[Bug]: Failed To Parse GPU JSON

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What is the Issue?

The issue at hand is a failed attempt to parse GPU JSON data, resulting in an error message that reads "json: cannot unmarshal array into Go value of type models.GPUResponse." This error is being encountered on a server running a container with an NVIDIA GPU.

What Happened?

The error message indicates that the server is unable to parse the GPU JSON data in the expected format. The server is running a container with an NVIDIA GPU, and the nvidia-smi command is being used to monitor the GPU's performance. However, the server is unable to parse the GPU JSON data, resulting in the error message.

Steps to Reproduce the Issue

To reproduce the issue, follow these steps:

  1. Run the docker logs corecontrol-agent-1 command to view the container's logs.
  2. Look for the error message "Failed to parse GPU JSON: json: cannot unmarshal array into Go value of type models.GPUResponse."
  3. Check the server's configuration to ensure that the GPU JSON data is being generated correctly.
  4. Verify that the server is running the correct version of the container and that the NVIDIA GPU is properly configured.

Operating System and Version

The server is running on a Linux operating system with version v1.0.1.

Logs

The following logs are being generated by the server:

[Server WA] Updated - CPU: 4.00%, RAM: 48.90%, Disk: 73.50%, GPU: 0.00%, Temp: 30.00°C, Uptime: 26.4 19:59
[Server WA] Failed to parse GPU JSON: json: cannot unmarshal array into Go value of type models.GPUResponse
[Server WA] Updated - CPU: 4.30%, RAM: 48.90%, Disk: 73.50%, GPU: 0.00%, Temp: 30.00°C, Uptime: 26.4 19:59
[App Portainer (https://port.bortus.io)] Checking...
[Server WA] Checking...
[Server WA] Uptime: "5 days, 0:53:03" (formatted: 26.4 19:59)
[Server WA] Failed to parse GPU JSON: json: cannot unmarshal array into Go value of type models.GPUResponse
[Server WA] Updated - CPU: 4.70%, RAM: 48.90%, Disk: 73.50%, GPU: 0.00%, Temp: 30.00°C, Uptime: 26.4 19:59
[App Portainer (https://port.bortus.io)] Response status: 200
[Server WA] Checking...
[Server WA] Uptime: "5 days, 0:53:08" (formatted: 26.4 19:59)
[Server WA] Failed to parse GPU JSON: json: cannot unmarshal array into Go value of type models.GPUResponse
[Server WA] Updated - CPU: 4.00%, RAM: 48.90%, Disk: 73.50%, GPU: 0.00%, Temp: 30.00°C, Uptime: 26.4 19:59
[App Portainer (https://port.bortus.io)] Checking...
[Server WA] Checking...
Reloaded notification configurations
[Server WA] Uptime: "5 days, 0:53:12" (formatted: 26.4 19:59)
[Server WA] Failed to parse GPU JSON: json: cannot unmarshal array into Go value of type models.GPUResponse
[Server WA] Updated - CPU: 4.50%, RAM: 48.90%, Disk: 73.50%, GPU: 0.00%, Temp: 30.00°C, Uptime: 26.4 19:59
[App Portainer (https://port.bortus.io)] Response status: 200
[Server WA] Checking...
[Server WA] Uptime: "5 days, 0:53:18" (formatted: 26.4 19:59)
[Server WA] Failed to parse GPU JSON: json: cannot unmarshal array into Go value of type models.GPUResponse
[Server WA] Updated - CPU: 3.70%, RAM: 48.90%, Disk: 73.50%, GPU: 0.00%, Temp: 30.00°C, Uptime: 26.4 19:59
[App Portainer (https://port.bortus.io)] Checking...
[Server WA] Checking...
[App Portainer (https://port.bortus.io)] Response status: 200
[Server WA] Uptime: "5 days, 0:53:23" (formatted: 26.4 19:59)
[Server WA] Failed to parse GPU JSON: json: cannot unmarshal array into Go value of type models.GPUResponse
[Server WA] Updated - CPU: 4.20%, RAM: 48.90%, Disk: 73.50%, GPU: 0.00%, Temp: 30.00°C, Uptime: 26.4 19:59
[Server WA] Checking...
[Server WA] Uptime: "5 days, 0:53:27" (formatted: 26.4 19:59)
[Server WA] Failed to parse GPU JSON: json: cannot unmarshal array into Go value of type models.GPUResponse
[Server WA] Updated - CPU: 4.40%, RAM: 48.90%, Disk: 73.50%, GPU: 0.00%, Temp: 30.00°C, Uptime: 26.4 19:59

Additional Information

The server with the glances container has an NVIDIA GPU. The nvidia-smi command is being used to monitor the GPU's performance.

bortus@wa:~$ nvidia-smi
Thu May  1 15:53:36 2025       
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 470.256.02   Driver Version: 570.133.20   CUDA Version: 12.8     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  Tesla P4            Off  | 00000000:18:00.0 Off |                    0 |
| N/A   58C    P0    24W /  75W |    349MiB /  7680MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
                                                                               
+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|    0   N/A  N/A   1408280      C   /opt/emby-server/bin/ffmpeg       266MiB |
+-----------------------------------------------------------------------------+

Troubleshooting Steps

To troubleshoot this issue, follow these steps:

  1. Check the server's configuration to ensure that the GPU JSON data is being generated correctly.
  2. Verify that the server is running the correct version of the container and that the NVIDIA GPU is properly configured.
  3. Check the logs for any errors or warnings related to the GPU JSON parsing.
  4. Try to reproduce the issue by running the docker logs corecontrol-agent-1 command and looking for the error message.
  5. If the issue persists, try to debug the code by adding print statements or using a debugger to identify the source of the error.

Conclusion

Q: What is the issue with parsing GPU JSON?

A: The issue is that the server is unable to parse the GPU JSON data in the expected format, resulting in an error message that reads "json: cannot unmarshal array into Go value of type models.GPUResponse."

Q: What is the cause of this issue?

A: The cause of this issue is likely due to a mismatch between the expected format of the GPU JSON data and the actual format of the data being generated by the server.

Q: How can I troubleshoot this issue?

A: To troubleshoot this issue, follow these steps:

  1. Check the server's configuration to ensure that the GPU JSON data is being generated correctly.
  2. Verify that the server is running the correct version of the container and that the NVIDIA GPU is properly configured.
  3. Check the logs for any errors or warnings related to the GPU JSON parsing.
  4. Try to reproduce the issue by running the docker logs corecontrol-agent-1 command and looking for the error message.
  5. If the issue persists, try to debug the code by adding print statements or using a debugger to identify the source of the error.

Q: What are some common causes of this issue?

A: Some common causes of this issue include:

  • A mismatch between the expected format of the GPU JSON data and the actual format of the data being generated by the server.
  • A problem with the server's configuration, such as a missing or incorrect GPU driver.
  • A problem with the container's configuration, such as a missing or incorrect NVIDIA GPU.
  • A problem with the code that is parsing the GPU JSON data, such as a bug or a missing dependency.

Q: How can I prevent this issue from occurring in the future?

A: To prevent this issue from occurring in the future, follow these best practices:

  • Ensure that the server's configuration is correct and up-to-date.
  • Verify that the server is running the correct version of the container and that the NVIDIA GPU is properly configured.
  • Check the logs regularly for any errors or warnings related to the GPU JSON parsing.
  • Test the code that is parsing the GPU JSON data thoroughly to ensure that it is working correctly.

Q: What are some additional resources that can help me troubleshoot this issue?

A: Some additional resources that can help you troubleshoot this issue include:

  • The official NVIDIA documentation for the GPU driver and the container.
  • The official Docker documentation for the container and the NVIDIA GPU.
  • Online forums and communities, such as the NVIDIA forums and the Docker forums.
  • Stack Overflow and other Q&A websites.

Q: Can you provide an example of how to debug this issue?

A: Here is an example of how to debug this issue:

  1. Add print statements to the code that is parsing the GPU JSON data to see what the data looks like.
  2. Use a debugger to step through the code and see where it is failing.
  3. Check the logs for any errors or warnings related to the GPU JSON parsing.
  4. Try to reproduce the issue by running the docker logs corecontrol-agent-1 and looking for the error message.

Q: Can you provide an example of how to fix this issue?

A: Here is an example of how to fix this issue:

  1. Update the server's configuration to ensure that the GPU JSON data is being generated correctly.
  2. Verify that the server is running the correct version of the container and that the NVIDIA GPU is properly configured.
  3. Check the logs for any errors or warnings related to the GPU JSON parsing.
  4. Try to reproduce the issue by running the docker logs corecontrol-agent-1 command and looking for the error message.

Conclusion

In conclusion, the issue of failed GPU JSON parsing is a complex problem that requires a thorough understanding of the server's configuration and the container's behavior. By following the troubleshooting steps outlined above and using the additional resources provided, you should be able to identify and resolve the issue. If you are still experiencing problems, please provide more information about your setup and the error messages you are seeing, and I will do my best to assist you further.