Merge branch 'main' into cicd/metroapps_workflows

Author: sowmiar1

manufacturing-ai-suite/industrial-edge-insights-time-series/Makefile

@@ -51,14 +51,6 @@ build_copyleft_sources:
 	@echo "Building Docker containers including copyleft licensed sources..."
 	$(DOCKER_COMPOSE) build --build-arg COPYLEFT_SOURCES=true;
 
-# This section generates an SSL certificate for secure communication.
-.PHONY: generated_ssl_certs_nginx
-generated_ssl_certs_nginx:
-	@echo "Generating SSL certificates for Nginx..."
-	@if [ -d "./nginx/ssl" ]; then rm -rf ./nginx/ssl; fi
-	@mkdir -p ./nginx/ssl
-	@openssl req -x509 -nodes -days ${DAYS} -${SHA_ALGO} -newkey rsa:${KEY_LENGTH} -keyout ./nginx/ssl/key.pem -out ./nginx/ssl/cert.pem -subj "/CN=localhost"
-	@chmod 644 ./nginx/ssl/key.pem ./nginx/ssl/cert.pem
 # Check if multiple particular variables in .env are assigned with values
 .PHONY: check_env_variables
 check_env_variables:
@@ -121,7 +113,7 @@ check_env_variables:
 	done
 
 .PHONY: up_mqtt_ingestion
-up_mqtt_ingestion: check_env_variables down generated_ssl_certs_nginx
+up_mqtt_ingestion: check_env_variables down
 	@export TELEGRAF_INPUT_PLUGIN=$$(if [ $(INCLUDE) = 'validation' ]; then echo "mqtt_consumer:net:cpu:disk:docker:diskio:kernel:mem:processes:swap:system"; else echo "mqtt_consumer"; fi); \
 	echo "Starting Docker containers..."; \
 	if [ $(INCLUDE) = 'validation' ]; then \
@@ -132,7 +124,7 @@ up_mqtt_ingestion: check_env_variables down generated_ssl_certs_nginx
 
 # Run Docker containers
 .PHONY: up_opcua_ingestion
-up_opcua_ingestion: check_env_variables down generated_ssl_certs_nginx
+up_opcua_ingestion: check_env_variables down
 	@export TELEGRAF_INPUT_PLUGIN=$$(if [ $(INCLUDE) = 'validation' ]; then echo "opcua:net:cpu:disk:docker:diskio:kernel:mem:processes:swap:system"; else echo "opcua"; fi); \
 	echo "Starting Docker containers..."; \
 	if [ $(INCLUDE) = 'validation' ]; then \
@@ -206,6 +198,8 @@ gen_helm_charts:
 	@cp -f grafana/entrypoint.sh helm/grafana_entrypoint.sh
 	@cp -f apps/${SAMPLE_APP}/time-series-analytics-config/config.json helm/
 	@cp -f telegraf/entrypoint.sh helm/telegraf_entrypoint.sh
+	@cp -f nginx/nginx-cert-gen.sh helm/nginx-cert-gen.sh
+	@cp -f nginx/nginx.conf helm/nginx.conf
 	@sed -i "s/name: .*/name: ${SAMPLE_APP}-sample-app/" "helm/Chart.yaml"
 	@sed -i "s/SAMPLE_APP: .*/SAMPLE_APP: ${SAMPLE_APP}/" "helm/values.yaml"
 	@echo "Helm packages generated"

manufacturing-ai-suite/industrial-edge-insights-time-series/docker-compose.yml

@@ -349,7 +349,7 @@ services:
       - "1883:1883" # MQTT TCP Proxy
     volumes:
       - ./nginx/nginx.conf:/opt/bitnami/nginx/conf/nginx.conf:ro
-      - ./nginx/ssl:/opt/bitnami/nginx/conf/bitnami/certs:ro
+      - ./nginx/nginx-cert-gen.sh:/docker-entrypoint-initdb.d/nginx-cert-gen.sh:ro
     networks:
       - timeseries_network
     depends_on:

manufacturing-ai-suite/industrial-edge-insights-time-series/docs/user-guide/get-started.md

@@ -211,7 +211,7 @@ make status
 
     - Use link `https://<host_ip>:3000/` to launch Grafana from browser (preferably, chrome browser)
 
-      > **Note**: Use link `http://<host_ip>:30001` to launch Grafana from browser (preferably, chrome browser) for the helm deployment
+      > **Note**: Use link `https://<host_ip>:30001` to launch Grafana from browser (preferably, chrome browser) for the helm deployment
 
     - Login to the Grafana with values set for `VISUALIZER_GRAFANA_USER` and `VISUALIZER_GRAFANA_PASSWORD`
       in `.env` file and select **Wind Turbine Dashboard**.

manufacturing-ai-suite/industrial-edge-insights-time-series/docs/user-guide/how-to-configure-alerts.md

@@ -76,7 +76,7 @@ data0
         .crit(lambda: "anomaly_status" > 0)
         .message('Anomaly detected: Wind Speed: {{ index .Fields "wind_speed" }}, Grid Active Power: {{ index .Fields "grid_active_power" }}, Anomaly Status: {{ index .Fields "anomaly_status" }}')
         .noRecoveries()
-        .post('https://localhost:3000/ts-api/opcua_alerts')
+        .post('http://localhost:5000/opcua_alerts')
         .timeout(30s)
 ```
 > **Note**:
@@ -188,23 +188,24 @@ Configure the tick script by following [these instructions](#1-configure-opc-ua-
 Copy the TICK script using the following command:
 
 ```sh
-cd edge-ai-suites/manufacturing-ai-suite/wind-turbine-anomaly-detection # path relative to git clone folder
+cd edge-ai-suites/manufacturing-ai-suite/industrial-edge-insights-time-series/apps/wind-turbine-anomaly-detection # path relative to git clone folder
 cd time-series-analytics-config
-mkdir -p windturbine_anomaly_detector
-cp -r models tick_scripts udfs windturbine_anomaly_detector/.
+export SAMPLE_APP="wind-turbine-anomaly-detection"
+mkdir -p $SAMPLE_APP
+cp -r models tick_scripts udfs $SAMPLE_APP/.
 
 POD_NAME=$(kubectl get pods -n ts-sample-app -o jsonpath='{.items[*].metadata.name}' | tr ' ' '\n' | grep deployment-time-series-analytics-microservice | head -n 1)
 
-kubectl cp windturbine_anomaly_detector $POD_NAME:/tmp/ -n ts-sample-app
+kubectl cp $SAMPLE_APP $POD_NAME:/tmp/ -n ts-sample-app
 ```
 
 3. Configuring OPC-UA Alert in config.json
 
 Make the following REST API call to the Time Series Analytics microservice. Note that the `mqtt` alerts key is replaced with the `opcua` key and its specific details:
 
 ```sh
-curl -X 'POST' \
-'http://<HOST_IP>:30002/config' \
+curl -k -X 'POST' \
+'https://<HOST_IP>:30001/ts-api/config' \
 -H 'accept: application/json' \
 -H 'Content-Type: application/json' \
 -d '{

manufacturing-ai-suite/industrial-edge-insights-time-series/docs/user-guide/how-to-configure-custom-udf.md

@@ -73,8 +73,8 @@ and config.json has been volume mounted for the Time Series Analytics Microservi
 
 3. Make the following REST API call to the Time Series Analytics microservice for the updated custom UDF:
     ```sh
-    curl -X 'POST' \
-    'http://<HOST_IP>:30002/config' \
+    curl -k -X 'POST' \
+    'https://<HOST_IP>:30001/ts-api/config' \
     -H 'accept: application/json' \
     -H 'Content-Type: application/json' \
     -d '{
@@ -153,11 +153,11 @@ to the Model Registry microservice.
 
 
 1. Run the following command, to update the configuration in `Time Series Analytics` microservice. 
-   Please note, the default of `<PORT>` value is `3000/ts-api` for docker compose deployment and `30002` for helm based deployment.
+   Please note, the default of `<PORT>` value is `3000` for docker compose deployment and `30001` for helm based deployment.
 
     ```bash
-    curl -X 'POST' \
-    'https://<HOST_IP>:<PORT>/config' \
+    curl -k -X 'POST' \
+    'https://<HOST_IP>:<PORT>/ts-api/config' \
     -H 'accept: application/json' \
     -H 'Content-Type: application/json' \
     -d '{

manufacturing-ai-suite/industrial-edge-insights-time-series/docs/user-guide/how-to-deploy-with-helm.md

@@ -106,7 +106,7 @@ To copy your own or existing model into Time Series Analytics Microservice in or
     cd edge-ai-suites/manufacturing-ai-suite/industrial-edge-insights-time-series/apps/wind-turbine-anomaly-detection # path relative to git clone folder
     cd time-series-analytics-config
     mkdir -p $SAMPLE_APP
-    cp -r models tick_scripts udfs $SAMPLE_APP.
+    cp -r models tick_scripts udfs $SAMPLE_APP/.
 
     POD_NAME=$(kubectl get pods -n ts-sample-app -o jsonpath='{.items[*].metadata.name}' | tr ' ' '\n' | grep deployment-time-series-analytics-microservice | head -n 1)
 
@@ -119,8 +119,8 @@ To copy your own or existing model into Time Series Analytics Microservice in or
 
 Run the following command to activate the UDF deployment package:
 ```sh
-curl -X 'GET' \
-  'http://<HOST_IP>:30002/config?restart=true' \
+curl -k -X 'GET' \
+  'https://<HOST_IP>:30001/ts-api/config?restart=true' \
   -H 'accept: application/json'
 ```
 

manufacturing-ai-suite/industrial-edge-insights-time-series/docs/user-guide/how-to-update-config.md

@@ -2,7 +2,7 @@
 
 The Time Series Analytics Microservice provides an interactive Swagger UI at `https://<host_ip>:3000/ts-api/docs`.
 
-**Note:** Use the link `http://localhost:30002/docs` to access the Swagger UI if doing a Helm-based deployment on a Kubernetes cluster.
+**Note:** Use the link `https://localhost:30001/ts-api/docs` to access the Swagger UI if doing a Helm-based deployment on a Kubernetes cluster.
 
 ## Accessing the Swagger UI
 

manufacturing-ai-suite/industrial-edge-insights-time-series/helm/templates/NOTES.txt

@@ -21,5 +21,5 @@ Verify the pod logs by executing
 
 `kubectl logs -f <NAME OF THE POD>`
 
-Access Grafana at `http://nodeip:{{ $.Values.config.grafana.ext.port }}`
+Access Grafana at `https://nodeip:{{ $.Values.config.nginx.ext.https_port }}`
 

manufacturing-ai-suite/industrial-edge-insights-time-series/helm/templates/broker.yaml

@@ -15,9 +15,7 @@ spec:
     app: ia-mqtt-broker
   ports:
     - name: broker-port
-      port: {{ .Values.config.mqttbroker.int.port }}
-      targetPort: {{ .Values.config.mqttbroker.int.port }}
-      nodePort: {{ .Values.config.mqttbroker.ext.port }}
+      port: {{ .Values.config.mqttbroker.mqttbroker_port }}
 ---
 apiVersion: apps/v1
 kind: Deployment

manufacturing-ai-suite/industrial-edge-insights-time-series/helm/templates/grafana.yaml

@@ -12,30 +12,28 @@ metadata:
 spec:
   type: NodePort
   selector:
-    app: grafana
+    app: ia-grafana
   ports:
   - name: grafana-port
-    port: {{ $.Values.config.grafana.int.port }}
-    targetPort: {{ $.Values.config.grafana.int.port }}
-    nodePort: {{ $.Values.config.grafana.ext.port }}
+    port: {{ $.Values.config.grafana.grafana_port }}
 
 ---
 apiVersion: apps/v1
 kind: Deployment
 metadata: 
   labels:
-    app: grafana
+    app: ia-grafana
   name: deployment-grafana
   namespace: {{ $.Values.namespace }}
 
 spec:
   selector:
     matchLabels:
-      app: grafana
+      app: ia-grafana
   template:
     metadata:
       labels:
-        app: grafana
+        app: ia-grafana
     spec:
       {{- if and $.Values.DOCKER_USERNAME $.Values.DOCKER_PASSWORD }}
       imagePullSecrets: