Isaac Automator allows a quick deployment of Isaac Sim and Isaac Lab to the public clouds (AWS, GCP, Azure, and Alibaba Cloud are currently supported).
The result is a fully configured remote-desktop cloud workstation, which can be used for development and testing of the robotic applications within minutes and on a budget. Isaac Automator supports varierty of GPU instances and stop-start functionality to save on cloud costs, provides tools to aid the workflow (uploading and downloading data, autorun, deployment management, etc).
docker
should be present on your system. Visit https://docs.docker.com/engine/install/ for installation instructions.
NGC API Key allows you to download docker images from https://ngc.nvidia.com/. Please prepare one or obtain it at https://ngc.nvidia.com/setup/api-key.
Please enter the following command in the project root directory to build the container:
./build
docker build --platform linux/x86_64 -t isa .
This will build the Isaac Automator container and tag it as isa
.
On Linux and MacOS there are two ways to run the automator commands:
# enter the automator container
./run
# inside container:
./somecommand
./run
like so:./run ./somecommand <parameters>
for example:
./run ./deploy-aws
./run ./destroy my-deployment
On Windows, you can run the automator commands by entering the container first and then running the command inside the container like so:
(enter the automator container)
docker run --platform linux/x86_64 -it --rm -v .:/app isa bash
(run the command inside the container)
./somecommand
If yoou have completed the above steps or already have your permissions and credentials set up, run the following command in the project root directory:
# enter the automator container
./run
# inside container:
./deploy-aws
Tip: Run ./deploy-aws --help
to see more options.
# enter the automator container
./run
# inside container:
./deploy-gcp
Tip: Run ./deploy-gcp --help
to see more options.
If You Have Single Subscription:
# enter the automator container
./run
# inside container:
./deploy-azure
If You Have Multiple Subscriptions:
# enter the automator container
./run
# inside container:
az login # login
az account show --output table # list subscriptions
az account set --subscription "<subscription_name>"
./deploy-azure --no-login
Tip: Run ./deploy-azure --help
to see more options.
Once you have prepared the access credentials, run the following command in the project root directory:
# enter the automator container
./run
# inside container:
./deploy-alicloud
Tip: Run ./deploy-alicloud --help
to see more options.
GPU-accelerated instances with NVIDIA A100, A10 and T4 GPUs are supported. You can find the complete list of instance types, availability and pricing at https://www.alibabacloud.com/help/en/ecs/user-guide/gpu-accelerated-compute-optimized-and-vgpu-accelerated-instance-families-1. Please note that vGPU instances are not supported.
Deployed Isaac Sim instances can be accessed via:
Look for the connection instructions at the end of the deploymnt command output. Additionally, this info is saved in state/<deployment-name>/info.txt
file.
You can view available arguments with --help
switch for the start scripts, in most cases you wouldn't need to change the defaults.
Tip: You can use ./connect <deployment-name>
helper command to connect to the deployed instance via ssh.
To use installed applications, connect to the deployed instance using noVNC or NoMachine. You can find the connection instructions at the end of the deployment command output. Additionally, this info is saved in state/<deployment-name>/info.txt
file.
Isaac Sim will be automatically started when cloud VM is deployed. Alternatively you can click "Isaac Sim" icon on the desktop or run the following command in the terminal on the deployed instance or launch it from the terminal as follows:
~/isaacsim.sh
To get a shell inside Isaac Sim container, click "Isaac Sim Shell" icon on the desktop. Alternatively you can run the following command in the terminal on the deployed instance:
~/isaacsim-shell.sh
Isaac Lab can be pre-installed on the deployed instances. To install a specific version of Isaac Lab, provide valid git reference from https://isaac-sim.github.io/IsaacLab/ as a value of --lab
parameter to the deployment command.
To run Isaac Lab click "Isaac Lab" icon on the desktop or run the following command in the terminal:
~/isaaclab.sh
Omniverse Isaac Gym Environments is deprecated in favor of Isaac Lab.
Omniverse Isaac Gym Reinforcement Learning Environments for Isaac Sim ("Omni Isaac Gym Envs") can be pre-installed on the deployed Isaac instances.
To run Omniverse Isaac Gym Environments click "Omni Isaac Gym Envs" icon on the desktop or run the following command in the terminal:
~/omni-isaac-gym-envs.sh
Default output directory (/OmniIsaacGymEnvs/omniisaacgymenvs/runs
) in the OmniIsaacGymEnvs contaner will be linked to the default results directory (/home/ubuntu/results
) on the deployed instance. You can download the contents of this directory to your local machine using ./download <deployment_name>
command.
Tip: To install a specific version of OmniIsaacGymEnvs, provide valid reference from https://github.com/NVIDIA-Omniverse/OmniIsaacGymEnvs as a value of --oige
parameter to the deployment command. For example, to install devel
branch on an AWS instance, run the following command:
./deploy-aws --oige devel
By default, Isaac Sim will be started when the cloud VM is deployed.
If you want to launch a custom application or script on startup, you can modify the uploads/autorun.sh
script (on your local machine). It will either be uploaded to the cloud VM automatically or you can upload it manually using the ./upload
command.
Every time the cloud VM is deployed or started from a stopped state, the autorun.sh
script will be executed.
This functionality can be useful for running batch jobs, generating data on startup or preparing the environment for the user.
The following folders are mapped to the running Isaac Sim container by default (container paths may be different for specific applications):
/home/ubuntu/uploads
(host) --> /uploads
(container) - user data uploaded to the deployment with ./upload
command or automatically from local uploads/
folder/home/ubuntu/results
(host) --> /results
(container) - results of the applications run on the deployment, can be downloaded from the deployed machine with ./download
command/home/ubuntu/workspace
(host) --> /workspace
(container) - workspace folder, can be used to exchange data between the host and the container.You can stop and re-start instances to save on cloud costs. To do so, run the following commands:
# enter the automator container
./run
# inside container:
./stop <deployment-name>
./start <deployment-name>
You can upload user data from uploads/
folder (in the project root) to the deployment by running the following command:
# enter the automator container
./run
# inside container:
./upload <deployment-name>
Data will be uploaded to /home/ubuntu/uploads
directory by default to all deployed instances. You can change this by passing --remote-dir
argument to the command. Run ./upload --help
to see more options.
You can download user data to results/
folder (in the project root) from deployed instances by running the following command:
# enter the automator container
./run
# inside container:
./download <deployment-name>
Data will be downloaded from /home/ubuntu/results
directory by default. You can change this by passing --remote-dir
argument to the command. Run ./download --help
to see more options.
If for some reason the deployment cloud resouces or software configuration get corrupted, you can attempt to repair the deployment by running the following command:
# run both terraform and ansible
./repair <deployment-name>
# just run terraform to try fixing the cloud resources
./repair <deployment-name> --no-ansible
# just run ansible to try fixing the software configuration
./repair <deployment-name> --no-terraform
To destroy a deployment, run the following command:
# enter the automator container
./run
# inside container:
./destroy <deployment-name>
You will be prompted to enter the deployment name to destroy.
Please note that information about the deployed cloud resources is stored in state/
directory. Do not delete this directory ever.