open-edge-platform · sgolebiewski-intel · Mar 3, 2026 · Mar 2, 2026
@@ -1 +1 @@
-Please refer [link](../docs/user-guide/how-to-guides/how-to-deploy-with-helm.md) for the helm deployment
+Please refer [link](../docs/user-guide/get-started/deploy-with-helm.md) for the helm deployment
@@ -268,8 +268,8 @@ var data = stream
 - [Kapacitor UDF Documentation](https://docs.influxdata.com/kapacitor/v1/guides/anomaly_detection/#writing-a-user-defined-function-udf)
 - [Example UDFs in Repository](https://github.com/open-edge-platform/edge-ai-suites/blob/main/manufacturing-ai-suite/industrial-edge-insights-time-series/apps/)
   - [Wind Turbine Anomaly Detection](https://github.com/open-edge-platform/edge-ai-suites/blob/main/manufacturing-ai-suite/industrial-edge-insights-time-series/apps/wind-turbine-anomaly-detection/time-series-analytics-config/udfs/windturbine_anomaly_detector.py)
-  - [Weld Anomaly Detection](https://github.com/open-edge-platform/edge-ai-suites/blob/main/manufacturing-ai-suite/industrial-edge-insights-time-series/apps/wind-turbine-anomaly-detection/time-series-analytics-config/udfs/weld_anomaly_detector.py)
+  - [Weld Anomaly Detection](https://github.com/open-edge-platform/edge-ai-suites/blob/main/manufacturing-ai-suite/industrial-edge-insights-time-series/apps/weld-anomaly-detection/time-series-analytics-config/udfs/weld_anomaly_detector.py)
 - [Kapacitor TICKscript Reference](https://docs.influxdata.com/kapacitor/v1/reference/tick/introduction/)
   - [Wind Turbine Anomaly Detection](https://github.com/open-edge-platform/edge-ai-suites/blob/main/manufacturing-ai-suite/industrial-edge-insights-time-series/apps/wind-turbine-anomaly-detection/time-series-analytics-config/tick_scripts/windturbine_anomaly_detector.tick)
-  - [Weld Anomaly Detection](https://github.com/open-edge-platform/edge-ai-suites/blob/main/manufacturing-ai-suite/industrial-edge-insights-time-series/apps/wind-turbine-anomaly-detection/time-series-analytics-config/tick_scripts/weld_anomaly_detector.tick)
+  - [Weld Anomaly Detection](https://github.com/open-edge-platform/edge-ai-suites/blob/main/manufacturing-ai-suite/industrial-edge-insights-time-series/apps/weld-anomaly-detection/time-series-analytics-config/tick_scripts/weld_anomaly_detector.tick)
 - [Configure Custom UDF Deployment](./configure-custom-udf.md)
@@ -1,3 +1,3 @@
 # Deploy using Helm Charts
 
-Please refer to [Deploy with helm](https://docs.openedgeplatform.intel.com/2025.2/edge-ai-suites/ai-suite-manufacturing/industrial-edge-insights-time-series/get-started/deploy-with-helm.html).
+Please refer to [Deploy with helm](https://docs.openedgeplatform.intel.com/dev/edge-ai-suites/ai-suite-manufacturing/industrial-edge-insights-time-series/get-started/deploy-with-helm.html).
@@ -10,7 +10,7 @@ For more details on deployment, refer to the [documentation](https://docs.opened
 ## Deploy using Kubernetes Charts
 
 ---
-For more details on deployment, refer to the [documentation](https://docs.openedgeplatform.intel.com/dev/edge-ai-suites/ai-suite-manufacturing/industrial-edge-insights-vision/pallet-defect-detection/how-to-guides/deploy-with-helm.html).
+For more details on deployment, refer to the [documentation](https://docs.openedgeplatform.intel.com/dev/edge-ai-suites/ai-suite-manufacturing/industrial-edge-insights-vision/pallet-defect-detection/get-started/deploy-with-helm.html).
 
 ## Supported versions
 

@@ -10,7 +10,7 @@ For more details on deployment, refer to the [documentation](https://docs.opened
 ## Deploy using Kubernetes Charts
 
 ---
-For more details on deployment, refer to the [documentation](https://docs.openedgeplatform.intel.com/dev/edge-ai-suites/ai-suite-manufacturing/industrial-edge-insights-vision/weld-porosity/how-to-guides/deploy-with-helm.html).
+For more details on deployment, refer to the [documentation](https://docs.openedgeplatform.intel.com/dev/edge-ai-suites/ai-suite-manufacturing/industrial-edge-insights-vision/weld-porosity/get-started/deploy-with-helm.html).
 
 ## Supported versions
 

@@ -10,7 +10,7 @@ For more details on deployment, refer to the [documentation](https://docs.opened
 ## Deploy using Kubernetes Charts
 
 ---
-For more details on deployment, refer to the [documentation](https://docs.openedgeplatform.intel.com/dev/edge-ai-suites/ai-suite-manufacturing/industrial-edge-insights-vision/worker-safety-gear-detection/how-to-deploy-using-helm-charts.html).
+For more details on deployment, refer to the [documentation](https://docs.openedgeplatform.intel.com/dev/edge-ai-suites/ai-suite-manufacturing/industrial-edge-insights-vision/worker-safety-gear-detection/get-started/deploy-with-helm.html).
 
 ## Supported versions
 

@@ -9,4 +9,4 @@ This reference application's configuration has the following environment variabl
 
 In addition to the ones above, the application also uses environment variables of following Microservice:
 
-- [DL Streamer Pipeline Server](https://docs.openedgeplatform.intel.com/dev/edge-ai-libraries/dlstreamer-pipeline-server/environment-variables.html)
+- [DL Streamer Pipeline Server](https://docs.openedgeplatform.intel.com/dev/edge-ai-libraries/dlstreamer-pipeline-server/get-started/environment-variables.html)
@@ -95,9 +95,9 @@ With this feature, during runtime, you can download a new model using the micros
 
    ![WebRTC streaming](../_assets/webrtc-streaming.png)
 
-    ### Downloading model with Model Download 
+    ### Downloading model with Model Download
 
-    At this point, user would like to restart the pipeline with a newer model. The new model can bea retrained version of the existing model or a different model altogether. We use [Model Download](https://github.com/open-edge-platform/edge-ai-libraries/blob/main/microservices/model-download/docs/user-guide/Overview.md) microservice to help download the model. It supports downloading  public models as well as geti models from a running Geti server. To learn more about it, see [here](https://github.com/open-edge-platform/edge-ai-libraries/blob/main/microservices/model-download/docs/user-guide/get-started.md).
+    At this point, user would like to restart the pipeline with a newer model. The new model can bea retrained version of the existing model or a different model altogether. We use [Model Download](https://github.com/open-edge-platform/edge-ai-libraries/blob/main/microservices/model-download/docs/user-guide/index.md) microservice to help download the model. It supports downloading  public models as well as geti models from a running Geti server. To learn more about it, see [here](https://github.com/open-edge-platform/edge-ai-libraries/blob/main/microservices/model-download/docs/user-guide/get-started.md).
 
     For our demonstration, we will assume the pallet defect detection model has been retrained and is available for downloaded from a Geti server using the Model Download service. Also, the downloaded location is accessible by the dlstreamer pipeline server. In our example, it is `/tmp/tmp-models`. The `/tmp`dir is already accessible by the sample application. If not, please add it to the `volumes` section of `dlstreamer-pipeline-server service in docker-compose file.
 
@@ -107,7 +107,7 @@ With this feature, during runtime, you can download a new model using the micros
    curl -k --location -X DELETE https://<HOST_IP>/api/pipelines/{instance_id}
    ```
 10. Start a new pipeline with this new model. Before that modify the payload.json to use this new model in `apps/pallet-defect-detection/payload.json`. Notice the model path in the payload has changed to the new model.
-    
+
     ```json
     [
         {

@@ -33,8 +33,8 @@ The following is an example of the pallet defect detection pipeline, which is in
 
 Customize the pipeline according to your needs. For details, see the following DL Streamer Pipeline Server documentation:
 
-- [Launch configurable pipelines](https://docs.openedgeplatform.intel.com/dev/edge-ai-libraries/dlstreamer-pipeline-server/how-to-launch-configurable-pipelines.html)
-- [Autostart pipelines](https://docs.openedgeplatform.intel.com/dev/edge-ai-libraries/dlstreamer-pipeline-server/how-to-autostart-pipelines.html)
+- [Launch configurable pipelines](https://docs.openedgeplatform.intel.com/dev/edge-ai-libraries/dlstreamer-pipeline-server/how-to-guides/launch-configurable-pipelines.html)
+- [Autostart pipelines](https://docs.openedgeplatform.intel.com/dev/edge-ai-libraries/dlstreamer-pipeline-server/how-to-guides/autostart-pipelines.html)
 
 ## Start the Pipeline
 >Note: If you're running multiple instances of app, ensure to provide `NGINX_HTTPS_PORT` number in the url for the app instance i.e. replace `<HOST_IP>` with `<HOST_IP>:<NGINX_HTTPS_PORT>`

@@ -9,4 +9,4 @@ This reference application's configuration has the following environment variabl
 
 In addition to the ones above, the application also uses environment variables of following Microservice:
 
-- [DL Streamer Pipeline Server](https://docs.openedgeplatform.intel.com/dev/edge-ai-libraries/dlstreamer-pipeline-server/environment-variables.html)
+- [DL Streamer Pipeline Server](https://docs.openedgeplatform.intel.com/dev/edge-ai-libraries/dlstreamer-pipeline-server/get-started/environment-variables.html)
@@ -95,9 +95,9 @@ With this feature, during runtime, you can download a new model using the micros
 
    ![WebRTC streaming](../_assets/webrtc-streaming.png)
 
-    ### Downloading model with Model Download 
+    ### Downloading model with Model Download
 
-    At this point, user would like to restart the pipeline with a newer model. The new model can bea retrained version of the existing model or a different model altogether. We use [Model Download](https://github.com/open-edge-platform/edge-ai-libraries/blob/main/microservices/model-download/docs/user-guide/Overview.md) microservice to help download the model. It supports downloading  public models as well as geti models from a running Geti server. To learn more about it, see [here](https://github.com/open-edge-platform/edge-ai-libraries/blob/main/microservices/model-download/docs/user-guide/get-started.md).
+    At this point, user would like to restart the pipeline with a newer model. The new model can bea retrained version of the existing model or a different model altogether. We use [Model Download](https://github.com/open-edge-platform/edge-ai-libraries/blob/main/microservices/model-download/docs/user-guide/index.md) microservice to help download the model. It supports downloading  public models as well as geti models from a running Geti server. To learn more about it, see [here](https://github.com/open-edge-platform/edge-ai-libraries/blob/main/microservices/model-download/docs/user-guide/get-started.md).
 
     For our demonstration, we will assume the pcb anomaly model has been retrained and is available for downloaded from a Geti server using the Model Download service. Also, the downloaded location is accessible by the dlstreamer pipeline server. In our example, it is `/tmp/tmp-models`. The `/tmp`dir is already accessible by the sample application. If not, please add it to the `volumes` section of `dlstreamer-pipeline-server service in docker-compose file.
 
@@ -107,7 +107,7 @@ With this feature, during runtime, you can download a new model using the micros
    curl -k --location -X DELETE https://<HOST_IP>/api/pipelines/{instance_id}
    ```
 10. Start a new pipeline with this new model. Before that modify the payload.json to use this new model in `apps/pcb-anomaly-detection/payload.json`. Notice the model path in the payload has changed to the new model.
-    
+
       ```json
       [
          {

@@ -33,8 +33,8 @@ The following is an example of the PCB anomaly detection pipeline, which is incl
 
 Customize the pipeline according to your needs. For details, see the following DL Streamer Pipeline Server documentation:
 
-- [Launch configurable pipelines](https://docs.openedgeplatform.intel.com/edge-ai-libraries/dlstreamer-pipeline-server/main/user-guide/how-to-launch-configurable-pipelines.html)
-- [Autostart pipelines](https://docs.openedgeplatform.intel.com/edge-ai-libraries/dlstreamer-pipeline-server/main/user-guide/how-to-autostart-pipelines.html)
+- [Launch configurable pipelines](https://docs.openedgeplatform.intel.com/edge-ai-libraries/dlstreamer-pipeline-server/main/user-guide/how-to-guides/launch-configurable-pipelines.html)
+- [Autostart pipelines](https://docs.openedgeplatform.intel.com/edge-ai-libraries/dlstreamer-pipeline-server/main/user-guide/how-to-guides/autostart-pipelines.html)
 
 ## Start the Pipeline
 

@@ -9,4 +9,4 @@ This reference application's configuration has the following environment variabl
 
 In addition to the ones above, the application also uses environment variables of following Microservice:
 
-- [DL Streamer Pipeline Server](https://docs.openedgeplatform.intel.com/dev/edge-ai-libraries/dlstreamer-pipeline-server/environment-variables.html)
+- [DL Streamer Pipeline Server](https://docs.openedgeplatform.intel.com/dev/edge-ai-libraries/dlstreamer-pipeline-server/get-started/environment-variables.html)
@@ -90,9 +90,9 @@ With this feature, during runtime, you can download a new model using the micros
 
    ![WebRTC streaming](../_assets/webrtc-streaming.png)
 
-    ### Downloading model with Model Download 
+    ### Downloading model with Model Download
 
-    At this point, user would like to restart the pipeline with a newer model. The new model can bea retrained version of the existing model or a different model altogether. We use [Model Download](https://github.com/open-edge-platform/edge-ai-libraries/blob/main/microservices/model-download/docs/user-guide/Overview.md) microservice to help download the model. It supports downloading  public models as well as geti models from a running Geti server. To learn more about it, see [here](https://github.com/open-edge-platform/edge-ai-libraries/blob/main/microservices/model-download/docs/user-guide/get-started.md).
+    At this point, user would like to restart the pipeline with a newer model. The new model can bea retrained version of the existing model or a different model altogether. We use [Model Download](https://github.com/open-edge-platform/edge-ai-libraries/blob/main/microservices/model-download/docs/user-guide/index.md) microservice to help download the model. It supports downloading  public models as well as geti models from a running Geti server. To learn more about it, see [here](https://github.com/open-edge-platform/edge-ai-libraries/blob/main/microservices/model-download/docs/user-guide/get-started.md).
 
     For our demonstration, we will assume the weld porosity model has been retrained and is available for downloaded from a Geti server using the Model Download service. Also, the downloaded location is accessible by the dlstreamer pipeline server. In our example, it is `/tmp/tmp-models`. The `/tmp`dir is already accessible by the sample application. If not, please add it to the `volumes` section of `dlstreamer-pipeline-server service in docker-compose file.
 
@@ -102,7 +102,7 @@ With this feature, during runtime, you can download a new model using the micros
    curl -k --location -X DELETE https://<HOST_IP>/api/pipelines/{instance_id}
    ```
 10. Start a new pipeline with this new model. Before that modify the payload.json to use this new model in `apps/weld-porosity/payload.json`. Notice the model path in the payload has changed to the new model.
-    
+
    ```json
    [
        {

@@ -34,8 +34,8 @@ The following is an example of the weld porosity classification pipeline, which
 
 Customize the pipeline according to your needs. For details, see the following DL Streamer Pipeline Server documentation:
 
-- [Launch configurable pipelines](https://docs.openedgeplatform.intel.com/dev/edge-ai-libraries/dlstreamer-pipeline-server/how-to-launch-configurable-pipelines.html)
-- [Autostart pipelines](https://docs.openedgeplatform.intel.com/dev/edge-ai-libraries/dlstreamer-pipeline-server/how-to-autostart-pipelines.html)
+- [Launch configurable pipelines](https://docs.openedgeplatform.intel.com/dev/edge-ai-libraries/dlstreamer-pipeline-server/how-to-guides/launch-configurable-pipelines.html)
+- [Autostart pipelines](https://docs.openedgeplatform.intel.com/dev/edge-ai-libraries/dlstreamer-pipeline-server/how-to-guides/autostart-pipelines.html)
 
 ## Start the Pipeline
 

@@ -9,5 +9,5 @@ This reference application's configuration has the following environment variabl
 
 In addition to the ones above, the application also uses environment variables of following Microservice:
 
-- [DL Streamer Pipeline Server](https://docs.openedgeplatform.intel.com/dev/edge-ai-libraries/dlstreamer-pipeline-server/environment-variables.html)
+- [DL Streamer Pipeline Server](https://docs.openedgeplatform.intel.com/dev/edge-ai-libraries/dlstreamer-pipeline-server/get-started/environment-variables.html)
 
@@ -82,9 +82,9 @@ With this feature, during runtime, you can download a new model using the micros
 
     ![WebRTC streaming](../_assets/webrtc-streaming.png)
 
-    ### Downloading model with Model Download 
+    ### Downloading model with Model Download
 
-    At this point, user would like to restart the pipeline with a newer model. The new model can bea retrained version of the existing model or a different model altogether. We use [Model Download](https://github.com/open-edge-platform/edge-ai-libraries/blob/main/microservices/model-download/docs/user-guide/Overview.md) microservice to help download the model. It supports downloading  public models as well as geti models from a running Geti server. To learn more about it, see [here](https://github.com/open-edge-platform/edge-ai-libraries/blob/main/microservices/model-download/docs/user-guide/get-started.md).
+    At this point, user would like to restart the pipeline with a newer model. The new model can bea retrained version of the existing model or a different model altogether. We use [Model Download](https://github.com/open-edge-platform/edge-ai-libraries/blob/main/microservices/model-download/docs/user-guide/index.md) microservice to help download the model. It supports downloading  public models as well as geti models from a running Geti server. To learn more about it, see [here](https://github.com/open-edge-platform/edge-ai-libraries/blob/main/microservices/model-download/docs/user-guide/get-started.md).
 
     For our demonstration, we will assume the worker safety gear detection model has been retrained and is available for downloaded from a Geti server using the Model Download service. Also, the downloaded location is accessible by the dlstreamer pipeline server. In our example, it is `/tmp/tmp-models`. The `/tmp`dir is already accessible by the sample application. If not, please add it to the `volumes` section of `dlstreamer-pipeline-server service in docker-compose file.
 
@@ -94,7 +94,7 @@ With this feature, during runtime, you can download a new model using the micros
    curl -k --location -X DELETE https://<HOST_IP>/api/pipelines/{instance_id}
    ```
 10. Start a new pipeline with this new model. Before that modify the payload.json to use this new model in `apps/worker-safety-gear-detection/payload.json`. Notice the model path in the payload has changed to the new model.
-    
+
     ```json
     [
         {

@@ -33,8 +33,8 @@ The following is an example of the Worker Safety Gear Detection pipeline, which
 
 Customize the pipeline according to your needs. For details, see the following DL Streamer Pipeline Server documentation:
 
-- [Launch configurable pipelines](https://docs.openedgeplatform.intel.com/dev/edge-ai-libraries/dlstreamer-pipeline-server/how-to-launch-configurable-pipelines.html)
-- [Autostart pipelines](https://docs.openedgeplatform.intel.com/dev/edge-ai-libraries/dlstreamer-pipeline-server/how-to-autostart-pipelines.html)
+- [Launch configurable pipelines](https://docs.openedgeplatform.intel.com/dev/edge-ai-libraries/dlstreamer-pipeline-server/how-to-guides/launch-configurable-pipelines.html)
+- [Autostart pipelines](https://docs.openedgeplatform.intel.com/dev/edge-ai-libraries/dlstreamer-pipeline-server/how-to-guides/autostart-pipelines.html)
 
 ## Start the Pipeline
Original file line number	Diff line number	Diff line change
		@@ -1 +1 @@
		Please refer [link](../docs/user-guide/how-to-guides/how-to-deploy-with-helm.md) for the helm deployment
		Please refer [link](../docs/user-guide/get-started/deploy-with-helm.md) for the helm deployment
Original file line number	Diff line number	Diff line change
Expand Up		@@ -9,4 +9,4 @@ This reference application's configuration has the following environment variabl

		In addition to the ones above, the application also uses environment variables of following Microservice:

		- [DL Streamer Pipeline Server](https://docs.openedgeplatform.intel.com/dev/edge-ai-libraries/dlstreamer-pipeline-server/environment-variables.html)
		- [DL Streamer Pipeline Server](https://docs.openedgeplatform.intel.com/dev/edge-ai-libraries/dlstreamer-pipeline-server/get-started/environment-variables.html)
Original file line number	Diff line number	Diff line change
Expand Up		@@ -9,5 +9,5 @@ This reference application's configuration has the following environment variabl

		In addition to the ones above, the application also uses environment variables of following Microservice:

		- [DL Streamer Pipeline Server](https://docs.openedgeplatform.intel.com/dev/edge-ai-libraries/dlstreamer-pipeline-server/environment-variables.html)
		- [DL Streamer Pipeline Server](https://docs.openedgeplatform.intel.com/dev/edge-ai-libraries/dlstreamer-pipeline-server/get-started/environment-variables.html)