title | linkTitle | weight | date | description |
---|---|---|---|---|
Quick start for macOS |
Quick start for macOS |
1 |
2019-09-04 |
Try OpenCue in the sandbox environment on macOS
|
OpenCue is an open source render management system. You can use OpenCue in visual effects and animation production to break down complex jobs into individual tasks. You can submit jobs to a queue that allocates rendering resources. You can also monitor rendering jobs from your workstation.
The sandbox environment provides a way to quickly start a test OpenCue deployment. You can use the test deployment to run small tests or for development work. The sandbox environment runs OpenCue components in separate Docker containers on your local machine.
This quick start takes approximately 20 minutes to complete.
You must have the following software installed on your machine:
- Python version 2.7 or greater
- The Python
pip
command - The Python virtualenv tool
- Docker
- Docker Compose
{{% alert title="Note" color="info"%}}Docker compose is included in the desktop installation of Docker on macOS.{{% /alert %}}
You must allocate a minimum of 6 GB of memory to Docker. To learn how to update the memory limit on macOS, see Get started with Docker Desktop for Mac.
If you don't already have a recent local copy of the OpenCue source code, you must do one of the following:
-
Download and unzip the OpenCue source code ZIP file.
-
If you have the
git
command installed on your machine, you can clone the repository:git clone https://github.com/AcademySoftwareFoundation/OpenCue.git
You deploy the sandbox environment using Docker Compose, which runs the following containers:
- a PostgresSQL database
- a Cuebot server
- an RQD rendering server
{{% alert title="Note" color="info"%}}In a production OpenCue deployment, you might run many hundreds of RQD rendering servers.{{% /alert %}}
The Docker Compose deployment process also configures the database and applies
any database migrations. The deployment process creates a db-data
directory
in the sandbox
directory. The db-data
directory is mounted as a volume in
the PostgresSQL database container and stores the contents of the database. If
you stop your database container, all data is preserved as long as you don't
remove this directory. If you need to start from scratch with a fresh
database, remove the contents of this directory and restart the containers
with the docker-compose
command.
To deploy the OpenCue sandbox environment:
-
Start the Terminal app.
-
Change to the root of the OpenCue source code directory:
cd OpenCue
-
To deploy the OpenCue sandbox environment, export the
CUE_FRAME_LOG_DIR
environment variable:{{% alert title="Note" color="info"%}}You must export all environment variables each time you start the sandbox.{{% /alert %}}
export CUE_FRAME_LOG_DIR=/tmp/rqd/logs
-
To specify a password for the database, export the
POSTGRES_PASSWORD
environment variable:export POSTGRES_PASSWORD=<REPLACE-WITH-A-PASSWORD>
-
To deploy the sandbox environment, run the
docker-compose
command:docker-compose --project-directory . -f sandbox/docker-compose.yml up
The command produces a lot of output. When the setup process completes, you see output similar to the following example:
rqd_1 | 2019-09-03 16:56:09,906 WARNING rqd3-__main__ RQD Starting Up rqd_1 | 2019-09-03 16:56:10,395 WARNING rqd3-rqcore RQD Started cuebot_1 | 2019-09-03 16:56:10,405 WARN pool-1-thread-1 com.imageworks.spcue.dispatcher.HostReportHandler - Unable to find host 172.18.0.5,org.springframework.dao.EmptyResultDataAccessException: Failed to find host 172.18.0.5 , c reating host.
Leave this shell running in the background.
OpenCue includes the following client packages to help you submit, monitor, and manage rendering jobs:
- PyCue is the OpenCue Python API. OpenCue client-side Python tools, such as
CueGUI and
cueadmin
, all use PyCue for communicating with your OpenCue deployment. - PyOutline is a Python library that provides a Python interface to the job specification XML. You can use PyOutline to construct complex jobs with Python code instead of working directly with XML.
- CueSubmit is a graphical user interface for configuring and launching rendering jobs to an OpenCue deployment.
- CueGUI is a graphical user interface you run to monitor and manage jobs, layers, and frames.
cueadmin
is the OpenCue command-line client for administering an OpenCue deployment.pycuerun
is a command-line client for submitting jobs to OpenCue.
To install the OpenCue client packages:
-
Open a second Terminal window.
-
Change to the root of the OpenCue source code directory:
cd OpenCue
-
Create a virtual environment for the Python packages:
virtualenv venv
-
Activate the
venv
virtual environment:source venv/bin/activate
-
Install the Python dependencies and client packages in the
venv
virtual environment:sandbox/install-clients.sh
To connect to the sandbox environment, you must first configure your local client packages to:
- Locate the
outline.cfg
PyOutline configuration file included in the OpenCue Git repository. - Locate the Cuebot server running in a Docker container on your machine.
To test the sandbox environment, run the following commands from the second Terminal window:
-
Set the location of the PyOutline configuration file:
{{% alert title="Note" color="info"%}}You must export all environment variables each time you start the client packages.{{% /alert %}}
export OL_CONFIG=pyoutline/etc/outline.cfg
-
The Cuebot docker container is forwarding the gRPC ports to your localhost, so you can connect to it as
localhost
:export CUEBOT_HOSTS=localhost
-
To verify the successful installation of the sandbox environment, as well as the connection between the client packages and sandbox, you can run the
cueadmin
command-line tool. To list the hosts in the sandbox environment, run the followingcueadmin
command:cueadmin -lh
The command produces output similar to the following:
Host Load NIMBY freeMem freeSwap freeMcp Cores Mem Idle Os Uptime State Locked Alloc Thread 172.18.0.5 52 False 24.2G 0K 183.1G 2.0 25.5G [ 2.00 / 25.5G ] Linux 00:04 UP OPEN local.general AUTO
-
Launch the CueSubmit app for submitting jobs:
{{% alert title="Note" color="info"%}}The OpenCue sandbox environment doesn't include any rendering software. To experiment with the user interface, you can execute simple command-line scripts.{{% /alert %}}
cuesubmit &
-
Launch the CueGUI app for monitoring jobs:
cuegui &
To delete the resources you created in this guide, run the following commands from the second shell:
-
To stop the sandbox environment, run the following command:
docker-compose --project-directory . -f sandbox/docker-compose.yml stop
-
To free up storage space, delete the containers:
docker-compose --project-directory . -f sandbox/docker-compose.yml rm
-
To delete the virtual environment for the Python client packages:
rm -rf venv
- Learn more about OpenCue concepts and terminology.
- Install the full OpenCue infrastructure.