timeseries, multimodal: Updated docs

Changes:
 1.docs - Updated docs for udf upload
 2.helm - Removed the config.json vol mount

Signed-off-by: Pooja Kumbharkar <pooja.kumbharkar@intel.com>

Author: pooja-intel

manufacturing-ai-suite/industrial-edge-insights-multimodal/Makefile

@@ -6,6 +6,7 @@
 
 INCLUDE ?= default_INCLUDE
 HELM_REGISTRY = oci://registry-1.docker.io/intel
+MAKEFLAGS += --no-print-directory
 
 DOCKER_COMPOSE_FILE = ./docker-compose.yml
 DOCKER_COMPOSE_VALIDATION_FILE=./docker-compose-validation.override.yml
@@ -126,6 +127,22 @@ check_env_variables:
 		esac; \
 	done
 
+.PHONY: wait_for_tsam
+wait_for_tsam:
+	@echo "Waiting for Time-Series Analytics microservice to be accessible..."; \
+	max_retries=30; \
+	retry=0; \
+	until [ "$$(curl -sk -o /dev/null -w '%{http_code}' https://localhost:3000/ts-api/health)" != "000" ]; do \
+		retry=$$((retry + 1)); \
+		if [ $$retry -ge $$max_retries ]; then \
+			echo "Timed out waiting for Time-Series Analytics microservice after $$max_retries attempts."; \
+			exit 1; \
+		fi; \
+		echo "  Not accessible yet (attempt $$retry/$$max_retries), retrying in 5s..."; \
+		sleep 5; \
+	done; \
+	echo "Time-Series Analytics microservice is accessible."
+
 .PHONY: upload_zip_file
 upload_zip_file:
 	@echo "Creating UDF deployment zip for weld anomaly detection..."
@@ -137,10 +154,11 @@ upload_zip_file:
 	if [ -d models ] && [ -n "$$(ls -A models 2>/dev/null)" ]; then folders="$$folders models"; fi; \
 	zip -r $$zip_file $$folders && \
 	echo "Created: $$zip_file"
+	@$(MAKE) wait_for_tsam
 	@echo "Uploading UDF deployment zip for weld anomaly detection to Time-Series Analytics microservice..."; \
 	zip_file=$(CURDIR)/configs/time-series-analytics-microservice/weld_anomaly_detector.zip; \
 	response=$$(curl -s -o /tmp/upload_response.json -w "%{http_code}" \
-		-X POST https://localhost:3000/ts-api/update_udf_deployment_package \
+		-X POST https://localhost:${GRAFANA_PORT}/ts-api/update_udf_deployment_package \
 		-F "file=@$$zip_file" \
 		-k); \
 	if [ "$$response" = "200" ]; then \
@@ -159,9 +177,10 @@ post_config:
 		echo "Error: config.json not found at $$config_file"; \
 		exit 1; \
 	fi; \
+	$(MAKE) wait_for_tsam; \
 	echo "Posting config for weld anomaly detection to Time-Series Analytics microservice..."; \
 	response=$$(curl -s -o /tmp/config_response.json -w "%{http_code}" \
-		-X POST https://localhost:3000/ts-api/config \
+		-X POST https://localhost:${GRAFANA_PORT}/ts-api/config \
 		-H 'accept: application/json' \
 		-H 'Content-Type: application/json' \
 		-d @$$config_file \
@@ -184,8 +203,6 @@ up: check_env_variables validate_host_ip down
 	else \
 		$(DOCKER_COMPOSE) up -d; \
 	fi; \
-	echo "Waiting 5 seconds before uploading UDF deployment package..."; \
-	sleep 5; \
 	$(MAKE) upload_zip_file
 
 # Status of the deployed containers
@@ -249,7 +266,6 @@ gen_helm_charts:
 	@cp -f configs/mqtt-broker/*.conf helm/
 	@cp -f configs/telegraf/config/*.conf helm/
 	@cp -f configs/telegraf/entrypoint.sh helm/telegraf_entrypoint.sh
-	@cp -f configs/time-series-analytics-microservice/config.json helm/
 	@cp -f configs/nginx/nginx-cert-gen.sh helm/nginx-cert-gen.sh
 	@cp -f configs/nginx/nginx.conf helm/nginx.conf
 	@cp -f configs/dlstreamer-pipeline-server/config.json helm/dlstreamer-pipeline-server.json

manufacturing-ai-suite/industrial-edge-insights-multimodal/docs/user-guide/get-started/deploy-with-helm.md

@@ -133,16 +133,14 @@ this sample application in Kubernetes environment:
            - weld_anomaly_detector.py
    ```
 
-2. Copy your new UDF package to the `time-series-analytics-microservice` pod:
+2. Upload your new UDF package to the `time-series-analytics-microservice` pod:
 
    ```bash
    cd edge-ai-suites/manufacturing-ai-suite/industrial-edge-insights-multimodal/configs/time-series-analytics-microservice # path relative to git clone folder
-   mkdir -p weld_anomaly_detector
-   cp -r models tick_scripts udfs weld_anomaly_detector/.
+   rm -f weld_anomaly_detector.zip
+   zip -r weld_anomaly_detector udfs/ models/ tick_scripts/
 
-   POD_NAME=$(kubectl get pods -n multimodal-sample-app -o jsonpath='{.items[*].metadata.name}' | tr ' ' '\n' | grep deployment-time-series-analytics-microservice | head -n 1)
-
-   kubectl cp weld_anomaly_detector $POD_NAME:/tmp/ -n multimodal-sample-app
+   curl -X POST https://localhost:30001/ts-api/update_udf_deployment_package -F "file=@weld_anomaly_detector.zip" -k
    ```
 
 > **Note:**
@@ -189,9 +187,9 @@ curl -k https://localhost:30001/dsps-api/pipelines/user_defined_pipelines/weld_d
 Run the following command to activate the UDF deployment package:
 
 ```bash
-curl -k -X 'GET' \
-'https://localhost:30001/ts-api/config?restart=true' \
--H 'accept: application/json'
+cd edge-ai-suites/manufacturing-ai-suite/industrial-edge-insights-multimodal/configs/time-series-analytics-microservice
+
+curl -s -X POST https://localhost:30001/ts-api/config   -H 'accept: application/json'   -H 'Content-Type: application/json'   -d @config.json   -k
 ```
 
 ## Step 6: Verify the Results

manufacturing-ai-suite/industrial-edge-insights-multimodal/helm/templates/provision-configmap.yaml

@@ -68,15 +68,6 @@ data:
 ---
 apiVersion: v1
 kind: ConfigMap
-metadata:
-  namespace: {{ .Values.namespace }}
-  name: time-series-analytics-microservice-config
-data:
-  config.json: |-
-{{ .Files.Get "config.json" | indent 4 }}
----
-apiVersion: v1
-kind: ConfigMap
 metadata:
   namespace: {{ .Values.namespace }}
   name: grafana-dashboard-yml

manufacturing-ai-suite/industrial-edge-insights-multimodal/helm/templates/time-series-analytics-microservice.yaml

@@ -70,9 +70,6 @@ spec:
         volumeMounts:
         - name: vol-temp-time-series-analytics-microservice
           mountPath: /tmp
-        - name: time-series-analytics-microservice-config
-          mountPath: /app/config.json
-          subPath: config.json
         - name: dev-dri
           mountPath: /dev/dri
           readOnly: true # Reduce risk while preserving access to GPU/NPU devices
@@ -124,9 +121,6 @@ spec:
       volumes:
       - name: vol-temp-time-series-analytics-microservice
         emptyDir: {}
-      - name: time-series-analytics-microservice-config
-        configMap:
-          name: time-series-analytics-microservice-config
       - name: dev-dri
         hostPath:
           path: /dev/dri

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

@@ -7,6 +7,7 @@
 DEFAULT_SAMPLE_APP := wind-turbine-anomaly-detection
 SAMPLE_APP_LIST := wind-turbine-anomaly-detection weld-anomaly-detection
 HELM_REGISTRY := oci://registry-1.docker.io/intel
+MAKEFLAGS += --no-print-directory
 
 ifdef app
 ifeq ($(filter $(app),$(SAMPLE_APP_LIST)),)
@@ -117,6 +118,22 @@ check_env_variables:
 		esac; \
 	done
 
+.PHONY: wait_for_tsam
+wait_for_tsam:
+	@echo "Waiting for Time-Series Analytics microservice to be accessible..."; \
+	max_retries=30; \
+	retry=0; \
+	until [ "$$(curl -sk -o /dev/null -w '%{http_code}' https://localhost:3000/ts-api/health)" != "000" ]; do \
+		retry=$$((retry + 1)); \
+		if [ $$retry -ge $$max_retries ]; then \
+			echo "Timed out waiting for Time-Series Analytics microservice after $$max_retries attempts."; \
+			exit 1; \
+		fi; \
+		echo "  Not accessible yet (attempt $$retry/$$max_retries), retrying in 5s..."; \
+		sleep 5; \
+	done; \
+	echo "Time-Series Analytics microservice is accessible."
+
 .PHONY: upload_zip_file
 upload_zip_file:
 	@echo "Creating UDF deployment zip for $(SAMPLE_APP)..."
@@ -128,10 +145,11 @@ upload_zip_file:
 	if [ -d models ] && [ -n "$$(ls -A models 2>/dev/null)" ]; then folders="$$folders models"; fi; \
 	zip -r $$zip_file $$folders && \
 	echo "Created: $$zip_file"
+	@$(MAKE) wait_for_tsam
 	@echo "Uploading UDF deployment zip for $(SAMPLE_APP) to Time-Series Analytics microservice..."; \
 	zip_file=$(CURDIR)/apps/$(SAMPLE_APP)/time-series-analytics-config/$(SAMPLE_APP).zip; \
 	response=$$(curl -s -o /tmp/upload_response.json -w "%{http_code}" \
-		-X POST https://localhost:3000/ts-api/update_udf_deployment_package \
+		-X POST https://localhost:${GRAFANA_PORT}/ts-api/update_udf_deployment_package \
 		-F "file=@$$zip_file" \
 		-k); \
 	if [ "$$response" = "200" ]; then \
@@ -150,9 +168,10 @@ post_config:
 		echo "Error: config.json not found at $$config_file"; \
 		exit 1; \
 	fi; \
+	$(MAKE) wait_for_tsam; \
 	echo "Posting config for $(SAMPLE_APP) to Time-Series Analytics microservice..."; \
 	response=$$(curl -s -o /tmp/config_response.json -w "%{http_code}" \
-		-X POST https://localhost:3000/ts-api/config \
+		-X POST https://localhost:${GRAFANA_PORT}/ts-api/config \
 		-H 'accept: application/json' \
 		-H 'Content-Type: application/json' \
 		-d @$$config_file \
@@ -186,8 +205,6 @@ up_mqtt_ingestion: check_env_variables down
 		done; \
 		$(DOCKER_COMPOSE) up --scale ia-opcua-server=0 -d $(shell $(DOCKER_COMPOSE) config --services | grep -v ia-mqtt-publisher); \
 	fi; \
-	echo "Waiting 5 seconds before uploading UDF deployment package..."; \
-	sleep 5; \
 	$(MAKE) upload_zip_file app=$(SAMPLE_APP);
 
 # Run Docker containers
@@ -209,8 +226,6 @@ up_opcua_ingestion: check_env_variables down
 	else \
 		$(DOCKER_COMPOSE) up --scale ia-opcua-server=$(num_of_streams) --scale ia-mqtt-publisher=0 -d; \
 	fi; \
-	echo "Waiting 5 seconds before uploading UDF deployment package..."; \
-	sleep 5; \
 	$(MAKE) upload_zip_file app=$(SAMPLE_APP);
 
 
@@ -277,7 +292,6 @@ gen_helm_charts:
 	@rm -rf helm/simulation-data
 	@cp -rf apps/${SAMPLE_APP}/simulation-data helm/
 	@cp -f apps/${SAMPLE_APP}/telegraf-config/*.conf helm
-	@cp -f apps/${SAMPLE_APP}/time-series-analytics-config/config.json helm/
 	@cp -f configs/telegraf/entrypoint.sh helm/telegraf_entrypoint.sh
 	@cp -f configs/nginx/nginx-cert-gen.sh helm/nginx-cert-gen.sh
 	@cp -f configs/nginx/nginx.conf helm/nginx.conf

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

@@ -189,12 +189,10 @@ To copy your own or existing model into Time Series Analytics Microservice in or
    ```sh
    export SAMPLE_APP="wind-turbine-anomaly-detection"
    cd edge-ai-suites/manufacturing-ai-suite/industrial-edge-insights-time-series/apps/wind-turbine-anomaly-detection/time-series-analytics-config # path relative to git clone folder
-   mkdir -p $SAMPLE_APP
-   cp -r models tick_scripts udfs $SAMPLE_APP/.
+   rm -f ${SAMPLE_APP}.zip
+   zip -r ${SAMPLE_APP}.zip models/ tick_scripts/ udfs/
 
-   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 $SAMPLE_APP $POD_NAME:/tmp/ -n ts-sample-app
+   curl -X POST https://localhost:30001/ts-api/update_udf_deployment_package -F "file=@${SAMPLE_APP}.zip" -k
    ```
 
 <!--hide_directive:::
@@ -221,12 +219,10 @@ To copy your own or existing model into Time Series Analytics Microservice in or
    ```sh
    export SAMPLE_APP="weld-anomaly-detection"
    cd edge-ai-suites/manufacturing-ai-suite/industrial-edge-insights-time-series/apps/weld-anomaly-detection/time-series-analytics-config # path relative to git clone folder
-   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)
+   rm -f ${SAMPLE_APP}.zip
+   zip -r ${SAMPLE_APP}.zip models/ tick_scripts/ udfs/
 
-   kubectl cp $SAMPLE_APP $POD_NAME:/tmp/ -n ts-sample-app
+   curl -X POST https://localhost:30001/ts-api/update_udf_deployment_package -F "file=@${SAMPLE_APP}.zip" -k
    ```
 
 <!--hide_directive:::
@@ -253,9 +249,9 @@ 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 -k -X 'GET' \
-  'https://<HOST_IP>:30001/ts-api/config?restart=true' \
-  -H 'accept: application/json'
+cd edge-ai-suites/manufacturing-ai-suite/industrial-edge-insights-time-series/apps/${SAMPLE_APP}/time-series-analytics-config
+
+curl -s -X POST https://localhost:30001/ts-api/config   -H 'accept: application/json'   -H 'Content-Type: application/json'   -d @config.json   -k
 ```
 
 ## Step 6: Verify the Results

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

@@ -68,15 +68,6 @@ data:
 ---
 apiVersion: v1
 kind: ConfigMap
-metadata:
-  namespace: {{ .Values.namespace }}
-  name: time-series-analytics-microservice-config
-data:
-  config.json: |-
-{{ .Files.Get "config.json" | indent 4 }}
----
-apiVersion: v1
-kind: ConfigMap
 metadata:
   namespace: {{ .Values.namespace }}
   name: grafana-dashboard-yml

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

@@ -70,8 +70,6 @@ spec:
         volumeMounts:
         - name: vol-temp-time-series-analytics-microservice
           mountPath: /tmp
-        - name: time-series-analytics-microservice-config
-          mountPath: /app/config.json
           subPath: config.json
         - name: dev-dri
           mountPath: /dev/dri
@@ -126,9 +124,6 @@ spec:
       volumes:
       - name: vol-temp-time-series-analytics-microservice
         emptyDir: {}
-      - name: time-series-analytics-microservice-config
-        configMap:
-          name: time-series-analytics-microservice-config
       - name: dev-dri
         hostPath:
           path: /dev/dri