher.png) Note that the number of tiles in the Elyra category depends on how you [installed Elyra](../getting_started/installation.md). ### Visual Pipeline Editor The Visual Pipeline Editor is used to work with [generic pipelines](../user_guide/pipelines.html#generic-pipelines) and [runtime-specific pipelines](../user_guide/pipelines.html#runtime-specific-pipelines). The editor includes the component palette, the canvas with a tool bar on top, and a properties panel, shown on the left, in the center, and the right, respectively. ![An empty pipeline in the Visual Pipeline Editor](../images/user_guide/jupyterlab-interface/visual-pipeline-editor.png) The palette provides access to components that you use to assemble pipelines. Components are managed using the [component catalogs sidebar](#manage-component-catalogs). The canvas is the main work area, where you [assemble the pipeline by adding nodes, connecting and configuring them](pipelines.html#creating-pipelines-using-the-visual-pipeline-editor) . The properties panel is used to configure pipeline properties and node properties. Refer to the [_Configuring the pipeline editor_ topic](pipeline-editor-configuration.md) to learn about customizing the editor. ### Metadata management sidebars Elyra adds multiple tabs to [JupyterLab's left sidebar](https://jupyterlab.readthedocs.io/en/stable/user/interface.html#left-and-right-sidebar). These tabs provide access to Elyra metadata, which is primarily used when you work with pipelines. ![JupyterLab sidebar tabs](../images/user_guide/jupyterlab-interface/jupyterlab-sidebars.png) #### Manage code snippets [Code snippets](code-snippets.md) allow for re-use of code in editors. To manage code snippets, open the `Code Snippets` tab. ![Code snippets tab](../images/user_guide/jupyterlab-interface/code-snippets-sidebar.png) #### Manage runtime configurations [Runtime configurations](runtime-conf.md) manage access to supported runtime environments that you use to run pipelines. To manage runtime configurations, open the `Runtimes` tab. ![Runtime configurations tab](../images/user_guide/jupyterlab-interface/runtime-configurations-sidebar.png) #### Manage runtime image configurations [Runtime image configurations](runtime-image-conf.md) identify container images that Elyra can utilize to run pipeline nodes on container-based platforms, such as Kubeflow Pipelines or Apache Airflow. To manage runtime image configurations, open the `Runtime Images` tab. ![Runtime images tab](../images/user_guide/jupyterlab-interface/runtime-images-sidebar.png) #### Manage component catalogs [Component catalogs](pipeline-components.md) provide access to components that you use to assemble pipelines. To manage component catalogs, open the `Component Catalogs` tab. ![Component catalogs tab](../images/user_guide/jupyterlab-interface/component-catalogs-sidebar.png)