Ready-to-run AWS Deadline Cloud samples for rendering (Maya, Blender, Houdini, Nuke); physical AI (robotics, autonomous driving simulation, MuJoCo, CARLA); synthetic data generation; generative AI video; and bioinformatics.
AWS Deadline Cloud samples
Build, submit, and operate real workloads on AWS Deadline Cloud. Start with the task you want to complete. Each sample stays self-contained in its existing directory.
What do you want to do?
| Goal | Start here | |---|---| | Deploy a farm | CloudFormation starter farm, Terraform starter farm, or AWS CDK starter farm | | Learn how a job is structured | Job development progression or the minimal job | | Render with a DCC | Blender render, Maya CLI render, or browse the job bundles | | Run a new DCC or application | Read about custom software delivery, then browse Conda recipes, host configuration scripts, containers, and job bundles | | Deliver custom plugins | Read about Plugin Sync, then compare plugin packages, host installations, and queue environments | | Connect studio systems | Browse submission hooks, custom submitters, queue environments, and event notifications | | Find a specific example | Use the repository map, then browse that area's complete category table | | Create a sample with an AI agent | Inspect skills for a matching task guide |
Quick start
- Configure a Deadline Cloud farm and install the
- Clone this repository and open its root directory.
- Preview a job's submission interface:
deadline bundle gui-submit jobbundles/guicontrol_showcase- Submit the minimal job to your configured queue:
deadline bundle submit jobbundles/simplejobRead each sample's README before deployment or submission. Samples can create billable AWS resources or run licensed software; review parameters, IAM permissions, licensing, and cleanup instructions first.
Repository map
| Area | Use it for | |---|---| | CloudFormation | Deploy starter farms, fleet support, storage, capacity automation, and notifications. | | Terraform | Deploy a starter farm with Terraform. | | AWS CDK | Deploy a starter farm with the AWS CDK in TypeScript. | | Job bundles | Define OpenJD rendering, simulation, ML, scientific, and utility jobs. | | Conda recipes | Build applications, adaptors, renderers, and plugins into versioned packages. | | Containers | Build worker-compatible or application container images. | | Queue environments | Prepare Conda, Rez, pip, caching, and licensing once per worker session. | | Host configuration scripts | Install privileged software and configure service-managed fleet worker hosts. | | Submission hooks | Inspect or modify job bundles immediately before submission. | | Utility scripts | Automate supporting tasks such as uploading job attachments. | | Agent skills | Give coding agents repeatable instructions for authoring jobs, packages, and host configs. | | Contributor documentation | Use the adaptable sample README starting point. | | Repository validation | Run unit, local-link, and live external-link checks. |
Each sample area README declares its tracked scope and provides a complete local index. Nested collection READMEs provide their own complete tables, while the root routes users to recommended paths rather than duplicating every sample.
Documentation
- AWS Deadline Cloud developer guide
- AWS Deadline Cloud user guide
- AWS Deadline Cloud API reference
- Open Job Description specification
- Contributing a sample
Security
If you discover a potential security issue, notify AWS Security through the vulnerability reporting page or email AWS Security. Do not create a public GitHub issue.
License
This repository is licensed under the MIT-0 License.
