Deploying Machine Learning Models in Production Lab C4W2

Course Q&A Machine Learning Engineering for Production(MLOps) Deploying Machine Learning Models in Production
1

Deploying Machine Learning Models in Production

Lab: Autoscaling TensorFlow model deployments with TF Serving and Kubernetes

When I reached

kubectl apply -f tf-serving/deployment.yaml

student_01_8c27e69de9f1@cloudshell:~/tfserving-gke (qwiklabs-gcp-00-c0de18497f97)$ kubectl get deployments
NAME               READY   UP-TO-DATE   AVAILABLE   AGE
image-classifier   0/1     1            0           55m

It never become READY 1/1

Log:

2024-05-05 12:58:55.867717: E tensorflow_serving/sources/storage_path/file_system_storage_path_source.cc:365] FileSystemStoragePathSource encountered a filesystem access error: Could not find base path gs://your-bucket-name/resnet_101 for servable image_classifier with error PERMISSION_DENIED: Error executing an HTTP request: HTTP response code 403 with body '{
  "error": {
    "code": 403,
    "message": "923026286156-compute@developer.gserviceaccount.com does not have storage.objects.get access to the Google Cloud Storage object. Permission 'storage.objects.get' denied on resource (or it may not exist).",
    "errors": [
      {
        "message": "923026286156-compute@developer.gserviceaccount.com does not have storage.objects.get access to the Google Cloud Storage object. Permission 'storage.objects.get' denied on resource (or it may not exist)."'
         when reading metadata of gs://your-bucket-name/resnet_101

gs://your-bucket-name/resnet_101. <—

$ cat tf-serving/configmap.yaml 
# Copyright 2020 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#            http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

apiVersion: v1
kind: ConfigMap
metadata: # kpt-merge: /tfserving-configs
  name: tfserving-configs
  annotations:
    internal.kpt.dev/upstream-identifier: '|ConfigMap|default|tfserving-configs'
data:
  MODEL_NAME: image_classifier
  MODEL_PATH: gs://your-bucket-name/resnet_101
2

Hi. I think you need to replace the your-bucket-name strings with the bucket name you used in the lab. Hope this helps.