Deploy NVIDIA Omniverse on AWS

Thank you for your inquiry about deploying NVIDIA Omniverse Nucleus using Amazon ECS or AWS Fargate as alternatives to the Amazon EC2 deployment described in the AWS blog post.

Yes, you can use Amazon ECS to run NVIDIA Omniverse Nucleus since Omniverse Nucleus itself does not require a GPU-backed instance, which makes it compatible with container orchestration services like Amazon ECS. The Nucleus server functions primarily as a database and collaboration engine, using Docker containers orchestrated via Docker Compose.

AWS Fargate is also a viable option for running the Nucleus server components, as it provides serverless compute for containers without managing the underlying infrastructure. This could simplify your operational overhead compared to managing EC2 instances.

To migrate from the EC2-based deployment to ECS or Fargate, you would need to:

1. Convert Docker Compose to ECS Task Definitions: NVIDIA Omniverse Nucleus uses Docker Compose to orchestrate multiple containers. You'll need to convert these definitions to ECS task definitions.
2. Networking Configuration: Adapt the network configuration to work with ECS/Fargate networking models, ensuring proper container communication.
3. Data Persistence: Configure persistent storage using Amazon EFS or other appropriate storage solutions to replace the EBS volumes used in the EC2 deployment.
4. Proxy Configuration: Adjust the NGINX reverse proxy setup to work within the containerized environment.
5. Access Management: Modify the IAM roles and policies to align with ECS/Fargate permission models.

Be aware of these potential challenges:

• The original Docker Compose setup may use host networking features not directly supported in Fargate
• Performance tuning might be required for optimal operation
• Backup and recovery processes would need to be redesigned for the containerized environment

As well I'd like to note that the reference architecture outlined in the blog post is a proof-of-concept architecture of Omniverse Nucleus on AWS. It is not intended as a production ready solution. For a more robust approach to NVIDIA Omniverse on AWS, please reference our open-source solution on Github: https://github.com/aws-samples/nvidia-omniverse-modular-solution-with-aws-cdk

While the blog post you mentioned discusses deploying NVIDIA Omniverse Nucleus on Amazon EC2, it's important to note that deploying NVIDIA Omniverse on Amazon ECS or AWS Fargate is not a straightforward or directly supported option based on the information provided in the available sources.

NVIDIA Omniverse typically requires GPU acceleration for optimal performance, which is not natively supported by AWS Fargate. Amazon ECS does support GPU workloads, but there are specific considerations and requirements to keep in mind:

1. For Amazon ECS, you would need to use EC2 instances with GPU capabilities. ECS provides GPU-optimized Amazon Machine Images (AMIs) with pre-configured NVIDIA kernel drivers and Docker GPU runtime.

2. You would need to use supported GPU-based instance types such as p2, p3, p4d, p5, g3, g4, g5, g6, or g6e series.

3. In your ECS task definitions, you would need to specify GPU requirements for optimal performance.

4. If you're using P2 instances, there are specific considerations and potential workarounds due to driver compatibility issues.

Given the complexity and specific requirements of NVIDIA Omniverse, it's recommended to follow NVIDIA's official deployment guidelines, which typically involve using dedicated GPU-enabled instances like those provided by Amazon EC2.

If you're looking to containerize and orchestrate GPU workloads, you might consider using Amazon EKS (Elastic Kubernetes Service) with GPU-enabled nodes, as this provides more flexibility for complex deployments requiring GPU acceleration.

Remember that deploying NVIDIA Omniverse or similar complex GPU-accelerated applications may require careful planning and potentially custom configurations to ensure optimal performance and compatibility with AWS services.
Sources
Amazon ECS task definitions for GPU workloads - Amazon Elastic Container Service
Gain operational insights for NVIDIA GPU workloads using Amazon CloudWatch Container Insights | AWS Cloud Operations Blog