@Marvin I am using this dockerfile to run my workloads in an azure push workpool with GPUs:

FROM nvidia/cuda:11.6.2-runtime-ubuntu20.04

When running a deployment, I get this error. Why would it be? Do you have any solution?

Flow run infrastructure exited with non-zero status code:
 Container exited with non-zero code (Error Code: 127)
This may be caused by attempting to run an image with a misspecified platform or architecture.

The error message you're encountering suggests that there might be an issue with the platform or architecture for the Docker image you're using. Specifically, error code 127 usually indicates that a command or file was not found, which can often arise from a mismatch in the expected environment. Here are a few steps to troubleshoot and potentially resolve the issue: 1. Check the CUDA Image Compatibility: Ensure that the

nvidia/cuda:11.6.2-runtime-ubuntu20.04

image is compatible with your deployment environment, especially considering the GPU requirements. 2. Install Required Dependencies: It might be that the image you're using doesn't have all the necessary dependencies. Specifically, check if Python and other required packages are installed. You can add the following to your Dockerfile:

Dockerfile
   FROM nvidia/cuda:11.6.2-runtime-ubuntu20.04

   # Install Python and other dependencies
   RUN apt-get update && apt-get install -y \
       python3 \
       python3-pip \
       && rm -rf /var/lib/apt/lists/*
   
   # Install Prefect
   RUN pip3 install prefect

3. Verify the Dockerfile and Prefect Configuration: Ensure that your Dockerfile is correctly set up for Prefect and that your deployments are configured to use the correct Docker image. Here is an example of how you might set up your workload:

Dockerfile
   # Base image
   FROM nvidia/cuda:11.6.2-runtime-ubuntu20.04

   # Install Python
   RUN apt-get update && apt-get install -y python3 python3-pip

   # Install Prefect
   RUN pip3 install prefect

   # Copy your flow code
   COPY your_flow.py /opt/prefect/flows/

   # Set the working directory
   WORKDIR /opt/prefect/flows/

   # Run the Prefect flow
   CMD ["python3", "your_flow.py"]

4. Test Locally: Before deploying, build and run your Docker image locally to ensure everything works as expected. This can help isolate whether the issue is with the Docker image itself or the deployment environment. 5. Platform and Architecture: Make sure that your deployment environment, such as the Azure push work pool, is configured to support the platform and architecture of your Docker image, especially since you're using CUDA for GPU workloads. If you continue facing issues, you might find useful information and troubleshooting steps in the Prefect documentation: - Prefect 2.x Docker Worker - Prefect 3.x Docker Infrastructure I hope this helps! If you have any more questions or if the issue persists, feel free to ask.