--- id: module_deadline title: Deadline Administration sidebar_label: Deadline --- import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem'; ## Preparation For [AWS Thinkbox Deadline](https://www.awsthinkbox.com/deadline) support you need to set a few things up in both OpenPype and Deadline itself 1. Deploy OpenPype executable to all nodes of Deadline farm. See [Install & Run](admin_use.md) 2. Enable Deadline Module in the [OpenPype Admin Settings](admin_settings_system.md#deadline). 3. Set up *Deadline Web API service*. For more details on how to do it, see [here](https://docs.thinkboxsoftware.com/products/deadline/10.1/1_User%20Manual/manual/web-service.html). 4. Point OpenPype to your deadline webservice URL in the [OpenPype Admin Settings](admin_settings_system.md#deadline). 5. Install our custom plugin and scripts to your deadline repository. It should be as simple as copying content of `openpype/modules/deadline/repository/custom` to `path/to/your/deadline/repository/custom`. ## Configuration OpenPype integration for Deadline consists of two parts: - The `OpenPype` Deadline Plug-in - A `GlobalJobPreLoad` Deadline Script (this gets triggered for each deadline job) The `GlobalJobPreLoad` handles populating render and publish jobs with proper environment variables using settings from the `OpenPype` Deadline Plug-in. The `OpenPype` Deadline Plug-in must be configured to point to a valid OpenPype executable location. The executable need to be installed to destinations accessible by DL process. Check permissions (must be executable and accessible by Deadline process) - Enable `Tools > Super User Mode` in Deadline Monitor - Go to `Tools > Configure Plugins...`, find `OpenPype` in the list on the left side, find location of OpenPype executable. It is recommended to use the `openpype_console` executable as it provides a bit more logging. - In case of multi OS farms, provide multiple locations, each Deadline Worker goes through the list and tries to find the first accessible location for itself. ![Configure plugin](assets/deadline_configure_plugin.png) ## Troubleshooting #### Publishing jobs fail directly in DCCs - Double check that all previously described steps were finished - Check that `deadlinewebservice` is running on DL server - Check that user's machine has access to deadline server on configured port #### Jobs are failing on DL side Each publishing from OpenPype consists of 2 jobs, first one is rendering, second one is the publishing job (triggered after successful finish of the rendering job). ![Jobs in DL](assets/deadline_fail.png) - Jobs are failing with `OpenPype executable was not found` error Check if OpenPype is installed on the Worker handling this job and ensure `OpenPype` Deadline Plug-in is properly [configured](#configuration) - Publishing job is failing with `ffmpeg not installed` error OpenPype executable has to have access to `ffmpeg` executable, check OpenPype `Setting > General` ![FFmpeg setting](assets/ffmpeg_path.png) - Both jobs finished successfully, but there is no review on Ftrack Make sure that you correctly set published family to be send to Ftrack. ![Ftrack Family](assets/ftrack/ftrack-collect-main.png) Example: I want send to Ftrack review of rendered images from Harmony : - `Host names`: "harmony" - `Families`: "render" - `Add Ftrack Family` to "Enabled" Make sure that you actually configured to create review for published subset in `project_settings/ftrack/publish/CollectFtrackFamily` ![Ftrack Family](assets/deadline_review.png) Example: I want to create review for all reviewable subsets in Harmony : - Add "harmony" as a new key an ".*" as a value. - Rendering jobs are stuck in 'Queued' state or failing Make sure that your Deadline is not limiting specific jobs to be run only on specific machines. (Eg. only some machines have installed particular application.) Check `project_settings/deadline` ![Deadline group](assets/deadline_group.png) Example: I have separated machines with "Harmony" installed into "harmony" group on Deadline. I want rendering jobs published from Harmony to run only on those machines.