Merge pull request Azure#521 from Azure/canary

Canary

Author: likamrat

docs/azure_jumpstart_ag/contoso_motors/arc_monitoring_servers/img/arcserverskubernetesclusters_inventoryworkbook.png renamed to archive/contoso_motors_old/arc_monitoring_servers_old/img/arcserverskubernetesclusters_inventoryworkbook.png

@@ -101,15 +101,15 @@ The second Azure Workbook functions as an inventory report detailing the various
 
 - The second and third inventories list your **Arc-enabled servers** and your **Arc-enabled Kubernetes clusters**. It provides information about the status, Arc agent version, the operating system, location, and the number of compliant and non-compliant policies.
 
-  ![Screenshot of inventory workbook arc servers and kubernetes clusters](./img/arcserverskubernetesclusters_inventoryworkbook.png)
+  ![Screenshot of inventory workbook arc servers and Kubernetes clusters](./img/arcserverskubernetesclusters_inventoryworkbook.png)
 
 - There is also an inventory for checking the **Updates Data** of the servers:
 
   ![Screenshot of inventory workbook updates data](./img/updatesdata_inventoryworkbook.png)
 
 - The last inventory will list any **Defender for Cloud active alerts**:
 
-  ![Screenshot of inventory workbook arc servers and kubernetes clusters](./img/defenderalerts_inventoryworkbook.png)
+  ![Screenshot of inventory workbook arc servers and Kubernetes clusters](./img/defenderalerts_inventoryworkbook.png)
 
 ## Next steps
 

docs/azure_jumpstart_ag/contoso_motors/arc_monitoring_servers/img/azure_monitor_initiative.png renamed to archive/contoso_motors_old/arc_monitoring_servers_old/img/azure_monitor_initiative.png

@@ -3,7 +3,7 @@ type: docs
 weight: 3
 linkTitle: "Contoso Motors"
 description: >-
-  Learn how Contoso Motors, a leading global automobile manufacturer, implements an AI-enhanced cloud-to-edge strategy with Azure Arc, IoT services, AKS hybrid, artificial intelligence, software distribution and data pipelines.
+  Learn how Contoso Motors, a leading global automobile manufacturer, implements an AI-enhanced cloud-to-edge strategy with Azure Arc, IoT services, Rancher K3s, artificial intelligence, software distribution and data pipelines.
 ---
 
 ## Overview
@@ -42,12 +42,11 @@ To get started with the "Contoso Motors" Jumpstart Agora scenario, we provided y
 | **Guide**  | **Contoso Motors service or platform** | **Technology stack** |
 |----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------|
 | [Deployment guide](../contoso_motors/deployment/) | Not applicable | Not applicable |
-| [Data pipeline and reporting across cloud and edge](../contoso_motors/data_opc/) | Operational technology (OT) | Azure IoT Operations, Azure Data Explorer, MQTT, Event Grid, Event Hub, AKS Edge Essentials, InfluxDB, MQTT simulators |
-| [Web UI and AI Inference flow](../contoso_motors/ai_inferencing/) | Operational technology (OT) | OpenVINO™ Open Model Zoo,Yolo8, OpenVINO™ Model Server (OVMS), AKS Edge Essentials, RTSP, Flask, OpenCV  |
-| [Welding defect scenario using OpenVINO™ and Kubernetes](../contoso_motors/welding_defect/)  | Welding monitoring  | RTSP simulator, OpenVINO™ Model Server (OVMS), AKS Edge Essentials, Flask, OpenCV  |
-| [Enabling AI at the edge to enhance workers safety](../contoso_motors/workers_safety/) | Workers safety  | RTSP simulator, OpenVINO™ Model Server (OVMS), AKS Edge Essentials, Flask, OpenCV |
-| [Infrastructure observability for Kubernetes and Arc-enabled Kubernetes](../contoso_motors/k8s_infra_observability/) | Infrastructure | Arc-enabled Kubernetes, AKS Edge Essentials, Prometheus, Grafana  |
-| [Infrastructure observability for Arc-enabled servers using Azure Monitor](../contoso_motors/arc_monitoring_servers/) |Infrastructure   | Arc-enabled servers, Azure Monitor |
+| [Data pipeline and reporting across cloud and edge](../contoso_motors/data_opc/) | Operational technology (OT) | Azure IoT Operations, Azure Data Explorer, MQTT, Event Grid, Event Hub, Rancher K3s, InfluxDB, MQTT simulators |
+| [Web UI and AI Inference flow](../contoso_motors/ai_inferencing/) | Operational technology (OT) | OpenVINO™ Open Model Zoo,Yolo8, OpenVINO™ Model Server (OVMS), Rancher K3s, RTSP, Flask, OpenCV  |
+| [Welding defect scenario using OpenVINO™ and Kubernetes](../contoso_motors/welding_defect/)  | Welding monitoring  | RTSP simulator, OpenVINO™ Model Server (OVMS), Rancher K3s, Flask, OpenCV  |
+| [Enabling AI at the edge to enhance workers safety](../contoso_motors/workers_safety/) | Workers safety  | RTSP simulator, OpenVINO™ Model Server (OVMS), Rancher K3s, Flask, OpenCV |
+| [Infrastructure observability for Kubernetes and Arc-enabled Kubernetes](../contoso_motors/k8s_infra_observability/) | Infrastructure | Arc-enabled Kubernetes, Rancher K3s, Prometheus, Grafana  |
 | [Cleanup deployment](../contoso_motors/cleanup/) | Not applicable | Not applicable |
 | [Troubleshooting](../contoso_motors/troubleshooting/) | Not applicable  | Not applicable |
 | [Frequently asked questions (FAQ)](../../faq/) | Not applicable  | Not applicable  |

docs/azure_jumpstart_ag/contoso_motors/arc_monitoring_servers/img/click_inventoryworkbook.png renamed to archive/contoso_motors_old/arc_monitoring_servers_old/img/click_inventoryworkbook.png

@@ -9,7 +9,7 @@ serviceOrPlatform: INFRASTRUCTURE
 technologyStack:
   - AI
   - OpenVINO™
-  - AKS EDGE ESSENTIALS
+  - Rancher K3s
   - OpenVINO™ MODEL SERVER
   - RTSP
 ---

docs/azure_jumpstart_ag/contoso_motors/arc_monitoring_servers/img/click_osworkbook.png renamed to archive/contoso_motors_old/arc_monitoring_servers_old/img/click_osworkbook.png

@@ -1,6 +1,6 @@
 ---
 type: docs
-weight: 8
+weight: 7
 title: Cleanup
 linkTitle: Cleanup
 ---

docs/azure_jumpstart_ag/contoso_motors/arc_monitoring_servers/img/cpuusage_osworkbook.png renamed to archive/contoso_motors_old/arc_monitoring_servers_old/img/cpuusage_osworkbook.png

@@ -7,10 +7,9 @@ summary: |
     Infrastructure observability plays a crucial role in the success of Contoso Motors' cloud to edge strategy. By implementing infrastructure observability, Contoso gains comprehensive monitoring and visualization capabilities for their Kubernetes and Arc-enabled Kubernetes environments. This empowers them to proactively monitor the health and performance of their infrastructure, identify potential issues, and make data-driven decisions to optimize their operations. With infrastructure observability, Contoso can ensure that their cloud and edge infrastructure remain reliable, efficient, and resilient, enabling them to deliver exceptional customer experiences.
 serviceOrPlatform: INFRASTRUCTURE
 technologyStack:
-  - AKS
   - PROMETHEUS
   - GRAFANA
-  - AKS EDGE ESSENTIALS
+  - Rancher K3s
 ---
 
 # Kubernetes infrastructure observability
@@ -27,7 +26,7 @@ By leveraging Prometheus and Grafana for infrastructure observability, Contoso e
 
 The observability infrastructure stack architecture leverages the [Kube Prometheus Stack](https://github.com/prometheus-community/helm-charts/tree/main/charts/kube-prometheus-stack). This stack is a collection of Kubernetes manifests, Grafana dashboards, and Prometheus rules that are used to set up and configure monitoring for Kubernetes clusters.
 
-The manufacturing plants deploy Prometheus instances, which periodically scrape metrics from the AKS edge essentials cluster. A Grafana instance is set up separately to centralize monitoring and visualization. The Prometheus instances send their metrics data to this central Grafana instance. Grafana dashboards are configured to display relevant metrics, allowing operators and administrators to monitor the health and performance of the entire infrastructure.
+The manufacturing plants deploy Prometheus instances, which periodically scrape metrics from the Rancher K3s cluster. A Grafana instance is set up separately to centralize monitoring and visualization. The Prometheus instances send their metrics data to this central Grafana instance. Grafana dashboards are configured to display relevant metrics, allowing operators and administrators to monitor the health and performance of the entire infrastructure.
 
 ![Screenshot showing Observability infrastructure stack architecture](./img/observability_technology_stack.png)
 
@@ -91,4 +90,6 @@ As an Operations team member at Contoso, you will have access to the Grafana das
 
 ## Next steps
 
-Continuing with the next Contoso Motors scenario, you can now proceed to the next guide to learn about [infrastructure observability for Arc-enabled servers using Azure Monitor](../arc_monitoring_servers/).
+<!-- Continuing with the next Contoso Motors scenario, you can now proceed to the next guide to learn about [infrastructure observability for Arc-enabled servers using Azure Monitor](../arc_monitoring_servers/). -->
+
+Now that you have successfully completed all of the Contoso Motors scenarios, continue to the next step to learn how to [cleanup the deployment](../cleanup/).

docs/azure_jumpstart_ag/contoso_motors/arc_monitoring_servers/img/dcr_datasources.png renamed to archive/contoso_motors_old/arc_monitoring_servers_old/img/dcr_datasources.png

@@ -1,6 +1,6 @@
 ---
 type: docs
-weight: 9
+weight: 8
 title: Troubleshooting
 linkTitle: Troubleshooting
 ---
@@ -39,7 +39,7 @@ Occasionally, you may need to review log output from scripts that run on the _Ag
 | _C:\Ag\Logs\Bootstrap.log_ | Output from the initial bootstrapping script that runs on _Ag-VM-Client_. |
 | _C:\Ag\Logs\ClusterSecrets.log_ | Output of secret creation on Kubernetes clusters. |
 | _C:\Ag\Logs\GitOps-Ag-*.log_ | Output of scripts that collect GitOps logs on the remote Kubernetes clusters. |
-| _C:\Ag\Logs\L1AKSInfra.log_ | Output of scripts that configure AKS Edge Essentials clusters on the nested virtual machines. |
+| _C:\Ag\Logs\installK3s-Ag-K3s*.log_ | Output of scripts that configure the Rancher K3s clusters. |
 | _C:\Ag\Logs\Observability.log_ | Output from the script that configures observability components of the solution. |
 | _C:\Ag\Logs\Tools.log_ | Output from the tasks that set up developer tools on _Ag-VM-Client_. |
 

docs/azure_jumpstart_ag/contoso_motors/arc_monitoring_servers/img/dcr_resources.png renamed to archive/contoso_motors_old/arc_monitoring_servers_old/img/dcr_resources.png

@@ -7,10 +7,9 @@ summary: |
     The Welding Defect page provides an overview of the welding defect scenario in the Contoso Motors solution. It describes the architecture and flow of information for detecting and classifying welding defects using AI. The page also explains the steps involved in the welding defect inference process, including UI selection, RTSP video simulation, frame capturing, image pre-processing/inferencing, and post-processing/rendering.
 serviceOrPlatform: Manufacturing
 technologyStack:
-  - AKS
   - OpenVINO™
   - AI
-  - AKS EDGE ESSENTIALS
+  - Rancher K3s
   - RTSP
 ---
 

docs/azure_jumpstart_ag/contoso_motors/arc_monitoring_servers/img/dcr_vmi.png renamed to archive/contoso_motors_old/arc_monitoring_servers_old/img/dcr_vmi.png

@@ -7,10 +7,9 @@ summary: |
     The enabling AI at the edge to enhance workers safety page provides an overview of how Contoso Motors uses AI to ensure workers' safety by detecting workers with no helmets on the factory floor. It describes the architecture and flow of information for detecting and classifying helmet adherence using AI. The page also explains the steps involved in the inference process, including UI selection, RTSP video simulation, frame capturing, image pre-processing/inferencing, and post-processing/rendering.
 serviceOrPlatform: Manufacturing
 technologyStack:
-  - AKS
   - OpenVINO™
   - AI
-  - AKS EDGE ESSENTIALS
+  - Rancher K3s
   - RTSP
 ---