C4W2 Graded Lab: Autoscaling TensorFlow model deployments with TF Serving and Kubernetes - Task5

Task 5. Creating TensorFlow Serving deployment

Takes a lot of time: student_02_b65ce1592149@cloudshell:~/tfserving-gke (qwiklabs-gcp-01-37d10d0eaa68)$ kubectl get deployments
NAME READY UP-TO-DATE AVAILABLE AGE
image-classifier 0/1 1 0 17m

Could this be correct. In the ungraded lab before, I had this step on my local machine within 70sec?


Bildschirmfoto vom 2023-01-08 13-27-30

Please get in touch with qwiklabs help to resolve infrastructure issues.
I don’t recall waiting for 17 minutes.

Problem solved:
In Task 5 you have to change configmap.yaml. Therefore:
cd tf_serving
nano configmap.yaml
then delete entry and copy this part:
apiVersion: v1
kind: ConfigMap
metadata:
name: tfserving-configs
data:
MODEL_NAME: image_classifier
MODEL_PATH: **gs://qwiklabs-gcp-03-4b91a600a7a2-**bucket/resnet_101

→ change the bold with your project ID, save and proceed, It will work,