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+1. Get the tensorflow serving URL by running these commands:
+{{- if .Values.ingress.enabled }}
+{{- range $host := .Values.ingress.hosts }}
+ {{- range $.Values.ingress.paths }}
+ http{{ if $.Values.ingress.tls }}s{{ end }}://{{ $host }}{{ . }}
+ {{- end }}
+{{- end }}
+{{- else if contains "NodePort" .Values.service.type }}
+ export NODE_PORT=$(kubectl get --namespace {{ .Release.Namespace }} -o jsonpath="{.spec.ports[0].nodePort}" services {{ include "tf-serving.fullname" . }})
+ export NODE_IP=$(kubectl get nodes --namespace {{ .Release.Namespace }} -o jsonpath="{.items[0].status.addresses[0].address}")
+ echo http://$NODE_IP:$NODE_PORT
+{{- else if contains "LoadBalancer" .Values.service.type }}
+ NOTE: It may take a few minutes for the LoadBalancer IP to be available.
+ You can watch the status of by running 'kubectl get svc -w {{ include "tf-serving.fullname" . }}'
+ export SERVICE_IP=$(kubectl get svc --namespace {{ .Release.Namespace }} {{ include "tf-serving.fullname" . }} -o jsonpath='{.status.loadBalancer.ingress[0].ip}')
+ echo http://$SERVICE_IP:{{ .Values.service.port }}
+{{- else if contains "ClusterIP" .Values.service.type }}
+ export SVC_NAME=$(kubectl get svc --namespace {{ .Release.Namespace }} -l "app={{ include "tf-serving.name" . }},modelName={{ .Values.modelName }},release={{ .Release.Name }}" -o jsonpath="{.items[0].metadata.name}")
+ kubectl port-forward svc/$SVC_NAME 8500
+{{- end }}