# Troubleshooting

This page provides troubleshooting steps, FAQs, and resources to help you resolve common issues.
If you encounter any problems with the application not addressed here, check the
[GitHub Issues](https://github.com/open-edge-platform/edge-ai-suites/issues) board. Feel free
to file new tickets there (after learning about the guidelines for
[Contributing](https://github.com/open-edge-platform/edge-ai-suites/blob/release-2026.2.0/CONTRIBUTING.md)).

## Troubleshooting Steps

1. **Changing the Host IP Address**

   - If you need to use a specific Host IP address instead of the one
     automatically detected during installation, you can explicitly provide it
     using the following command:

     ```bash
     ./install.sh <application-name> <HOST_IP>
     ```

     Example:

     ```bash
     ./install.sh smart-parking 192.168.1.100
     ```

2. **Containers Not Starting**
   - Check the Docker logs for errors:

     ```bash
     docker ps -a
     docker logs <CONTAINER_ID>
     ```

3. **Failed Service Deployment**

   - If unable to deploy services successfully due to proxy issues, ensure the
     proxy is configured in the `~/.docker/config.json`:

     ```json
     {
       "proxies": {
         "default": {
           "httpProxy": "http://your-proxy:port",
           "httpsProxy": "https://your-proxy:port",
           "noProxy": "localhost,127.0.0.1"
         }
       }
     }
     ```

   - After editing the file, restart docker:

     ```bash
     sudo systemctl daemon-reload
     sudo systemctl restart docker
     ```

4. **Video stream not displaying on Grafana UI**

   - If you do not see the video stream because of a URL issue, ensure that
     `WEBRTC_URL` in Grafana has:

      ```bash
      # When Grafana is opened on https://localhost/grafana
      https://localhost/mediamtx/

      # When Grafana is opened on https://<HOST_IP>/grafana
      https://<HOST_IP>/mediamtx/
      ```

## Troubleshooting Helm deployments

1. **Deploy with Intel GPU K8S Extension on Open Edge Platform**

   If you're deploying a GPU based pipeline (example: with VA-API elements
   like `vapostproc`, `vah264dec` etc., and/or with `device=GPU` in `gvadetect`
   in `config.json`) with Intel GPU k8s Extension on Open Edge Platform,
   ensure to set the following details in the file `helm/values.yaml`
   appropriately in order to utilize the underlying GPU.

   ```sh
   gpu:
     enabled: true
     type: "gpu.intel.com/i915"
     count: 1
   ```

2. **`dlstreamer-pipeline-server` pod shows `CreateContainerError`**

   - **Issue**: The `dlstreamer-pipeline-server` pod fails to start and shows
     `CreateContainerError`. This issue is seen only on environments using the
     `docker://` container runtime.
   - **Check Container Runtime**: Run the following command to check which
     container runtime is being used:

     ```bash
     kubectl get nodes -o wide
     ```

     Inspect the `CONTAINER-RUNTIME` column to check if the node is using the
     `docker://` runtime.

   - **Fix**: Run the following command to configure the Intel GPU device plugin
     for container runtime compatibility:

     ```bash
     kubectl patch ds intel-gpu-plugin -n intel-device-plugins --type='json' \
       -p='[{"op": "add", "path": "/spec/template/spec/containers/0/args/-", "value": "-bypath=none"}]'
     ```

     Restart the Helm Deployment once this fix is implemented.