Quick start guide
- Prerequisites
- Setting up a Deadline repository on Ubuntu
- Setting up a local workstation
- Setting up a CPU/GPU rendering node
Prerequisites
- Create a project and add an SSH key
- Optionally download CLI tool
Setting up a Deadline repository on Ubuntu
- Choose a virtual machine add enough storage to hold your input and output media
- Use the Ubuntu 22.04 + Docker image (in CLI tool type
-image ubuntu-2204-docker)
password to a secure memorable password, you will need it for the remote server client later
Also replace the IP address of your server
/opt/Thinkbox/DeadlineRepository10
In order for Deadline to function correctly, it is essential that the Repository is visible to all connecting machines.
This particular section outlines the process of sharing the Repository folder and adjusting its permissions to
guarantee that Clients are granted the required access. Specifically, the Clients must be granted read access
to both the Repository root and its subdirectories.
Using the file share
To access your shared directory on the server via your local computer (replace the password): LinuxInstalling the remote connection server
The remote connection server allows for secure remote access to the Deadline database, enabling users to monitor and manage rendering jobs from outside the local network. It will be used for your local clients to connect to.Setting up a local workstation
To install a client on your local Windows, Mac, or Linux computer follow these instructions: https://docs.thinkboxsoftware.com/products/deadline/10.2/1_User%20Manual/manual/quick-install-client.html Configure your client to use a remote connection (not direct) with the following addressyour-server-ip:4433 use TLS
and supply the certificate from the server /opt/Thinkbox/Deadline10/certs/Deadline10RemoteClient.pfx
(you will need to copy it to your local computer)
You can copy it to your local device like this (Linux):
Setting up a CPU/GPU rendering node
- Choose a virtual machine with an NVIDIA GPU and Configure
- Use the Ubuntu 22.04 + NVIDIA drivers + Docker image (in CLI tool type
-image ubuntu-nvidia-docker)
- Choose a CPU only virtual machine
- Use the Ubuntu 22.04 + Docker image (in CLI tool type
-image ubuntu-2204-docker)