Job bundles are the easiest way to define your jobs for AWS Deadline Cloud. They encapsulate an Open Job Description job template into a directory with additional information such the files and directories that your Jobs need. Read more about how to build a job bundle in the Deadline Cloud developer guide. See the example Blender job submission below for more about submitting these jobs to your farm.
This list highlights just a few of the available job bundles. Browse the directory directly to discover the rest!
The simple_job job bundle supplements the Deadline Cloud developer guide set up a developer farm section. You can step through its instructions to get a developer-focused overview, using the AWS and Deadline Cloud CLIs to create a farm, queue, and fleets, submit jobs, and see the details of how job attachments work.
The job bundles job_env_vars, job_env_with_new_command, and job_env_daemon_process supplement the developer guide control the job environment section. These jobs show how to use Open Job Description environments. Look at the queue environment samples for more ideas.
The job bundles job_attachments_devguide and job_attachments_devguide_output
supplement the developer guide job attachments section.
Learn how data flow metadata on path job parameters and the job bundle asset_references.yaml file work together to describe the files
a job needs as input, and produce as output. When job bundles specify this metadata, they can work with either job attachments or shared file systems.
The cli_job job bundle is a way to submit a multi-line bash script to Deadline Cloud. The script job parameter uses a multi-line edit control, and a data directory job parameter lets you select a directory of data for the script to read from and write to.
The gui_control_showcase job bundle shows every GUI control that user interface metadata on Open Job Description job parameters support.
Developing a job bundle can start small and simple, then grow complex as you add more job parameters, steps, and scripts. The job_dev_progression directory contains a sequence of four job bundle development stages to help manage that growing complexity. Read through the code and run these jobs on your Deadline Cloud farm to get a feel for it.
The blender_render job bundle shows how to support a CLI application in about 100 lines of YAML. A majority of the template is metadata for the job parameters, defining the parameter names, types, defaults, and user interface metadata. The step definition includes a parameter space to define a task for each frame for a range expression in the Frames job parameter, and a short script that substitutes job parameters and the Frame task parameter into a script command for each task.
If you've created a similar job for your favorite DCC, see CONTRIBUTING.md for how to add it here.
The turntable_with_maya_arnold job bundle is an example pipeline utility job for taking a 3D model stored as an OBJ file, and creating a turntable render video. It demonstrates how someone comfortable with YAML and scripting in a digital content creation (DCC) application can create utility jobs that are easy to submit from a GUI.
The tile_render_with_maya_arnold job bundle demonstrates a two-step job that first renders all the frames in tiles using a 3-dimensional task parameter space (Frame * TileNumberX * TileNumberY), and then assembles all the tiles for each frame using FFmpeg. It includes a simple scene and default parameters to make it simple to try out.
The tile_render_maya_ffmpeg_for_blogpost job bundle goes with the blog post Create a tile rendering job with modifications for AWS Deadline Cloud that walks through customizing one of the Deadline Cloud adaptors and writing a tile rendering job template.
The copy_s3_prefix_to_job_attachments job bundle can help you pre-populate a queue's job attachment S3 bucket with data files by copying them from where they are already stored on S3. It scans the source S3 prefix, then distributes the hashing and data copies across a number of workers you specify. Because job attachments uses content-addressed storage for data files, users that later submit jobs with these files attached will not have to upload them.
With a job bundle in hand, the Deadline Cloud CLI provides ways for you to submit jobs to run on your Deadline Cloud queues. Read more about how to submit a job in the Deadline Cloud developer guide.
Here's the submitter GUI you can see after configuring the Deadline Cloud CLI
and running deadline bundle gui-submit blender_render/ in this samples directory:
Alternatively, you can submit this job bundle with the command
deadline bundle submit --name Demo -p BlenderSceneFile=<location-of-your-scene-file> -p OutputDir=<file-path-for-job-outputs> blender_render/
or use the deadline.client.api.create_job_from_job_bundle function in the deadline Python package.
If you do not want to use the deadline Python package's support for features like job attachments, you can also submit the job template by calling the
deadline:CreateJob API directly.