Document Details

Azure Stack Edge Gpu Modify Fpga Modules Gpu
Home / Scan #41 / Azure Stack Edge Gpu Modify Fpga Modules Gpu
Sad Tux - Windows bias detected
This page contains Windows bias

About This Page

This page is part of the Azure documentation. It contains code examples and configuration instructions for working with Azure services.
GitHub View on GitHub 📚 View on Microsoft Learn

Bias Analysis

Detected Bias Types
windows_tools
windows_first
powershell_heavy
Summary
The documentation page demonstrates a moderate Windows bias, particularly in the networking section, where it references using the PowerShell interface to interact with the device and retrieve module information. The PowerShell method is mentioned before any Linux or cross-platform alternatives, and there is no mention of Linux-native tools or CLI commands for similar tasks. The overall documentation assumes familiarity with Windows-centric tools and patterns, with no explicit Linux command-line examples or instructions, despite recommending Linux VMs for IoT Edge deployment.
Recommendations
  • Provide Linux-native command-line examples (e.g., using SSH and iotedge CLI) for querying module status and IP addresses.
  • Mention cross-platform alternatives (such as Azure CLI, kubectl, or iotedge CLI) alongside or before PowerShell-based instructions.
  • Ensure that all references to device management interfaces include both Windows (PowerShell) and Linux (Bash/SSH) options.
  • Add explicit Linux usage patterns for common tasks, such as monitoring modules, retrieving logs, and troubleshooting.
  • Review and update all sections to avoid assuming the user is operating from a Windows environment.
GitHub Create Pull Request

Scan History

Date Scan Status Result
2025-07-12 23:44 #41 cancelled Biased Biased
2025-07-12 00:58 #8 cancelled Clean Clean
2025-07-10 05:06 #7 processing Clean Clean

Flagged Code Snippets

{
  "HostConfig": 
  {
   "Binds": 
    [
     "<Host storage path for Edge local share>:<Module storage path>"
    ]
   }
}

However, to query the IP address assigned to your module, you can use the Kubernetes dashboard as described in [Get IP address for services or modules](azure-stack-edge-gpu-monitor-kubernetes-dashboard.md#get-ip-address-for-services-or-modules). 

Alternatively, you can [Connect to the PowerShell interface of the device](azure-stack-edge-gpu-connect-powershell-interface.md#connect-to-the-powershell-interface) and use the `iotedge` list command to list all the modules running on your device. The [Command output](azure-stack-edge-gpu-connect-powershell-interface.md#debug-kubernetes-issues-related-to-iot-edge) will also indicate the external IPs associated with the module.


## Resource usage 

With the Kubernetes-based IoT Edge setups on GPU devices, the resources such as hardware acceleration, memory, and CPU requirements are specified differently than on the FPGA devices. 

#### Compute acceleration usage

To deploy modules on FPGA, use the container create options <!--with Device Bindings--> as shown in the following config: <!--not sure where are device bindings in this config-->