Home for open source code related to AWS Deadline Cloud. AWS Deadline Cloud is a fully managed render farm service that simplifies infrastructure management and scaling for teams delivering computer generated imagery.
This GitHub org has integrations (such as job submission plugins) for a selection of digital content creation (DCC) software. These integrations allow users to submit jobs from inside their favorite applications. See the integrations user guide for more info about features, usage, and compatibility.
| Repository | Description |
|---|---|
| deadline-cloud | A Python CLI and library for interacting with Deadline Cloud, especially submitting jobs. |
| deadline-cloud-samples | Example code and tools for running workloads on Deadline Cloud. |
| deadline-cloud-job-attachments | A Python library for Deadline Cloud Job Attachments related functionality. |
| deadline-cloud-worker-agent | Software that runs on workers and communicates with the Deadline Cloud API for receiving and completing tasks. |
How do I install Deadline Cloud tools on my workstation?
You can run the Deadline Cloud submitter installer. The installer can be found by going to the AWS Console > AWS Deadline Cloud > Downloads > Deadline Cloud submitter installer > Download.
Where can I find documentation for the AWS Deadline Cloud service?
See the AWS Deadline Cloud documentation.
How do I report a bug with an integration or tool?
Please open an issue in the relevant repository.
How do I build my own integration?
You can look through deadline-cloud-samples for example job bundles, conda recipes, and other tooling. You can also look through the pre-built integrations below for larger examples.
Where can I find information about defining jobs?
Deadline uses Open Job Description for defining jobs. See the Open Job Description specification or other repositories in the Open Job Description GitHub org.
Do you accept feature requests or contributions?
Yes, contributions are gratefully accepted! You can open an issue to request a feature or receive early feedback on an idea before raising a pull request. Pull requests are welcomed for features that would be widely useful to the community and which align with the existing code base.
What if I want to adapt an existing integration to my specific workload?
Consider forking a repository and making your changes in the fork.