feat: WeatherNext2 Initial Updates

* feat:MongoDB Voyage 3.5-Lite

* chore:apply linter

* Update voyage-3.5-lite.ipynb

Fixing MODEL_NAME

.cloud-build/execute_changed_notebooks_helper.py

@@ -365,7 +365,7 @@ def process_and_execute_notebook(
             # Use gcloud to get tail
             try:
                 result.error_message = subprocess.check_output(
-                    ["gsutil", "cat", "-r", "-1000", log_file_uri], encoding="UTF-8"
+                    ["gcloud", "storage", "cat", "--range", "-1000", log_file_uri], encoding="UTF-8"
                 )
             except Exception as error:
                 result.error_message = str(error)

.cloud-build/execute_notebook_helper.py

@@ -56,8 +56,8 @@ def execute_notebook(
     print("\n=== DOWNLOAD EXECUTED NOTEBOOK ===\n")
     print(f"Please debug the executed notebook by downloading the executed notebook:")
 
-    print("Option 1. Using gsutil. Run the following command in your terminal.")
-    print(f'\tgsutil cp "{output_file_or_uri}" .')
+    print("Option 1. Using gcloud storage. Run the following command in your terminal.")
+    print(f'\tgcloud storage cp "{output_file_or_uri}" .')
 
     print("Option 2. Using this link.")
     print(f"\thttps://storage.googleapis.com/{output_file_or_uri[5:]}")

.cloud-build/utils/NotebookProcessors.py

@@ -108,7 +108,7 @@ class VertexAIInstallProprocessor(Preprocessor):
         if "google-cloud-aiplatform" not in content:
             return content
         return (
-            f"gsutil cp {self.vertex_ai_wheel} google-cloud-aiplatform.whl\n" + 
+            f"gcloud storage cp {self.vertex_ai_wheel} google-cloud-aiplatform.whl\n" + 
             content.replace("google-cloud-aiplatform\n", "google-cloud-aiplatform.whl\n")
             .replace("google-cloud-aiplatform ", "google-cloud-aiplatform.whl ")
         )

.cloud-build/utils/util.py

@@ -15,7 +15,7 @@ def download_file(bucket_name: str, blob_name: str, destination_file: str) -> st
     remote_file_path = "".join(["gs://", "/".join([bucket_name, blob_name])])
 
     subprocess.check_output(
-        ["gsutil", "cp", remote_file_path, destination_file], encoding="UTF-8"
+        ["gcloud", "storage", "cp", remote_file_path, destination_file], encoding="UTF-8"
     )
 
     return destination_file
@@ -27,7 +27,7 @@ def upload_file(
 ) -> str:
     """Copies a local file to a GCS path"""
     subprocess.check_output(
-        ["gsutil", "cp", local_file_path, remote_file_path], encoding="UTF-8"
+        ["gcloud", "storage", "cp", local_file_path, remote_file_path], encoding="UTF-8"
     )
 
     return remote_file_path

.github/workflows/ci.yaml

@@ -7,11 +7,11 @@ jobs:
     runs-on: ubuntu-latest
     steps:
     - name: Set up Python
-      uses: actions/setup-python@v5
+      uses: actions/setup-python@v6
       with:
-        python-version: '3.x'      
+        python-version: '3.14'      
     - name: Fetch pull request branch
-      uses: actions/checkout@v4
+      uses: actions/checkout@v6
       with:
         fetch-depth: 0      
     - name: Fetch base main branch

.github/workflows/linter/Dockerfile

@@ -4,7 +4,7 @@
 # 2. To lint specific notebooks:
 # docker run -v ${PWD}:/setup/app gcr.io/python-docs-samples-tests/notebook_linter:latest notebooks/1.ipynb notebooks/2.ipynb
 
-FROM python:3.13
+FROM python:3.14
 
 WORKDIR setup
 

.github/workflows/linter/requirements.txt

@@ -2,9 +2,9 @@ git+https://github.com/tensorflow/docs
 ipython
 jupyter
 nbconvert
-black==25.1.0
-pyupgrade==3.20.0
-isort==6.0.1
+black==25.12.0
+pyupgrade==3.21.0
+isort==7.0.0
 flake8==7.3.0
 nbqa==1.9.1
 

community-content/pipeline_components/google-cloud/Vertex_AI/Models/Upload_PyTorch_model_archive/component.yaml

@@ -148,7 +148,7 @@ implementation:
 
       # Downloading the model archive from GCS
       # TODO: Fix gsutil bugs (requires project ID, has auth issues) and use gsutil instead.
-      # gsutil cp "$model_archive_uri" "$model_archive_local_path"
+      # gcloud storage cp "$model_archive_uri" "$model_archive_local_path"
       pip install google-cloud-storage
       python -c '
       import sys

community-content/pipeline_components/google-cloud/storage/download/component.yaml

@@ -24,12 +24,12 @@ implementation:
 
             # Checking whether the URI points to a single blob, a directory or a URI pattern
             # URI points to a blob when that URI does not end with slash and listing that URI only yields the same URI
-            if [[ "$uri" != */ ]] && (gsutil ls "$uri" | grep --fixed-strings --line-regexp "$uri"); then
+            if [[ "$uri" != */ ]] && (gcloud storage ls "$uri" | grep --fixed-strings --line-regexp "$uri"); then
                 mkdir -p "$(dirname "$output_path")"
-                gsutil -m cp -r "$uri" "$output_path"
+                gcloud storage cp --recursive "$uri" "$output_path"
             else
                 mkdir -p "$output_path" # When source path is a directory, gsutil requires the destination to also be a directory
-                gsutil -m rsync -r "$uri" "$output_path" # gsutil cp has different path handling than Linux cp. It always puts the source directory (name) inside the destination directory. gsutil rsync does not have that problem.
+                gcloud storage rsync --recursive "$uri" "$output_path" # gsutil cp has different path handling than Linux cp. It always puts the source directory (name) inside the destination directory. gsutil rsync does not have that problem.
             fi
         - inputValue: GCS path
         - outputPath: Data

community-content/pytorch_image_classification_distributed_data_parallel_training_with_vertex_sdk/trainer/requirements.txt

@@ -1,3 +1,3 @@
-torch==2.2.0
+torch==2.8.0
 torchvision==0.9.1
 tensorboard==2.5.0

community-content/pytorch_image_classification_single_gpu_with_vertex_sdk_and_torchserve/vertex_prediction_with_custom_torchserve_container.ipynb

@@ -110,7 +110,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls $gcs_output_uri_prefix"
+        "! gcloud storage ls $gcs_output_uri_prefix"
       ]
     },
     {
@@ -192,7 +192,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil cp -r $gcs_output_uri_prefix/model ./model_server/"
+        "! gcloud storage cp --recursive $gcs_output_uri_prefix/model ./model_server/"
       ]
     },
     {
@@ -556,7 +556,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil rm -rf $gcs_output_uri_prefix"
+        "! gcloud storage rm --recursive --continue-on-error $gcs_output_uri_prefix"
       ]
     },
     {

community-content/pytorch_image_classification_single_gpu_with_vertex_sdk_and_torchserve/vertex_training_with_custom_container.ipynb

@@ -412,7 +412,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls $gcs_output_uri_prefix"
+        "! gcloud storage ls $gcs_output_uri_prefix"
       ]
     }
   ],

community-content/pytorch_text_classification_using_vertex_sdk_and_gcloud/custom_container/scripts/train-cloud.sh

@@ -77,4 +77,4 @@ echo "After the job is completed successfully, model files will be saved at $JOB
 
 # # Verify the model was exported
 # echo "Verify the model was exported:"
-# gsutil ls ${JOB_DIR}/
+# gcloud storage ls ${JOB_DIR}/

community-content/pytorch_text_classification_using_vertex_sdk_and_gcloud/predictor/Dockerfile.serve

@@ -34,4 +34,4 @@ RUN echo "service_envelope=json\n"     "inference_address=http://0.0.0.0:${AIP_H
 USER model-server
 
 # run Torchserve HTTP serve to respond to prediction requests
-CMD ["echo", "AIP_STORAGE_URI=${AIP_STORAGE_URI}", ";",     "gsutil", "cp", "-r", "${AIP_STORAGE_URI}/${MODEL_NAME}.mar", "/home/model-server/model-store/", ";",     "ls", "-ltr", "/home/model-server/model-store/", ";",     "torchserve", "--start", "--ts-config=/home/model-server/config.properties",     "--models", "${MODEL_NAME}=${MODEL_NAME}.mar",     "--model-store", "/home/model-server/model-store"]
+CMD ["echo", "AIP_STORAGE_URI=${AIP_STORAGE_URI}", ";",     "gcloud", "storage", "cp", "--recursive", "${AIP_STORAGE_URI}/${MODEL_NAME}.mar", "/home/model-server/model-store/", ";",     "ls", "-ltr", "/home/model-server/model-store/", ";",     "torchserve", "--start", "--ts-config=/home/model-server/config.properties",     "--models", "${MODEL_NAME}=${MODEL_NAME}.mar",     "--model-store", "/home/model-server/model-store"]

community-content/pytorch_text_classification_using_vertex_sdk_and_gcloud/python_package/scripts/train-cloud.sh

@@ -67,4 +67,4 @@ echo "After the job is completed successfully, model files will be saved at $JOB
 
 # # Verify the model was exported
 # echo "Verify the model was exported:"
-# gsutil ls ${JOB_DIR}/
+# gcloud storage ls ${JOB_DIR}/

community-content/tf_agents_bandits_movie_recommendation_with_kfp_and_vertex_sdk/mlops_pipeline_tf_agents_bandits_movie_recommendation/mlops_pipeline_tf_agents_bandits_movie_recommendation.ipynb

@@ -478,8 +478,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION $BUCKET_NAME"
-      ]
+        "! gcloud storage buckets create --location $REGION $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -498,8 +497,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_NAME"
-      ]
+        "! gcloud storage ls --all-versions --long $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -582,8 +580,7 @@
       "outputs": [],
       "source": [
         "# Download the sample data into your RAW_DATA_PATH\n",
-        "! gsutil cp \"gs://cloud-samples-data/vertex-ai/community-content/tf_agents_bandits_movie_recommendation_with_kfp_and_vertex_sdk/u.data\" $RAW_DATA_PATH"
-      ]
+        "! gcloud storage cp \"gs://cloud-samples-data/vertex-ai/community-content/tf_agents_bandits_movie_recommendation_with_kfp_and_vertex_sdk/u.data\" $RAW_DATA_PATH"      ]
     },
     {
       "cell_type": "code",
@@ -1621,9 +1618,7 @@
         "! gcloud scheduler jobs delete $SIMULATOR_SCHEDULER_JOB --quiet\n",
         "\n",
         "# Delete Cloud Storage objects that were created.\n",
-        "! gsutil -m rm -r $PIPELINE_ROOT\n",
-        "! gsutil -m rm -r $TRAINING_ARTIFACTS_DIR"
-      ]
+        "! gcloud storage rm --recursive $PIPELINE_ROOT\n",        "! gcloud storage rm --recursive $TRAINING_ARTIFACTS_DIR"      ]
     }
   ],
   "metadata": {

community-content/tf_agents_bandits_movie_recommendation_with_kfp_and_vertex_sdk/step_by_step_sdk_tf_agents_bandits_movie_recommendation/step_by_step_sdk_tf_agents_bandits_movie_recommendation.ipynb

@@ -398,6 +398,7 @@
         "if not IS_GOOGLE_CLOUD_NOTEBOOK:\n",
         "    if \"google.colab\" in sys.modules:\n",
         "        from google.colab import auth as google_auth\n",
+        "\n",
         "        google_auth.authenticate_user()\n",
         "\n",
         "    # If you are running this notebook locally, replace the string below with the\n",
@@ -472,7 +473,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION $BUCKET_NAME"
+        "! gcloud storage buckets create --location $REGION $BUCKET_NAME"
       ]
     },
     {
@@ -492,7 +493,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_NAME"
+        "! gcloud storage ls --all-versions --long $BUCKET_NAME"
       ]
     },
     {
@@ -565,7 +566,7 @@
       "outputs": [],
       "source": [
         "# Copy the sample data into your DATA_PATH\n",
-        "! gsutil cp \"gs://cloud-samples-data/vertex-ai/community-content/tf_agents_bandits_movie_recommendation_with_kfp_and_vertex_sdk/u.data\"  $DATA_PATH"
+        "! gcloud storage cp \"gs://cloud-samples-data/vertex-ai/community-content/tf_agents_bandits_movie_recommendation_with_kfp_and_vertex_sdk/u.data\"  $DATA_PATH"
       ]
     },
     {
@@ -579,11 +580,15 @@
         "# Set hyperparameters.\n",
         "BATCH_SIZE = 8  # @param {type:\"integer\"} Training and prediction batch size.\n",
         "TRAINING_LOOPS = 5  # @param {type:\"integer\"} Number of training iterations.\n",
-        "STEPS_PER_LOOP = 2  # @param {type:\"integer\"} Number of driver steps per training iteration.\n",
+        "STEPS_PER_LOOP = (\n",
+        "    2  # @param {type:\"integer\"} Number of driver steps per training iteration.\n",
+        ")\n",
         "\n",
         "# Set MovieLens simulation environment parameters.\n",
         "RANK_K = 20  # @param {type:\"integer\"} Rank for matrix factorization in the MovieLens environment; also the observation dimension.\n",
-        "NUM_ACTIONS = 20  # @param {type:\"integer\"} Number of actions (movie items) to choose from.\n",
+        "NUM_ACTIONS = (\n",
+        "    20  # @param {type:\"integer\"} Number of actions (movie items) to choose from.\n",
+        ")\n",
         "PER_ARM = False  # Use the non-per-arm version of the MovieLens environment.\n",
         "\n",
         "# Set agent parameters.\n",
@@ -621,7 +626,8 @@
       "source": [
         "# Define RL environment.\n",
         "env = movielens_py_environment.MovieLensPyEnvironment(\n",
-        "    DATA_PATH, RANK_K, BATCH_SIZE, num_movies=NUM_ACTIONS, csv_delimiter=\"\\t\")\n",
+        "    DATA_PATH, RANK_K, BATCH_SIZE, num_movies=NUM_ACTIONS, csv_delimiter=\"\\t\"\n",
+        ")\n",
         "environment = tf_py_environment.TFPyEnvironment(env)\n",
         "\n",
         "# Define RL agent/algorithm.\n",
@@ -631,7 +637,8 @@
         "    tikhonov_weight=TIKHONOV_WEIGHT,\n",
         "    alpha=AGENT_ALPHA,\n",
         "    dtype=tf.float32,\n",
-        "    accepts_per_arm_features=PER_ARM)\n",
+        "    accepts_per_arm_features=PER_ARM,\n",
+        ")\n",
         "print(\"TimeStep Spec (for each batch):\\n\", agent.time_step_spec, \"\\n\")\n",
         "print(\"Action Spec (for each batch):\\n\", agent.action_spec, \"\\n\")\n",
         "print(\"Reward Spec (for each batch):\\n\", environment.reward_spec(), \"\\n\")\n",
@@ -639,7 +646,8 @@
         "# Define RL metric.\n",
         "optimal_reward_fn = functools.partial(\n",
         "    environment_utilities.compute_optimal_reward_with_movielens_environment,\n",
-        "    environment=environment)\n",
+        "    environment=environment,\n",
+        ")\n",
         "regret_metric = tf_bandit_metrics.RegretMetric(optimal_reward_fn)\n",
         "metrics = [regret_metric]"
       ]
@@ -704,35 +712,38 @@
         "    if training_data_spec_transformation_fn is None:\n",
         "        data_spec = agent.policy.trajectory_spec\n",
         "    else:\n",
-        "        data_spec = training_data_spec_transformation_fn(\n",
-        "            agent.policy.trajectory_spec)\n",
-        "    replay_buffer = trainer.get_replay_buffer(data_spec, environment.batch_size,\n",
-        "                                              steps_per_loop)\n",
+        "        data_spec = training_data_spec_transformation_fn(agent.policy.trajectory_spec)\n",
+        "    replay_buffer = trainer.get_replay_buffer(\n",
+        "        data_spec, environment.batch_size, steps_per_loop\n",
+        "    )\n",
         "\n",
         "    # `step_metric` records the number of individual rounds of bandit interaction;\n",
         "    # that is, (number of trajectories) * batch_size.\n",
         "    step_metric = tf_metrics.EnvironmentSteps()\n",
         "    metrics = [\n",
         "        tf_metrics.NumberOfEpisodes(),\n",
-        "        tf_metrics.AverageEpisodeLengthMetric(batch_size=environment.batch_size)\n",
+        "        tf_metrics.AverageEpisodeLengthMetric(batch_size=environment.batch_size),\n",
         "    ]\n",
         "    if additional_metrics:\n",
         "        metrics += additional_metrics\n",
         "\n",
         "    if isinstance(environment.reward_spec(), dict):\n",
-        "        metrics += [tf_metrics.AverageReturnMultiMetric(\n",
-        "            reward_spec=environment.reward_spec(),\n",
-        "            batch_size=environment.batch_size)]\n",
-        "    else:\n",
         "        metrics += [\n",
-        "            tf_metrics.AverageReturnMetric(batch_size=environment.batch_size)]\n",
+        "            tf_metrics.AverageReturnMultiMetric(\n",
+        "                reward_spec=environment.reward_spec(), batch_size=environment.batch_size\n",
+        "            )\n",
+        "        ]\n",
+        "    else:\n",
+        "        metrics += [tf_metrics.AverageReturnMetric(batch_size=environment.batch_size)]\n",
         "\n",
         "    # Store intermediate metric results, indexed by metric names.\n",
         "    metric_results = defaultdict(list)\n",
         "\n",
         "    if training_data_spec_transformation_fn is not None:\n",
-        "        def add_batch_fn(data): return replay_buffer.add_batch(training_data_spec_transformation_fn(data)) \n",
-        "        \n",
+        "\n",
+        "        def add_batch_fn(data):\n",
+        "            return replay_buffer.add_batch(training_data_spec_transformation_fn(data))\n",
+        "\n",
         "    else:\n",
         "        add_batch_fn = replay_buffer.add_batch\n",
         "\n",
@@ -742,10 +753,12 @@
         "        env=environment,\n",
         "        policy=agent.collect_policy,\n",
         "        num_steps=steps_per_loop * environment.batch_size,\n",
-        "        observers=observers)\n",
+        "        observers=observers,\n",
+        "    )\n",
         "\n",
         "    training_loop = trainer.get_training_loop_fn(\n",
-        "        driver, replay_buffer, agent, steps_per_loop)\n",
+        "        driver, replay_buffer, agent, steps_per_loop\n",
+        "    )\n",
         "    saver = policy_saver.PolicySaver(agent.policy)\n",
         "\n",
         "    for _ in range(training_loops):\n",
@@ -783,7 +796,8 @@
         "    environment=environment,\n",
         "    training_loops=TRAINING_LOOPS,\n",
         "    steps_per_loop=STEPS_PER_LOOP,\n",
-        "    additional_metrics=metrics)\n",
+        "    additional_metrics=metrics,\n",
+        ")\n",
         "\n",
         "tf.profiler.experimental.stop()"
       ]
@@ -1092,11 +1106,15 @@
       },
       "outputs": [],
       "source": [
-        "RUN_HYPERPARAMETER_TUNING = True  # Execute hyperparameter tuning instead of regular training.\n",
+        "RUN_HYPERPARAMETER_TUNING = (\n",
+        "    True  # Execute hyperparameter tuning instead of regular training.\n",
+        ")\n",
         "TRAIN_WITH_BEST_HYPERPARAMETERS = False  # Do not train.\n",
         "\n",
         "HPTUNING_RESULT_DIR = \"hptuning/\"  # @param {type: \"string\"} Directory to store the best hyperparameter(s) in `BUCKET_NAME` and locally (temporarily).\n",
-        "HPTUNING_RESULT_PATH = os.path.join(HPTUNING_RESULT_DIR, \"result.json\")  # @param {type: \"string\"} Path to the file containing the best hyperparameter(s)."
+        "HPTUNING_RESULT_PATH = os.path.join(\n",
+        "    HPTUNING_RESULT_DIR, \"result.json\"\n",
+        ")  # @param {type: \"string\"} Path to the file containing the best hyperparameter(s)."
       ]
     },
     {
@@ -1124,7 +1142,7 @@
         "    image_uri: str,\n",
         "    args: List[str],\n",
         "    location: str = \"us-central1\",\n",
-        "    api_endpoint: str = \"us-central1-aiplatform.googleapis.com\"\n",
+        "    api_endpoint: str = \"us-central1-aiplatform.googleapis.com\",\n",
         ") -> None:\n",
         "    \"\"\"Creates a hyperparameter tuning job using a custom container.\n",
         "\n",
@@ -1197,8 +1215,8 @@
         "\n",
         "    # Create job\n",
         "    response = client.create_hyperparameter_tuning_job(\n",
-        "        parent=parent,\n",
-        "        hyperparameter_tuning_job=hyperparameter_tuning_job)\n",
+        "        parent=parent, hyperparameter_tuning_job=hyperparameter_tuning_job\n",
+        "    )\n",
         "    job_id = response.name.split(\"/\")[-1]\n",
         "    print(\"Job ID:\", job_id)\n",
         "    print(\"Job config:\", response)\n",
@@ -1242,7 +1260,8 @@
         "    image_uri=f\"gcr.io/{PROJECT_ID}/{HPTUNING_TRAINING_CONTAINER}:latest\",\n",
         "    args=args,\n",
         "    location=REGION,\n",
-        "    api_endpoint=f\"{REGION}-aiplatform.googleapis.com\")"
+        "    api_endpoint=f\"{REGION}-aiplatform.googleapis.com\",\n",
+        ")"
       ]
     },
     {
@@ -1292,7 +1311,8 @@
         "    name = client.hyperparameter_tuning_job_path(\n",
         "        project=project,\n",
         "        location=location,\n",
-        "        hyperparameter_tuning_job=hyperparameter_tuning_job_id)\n",
+        "        hyperparameter_tuning_job=hyperparameter_tuning_job_id,\n",
+        "    )\n",
         "    response = client.get_hyperparameter_tuning_job(name=name)\n",
         "    return response"
       ]
@@ -1313,7 +1333,8 @@
         "        location=REGION,\n",
         "        api_endpoint=f\"{REGION}-aiplatform.googleapis.com\")\n",
         "    if response.state.name == 'JOB_STATE_SUCCEEDED':\n",
-        "        print(\"Job succeeded.\\nJob Time:\", response.update_time - response.create_time)\n",
+        "        print(\"Job succeeded.\n",
+        "Job Time:\", response.update_time - response.create_time)\n",
         "        trials = response.trials\n",
         "        print(\"Trials:\", trials)\n",
         "        break\n",
@@ -1348,8 +1369,8 @@
         "if trials:\n",
         "    # Dict mapping from metric names to the best metric values seen so far\n",
         "    best_objective_values = dict.fromkeys(\n",
-        "        [metric.metric_id for metric in trials[0].final_measurement.metrics],\n",
-        "        -np.inf)\n",
+        "        [metric.metric_id for metric in trials[0].final_measurement.metrics], -np.inf\n",
+        "    )\n",
         "    # Dict mapping from metric names to a list of the best combination(s) of\n",
         "    # hyperparameter(s). Each combination is a dict mapping from hyperparameter\n",
         "    # names to their values.\n",
@@ -1358,12 +1379,13 @@
         "        # `final_measurement` and `parameters` are `RepeatedComposite` objects.\n",
         "        # Reference the structure above to extract the value of your interest.\n",
         "        for metric in trial.final_measurement.metrics:\n",
-        "            params = {\n",
-        "                param.parameter_id: param.value for param in trial.parameters}\n",
+        "            params = {param.parameter_id: param.value for param in trial.parameters}\n",
         "            if metric.value > best_objective_values[metric.metric_id]:\n",
         "                best_params[metric.metric_id] = [params]\n",
         "            elif metric.value == best_objective_values[metric.metric_id]:\n",
-        "                best_params[param.parameter_id].append(params)  # Handle cases where multiple hyperparameter values lead to the same performance.\n",
+        "                best_params[param.parameter_id].append(\n",
+        "                    params\n",
+        "                )  # Handle cases where multiple hyperparameter values lead to the same performance.\n",
         "    print(\"Best hyperparameter value(s):\")\n",
         "    for metric, params in best_params.items():\n",
         "        print(f\"Metric={metric}: {sorted(params)}\")\n",
@@ -1443,7 +1465,9 @@
       },
       "outputs": [],
       "source": [
-        "PREDICTION_CONTAINER = \"prediction-custom-container\"  # @param {type:\"string\"} Name of the container image."
+        "PREDICTION_CONTAINER = (\n",
+        "    \"prediction-custom-container\"  # @param {type:\"string\"} Name of the container image.\n",
+        ")"
       ]
     },
     {
@@ -1475,7 +1499,7 @@
         "  machineType: 'E2_HIGHCPU_8'\"\"\".format(\n",
         "    PROJECT_ID=PROJECT_ID,\n",
         "    PREDICTION_CONTAINER=PREDICTION_CONTAINER,\n",
-        "    ARTIFACTS_DIR=ARTIFACTS_DIR\n",
+        "    ARTIFACTS_DIR=ARTIFACTS_DIR,\n",
         ")\n",
         "\n",
         "with open(\"cloudbuild.yaml\", \"w\") as fp:\n",
@@ -1592,8 +1616,12 @@
       },
       "outputs": [],
       "source": [
-        "RUN_HYPERPARAMETER_TUNING = False  # Execute regular training instead of hyperparameter tuning.\n",
-        "TRAIN_WITH_BEST_HYPERPARAMETERS = True  # @param {type:\"bool\"} Whether to use learned hyperparameters in training."
+        "RUN_HYPERPARAMETER_TUNING = (\n",
+        "    False  # Execute regular training instead of hyperparameter tuning.\n",
+        ")\n",
+        "TRAIN_WITH_BEST_HYPERPARAMETERS = (\n",
+        "    True  # @param {type:\"bool\"} Whether to use learned hyperparameters in training.\n",
+        ")"
       ]
     },
     {
@@ -1633,10 +1661,12 @@
         "job = aiplatform.CustomContainerTrainingJob(\n",
         "    display_name=\"train-movielens\",\n",
         "    container_uri=f\"gcr.io/{PROJECT_ID}/{HPTUNING_TRAINING_CONTAINER}:latest\",\n",
-        "    command=[\"python3\", \"-m\", \"src.training.task\"] + args,  # Pass in training arguments, including hyperparameters.\n",
+        "    command=[\"python3\", \"-m\", \"src.training.task\"]\n",
+        "    + args,  # Pass in training arguments, including hyperparameters.\n",
         "    model_serving_container_image_uri=f\"gcr.io/{PROJECT_ID}/{PREDICTION_CONTAINER}:latest\",\n",
         "    model_serving_container_predict_route=\"/predict\",\n",
-        "    model_serving_container_health_route=\"/health\")\n",
+        "    model_serving_container_health_route=\"/health\",\n",
+        ")\n",
         "\n",
         "print(\"Training Spec:\", job._managed_model)\n",
         "\n",
@@ -1645,7 +1675,8 @@
         "    replica_count=1,\n",
         "    machine_type=\"n1-standard-4\",\n",
         "    accelerator_type=\"ACCELERATOR_TYPE_UNSPECIFIED\",\n",
-        "    accelerator_count=0)"
+        "    accelerator_count=0,\n",
+        ")"
       ]
     },
     {
@@ -1784,7 +1815,7 @@
         "! gcloud ai models delete $model.name --quiet\n",
         "\n",
         "# Delete Cloud Storage objects that were created\n",
-        "! gsutil -m rm -r $ARTIFACTS_DIR"
+        "! gcloud storage rm --recursive $ARTIFACTS_DIR"
       ]
     }
   ],

community-content/tf_keras_image_classification_distributed_multi_worker_with_vertex_sdk/multi_worker_vertex_training_on_cpu_with_custom_container.ipynb

@@ -324,7 +324,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls $gcs_output_uri_prefix"
+        "! gcloud storage ls $gcs_output_uri_prefix"
       ]
     },
     {
@@ -344,7 +344,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil rm -rf $gcs_output_uri_prefix"
+        "! gcloud storage rm --recursive --continue-on-error $gcs_output_uri_prefix"
       ]
     }
   ],

community-content/tf_keras_image_classification_distributed_multi_worker_with_vertex_sdk/multi_worker_vertex_training_on_gpu_with_custom_container.ipynb

@@ -328,7 +328,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls $gcs_output_uri_prefix"
+        "! gcloud storage ls $gcs_output_uri_prefix"
       ]
     },
     {
@@ -348,7 +348,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil rm -rf $gcs_output_uri_prefix"
+        "! gcloud storage rm --recursive --continue-on-error $gcs_output_uri_prefix"
       ]
     }
   ],

community-content/tf_keras_text_classification_distributed_single_worker_gpus_with_gcloud_local_run_and_vertex_sdk/vertex_training_with_local_mode_container.ipynb

@@ -341,7 +341,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls $gcs_output_uri_prefix"
+        "! gcloud storage ls $gcs_output_uri_prefix"
       ]
     },
     {
@@ -361,7 +361,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil rm -rf $gcs_output_uri_prefix"
+        "! gcloud storage rm --recursive --continue-on-error $gcs_output_uri_prefix"
       ]
     }
   ],

community-content/vertex-distributed-training/a3mega/llama-3-8b-nemo-pretraining/docker/requirements.txt

@@ -5,6 +5,6 @@ immutabledict==4.2.1
 protobuf==4.25.8
 opencv-python-headless==4.11.0.86
 docutils==0.16
-urllib3==2.5.0
+urllib3==2.6.0
 google-cloud-storage==3.0.0
 retrying

community-content/vertex-distributed-training/a3mega/llama-3-8b-nemo-pretraining/requirements.txt

@@ -45,5 +45,5 @@ six==1.17.0
 sniffio==1.3.1
 typing-inspection==0.4.0
 typing_extensions==4.13.2
-urllib3==2.4.0
+urllib3==2.6.0
 websockets==15.0.1

community-content/vertex_model_garden/model_oss/cloudnerf/local_colmap_and_resize.sh

@@ -66,7 +66,7 @@ mkdir -p "$local_folder"
 mkdir -p "$output_folder"
 
 # Download the content from the GCS URI
-gsutil -m cp -r "$gcs_dataset_path"/* "$local_folder/"
+gcloud storage cp --recursive "$gcs_dataset_path"/* "$local_folder/"
 
 # Process files in the local folder
 for file in "$local_folder"/*; do
@@ -122,23 +122,23 @@ cp -r "$output_folder" "$images_folder"/images_2
 pushd "$images_folder"/images_2
 ls | xargs -P 8 -I {} mogrify -resize 50% {}
 popd
-gsutil -m cp -r "$images_folder"/images_2/*  "$gcs_experiment_path"/data/images_2
+gcloud storage cp --recursive "$images_folder"/images_2/*  "$gcs_experiment_path"/data/images_2
 
 cp -r "$output_folder" "$images_folder"/images_4
 pushd "$images_folder"/images_4
 ls | xargs -P 8 -I {} mogrify -resize 25% {}
 popd
-gsutil -m cp -r "$images_folder"/images_4/*  "$gcs_experiment_path"/data/images_4
+gcloud storage cp --recursive "$images_folder"/images_4/*  "$gcs_experiment_path"/data/images_4
 
 cp -r "$output_folder" "$images_folder"/images_8
 pushd "$images_folder"/images_8
 ls | xargs -P 8 -I {} mogrify -resize 12.5% {}
 popd
-gsutil -m cp "$images_folder"/images_8/*  "$gcs_experiment_path"/data/images_8
+gcloud storage cp "$images_folder"/images_8/*  "$gcs_experiment_path"/data/images_8
 
 # Copy images and sparse reconstruction files to gcs experiment folder.
-gsutil -m cp "$images_folder"/images/*  "$gcs_experiment_path"/data/images
-gsutil -m cp -r "$local_folder"/sparse  "$gcs_experiment_path"/data
-gsutil -m cp "$local_folder"/database.db  "$gcs_experiment_path"/data
+gcloud storage cp "$images_folder"/images/*  "$gcs_experiment_path"/data/images
+gcloud storage cp --recursive "$local_folder"/sparse  "$gcs_experiment_path"/data
+gcloud storage cp "$local_folder"/database.db  "$gcs_experiment_path"/data
 
 echo "Processing complete."

community-content/vertex_model_garden/model_oss/cloudnerf/render.sh

@@ -99,14 +99,14 @@ create_dir_if_not_exists "$CHECKPOINTS_PATH"
 touch "$local_experiment_path/$exp_folder_name/log_render.txt"
 
 # Copy experiment from GCS bucket to local
-gsutil -m cp -r "${args[-gcs_experiment_path]}/data" "$local_experiment_path/$exp_folder_name" || exit 1
-gsutil -m cp -r "${args[-gcs_experiment_path]}/checkpoints/${training_job_name}/*" "$CHECKPOINTS_PATH" || exit 1
+gcloud storage cp --recursive "${args[-gcs_experiment_path]}/data" "$local_experiment_path/$exp_folder_name" || exit 1
+gcloud storage cp --recursive "${args[-gcs_experiment_path]}/checkpoints/${training_job_name}/*" "$CHECKPOINTS_PATH" || exit 1
 
 # Check and copy keyframes file.
 if [[ -n ${args[-gcs_keyframes_file]} ]]; then
   keyframes_file_basename=$(basename "${args[-gcs_keyframes_file]}")
   local_keyframes_file="$local_dataset_path/$keyframes_file_basename"
-  gsutil cp "${args[-gcs_keyframes_file]}" "$local_keyframes_file" || exit 1
+  gcloud storage cp "${args[-gcs_keyframes_file]}" "$local_keyframes_file" || exit 1
   echo "Local keyframe file: $local_keyframes_file"
   launch_rendering "$local_keyframes_file"
 else
@@ -114,4 +114,4 @@ else
 fi
 
 # Copy rendered data back to GCS.
-gsutil -m cp -r "$OUTPUT_RENDER_PATH" "${args[-gcs_experiment_path]}/render/${rendering_job_name}"
+gcloud storage cp --recursive "$OUTPUT_RENDER_PATH" "${args[-gcs_experiment_path]}/render/${rendering_job_name}"

community-content/vertex_model_garden/model_oss/cloudnerf/train.sh

@@ -74,7 +74,7 @@ create_dir_if_not_exists "$local_experiment_path"
 create_dir_if_not_exists "$local_experiment_path/$scene_folder_name"
 
 # Copy experiment from GCS bucket to local.
-gsutil -m cp -r "${gcs_experiment_path}/data" "$local_experiment_path/$scene_folder_name" || exit 1
+gcloud storage cp --recursive "${gcs_experiment_path}/data" "$local_experiment_path/$scene_folder_name" || exit 1
 
 echo "GCS Experiment: $gcs_experiment_path"
 echo "Gin Config File: $gin_config_file"
@@ -89,6 +89,6 @@ accelerate launch train.py --gin_configs="$gin_config_file" \
   --gin_bindings="Config.factor = ${factor}" \
   --gin_bindings="Config.max_steps = ${max_training_steps}"
 
-gsutil -m rm -r "${gcs_experiment_path}/checkpoints/${training_job_name}"
-gsutil -m cp -r "$local_experiment_path/$scene_folder_name/config.gin" "${gcs_experiment_path}/${training_job_name}_config.gin"
-gsutil -m cp -r "$local_experiment_path/$scene_folder_name/checkpoints/*/*" "${gcs_experiment_path}/checkpoints/${training_job_name}"
+gcloud storage rm --recursive "${gcs_experiment_path}/checkpoints/${training_job_name}"
+gcloud storage cp --recursive "$local_experiment_path/$scene_folder_name/config.gin" "${gcs_experiment_path}/${training_job_name}_config.gin"
+gcloud storage cp --recursive "$local_experiment_path/$scene_folder_name/checkpoints/*/*" "${gcs_experiment_path}/checkpoints/${training_job_name}"

community-content/vertex_model_garden/model_oss/notebook_util/dataset_validation_util.py

@@ -102,10 +102,10 @@ def download_gcs_uri_to_local(
     if not os.path.exists(destination_dir):
       os.mkdir(destination_dir)
     subprocess.check_output([
-        "gsutil",
-        "-m",
+        "gcloud",
+        "storage",
         "cp",
-        "-r",
+        "--recursive",
         gcs_uri,
         destination_dir,
     ])

notebooks/community/CODEOWNERS

@@ -26,6 +26,8 @@
 /vertex_endpoints/find_ideal_machine_type/find_ideal_machine_type/find_ideal_machine_type.ipynb @entrpn
 /vertex_endpoints/nvidia-triton/nvidia-triton-custom-container-prediction.ipynb @RajeshThallam
 /vertex_endpoints/optimized_tensorflow_runtime @vlasenkoalexey
+/notebooks/community/alphagenome/cloudai_alphagenome_vai_quickstart.ipynb @dpanigra
+/notebooks/community/weathernext/weathernext_2_early_access_program.ipynb @dpanigra
 /notebooks/community/ml_ops/stage2/get_started_with_visionapi_and_automl.ipynb @mansari
 /notebooks/community/neo4j/graph_paysim.ipynb @benofben @laeg
 /notebooks/community/ml_ops/stage1/get_started_with_visionapi_and_vertex_datasets.ipynb @mansari

notebooks/community/alphagenome/README.md

@@ -0,0 +1,93 @@
+![AlphaGenome header image](https://raw.githubusercontent.com/google-deepmind/alphagenome/refs/heads/main/docs/source/_static/header.png)
+
+# AlphaGenome
+[**Overview**](#overview) | [**Use Cases**](#use-cases) | [**Documentation**](#documentation) | [**Pricing**](#pricing) | [**Quick start**](#quick-start)
+
+## Overview
+**Disclaimer:** *Experimental*.
+
+*The AlphaGenome Private Preview is a "Pre-GA Offering" subject to the "Pre-GA
+Offerings Terms" in the General Service Terms section of the Google Cloud
+[Service Specific Terms](https://cloud.google.com/terms/service-terms). It is
+also a “Generative AI Preview Product” as defined in and subject to the
+[Additional Terms for Generative AI Preview Products](https://cloud.google.com/trustedtester/aitos?e=48754805&hl=en).
+Pre-GA products are available "as is" and might have limited support. For more
+information, see the [launch stage](https://cloud.google.com/products?e=48754805#product-launch-stages)
+descriptions.*
+
+Access to the AlphaGenome model capabilities requires application and approval.
+Users must be added to an allowlist to use the service.
+If you are interested in applying to the program, **Request Access** above.
+
+ 
+
+AlphaGenome is Google DeepMind’s unifying model for deciphering the regulatory
+code within DNA sequences.
+
+AlphaGenome offers multimodal predictions, encompassing diverse functional
+outputs such as gene expression, splicing patterns, chromatin features, and
+contact maps (see diagram below). The model analyzes DNA sequences of up to 1
+million base pairs in length and can deliver predictions at single base-pair
+resolution for most outputs.
+
+Training data was sourced from large public consortia including
+[ENCODE](http://encodeproject.org/), [GTEx](https://www.gtexportal.org/),
+[4D Nucleome](https://4dnucleome.org/) and
+[FANTOM5](https://fantom.gsc.riken.jp/5/), which experimentally measured these
+properties covering important modalities of gene regulation across hundreds of
+human and mouse cell types and tissues.
+
+![Diagram showing an overview of the AlphaGenome model architecture and its inputs/outputs](https://www.alphagenomedocs.com/_images/model_overview.png)
+
+## Use Cases
+*   **Sequence-to-function predictions:** Predict multiple functional tracks (such as gene expression, splicing) from DNA sequences across a wide variety of tissues and cell types.
+
+*   **Variant effect scoring:** Assess the impact of genetic variants by comparing predictions for the reference and alternative alleles and summarising the differences between them.
+
+*   **Identify functional regions:** Use in silico mutagenesis (ISM) to identify functionally important regions in the DNA sequence.
+
+*   **Human and mouse capability:** Generate predictions for both human and mouse genomes.
+
+## Documentation
+This API provides access to AlphaGenome, Google DeepMind's unifying model for
+deciphering the regulatory code within DNA sequences. AlphaGenome offers
+multimodal predictions, encompassing diverse functional outputs including gene
+expression, splicing patterns, chromatin features, and contact maps (see diagram
+below). The model analyzes up to 1 million base pairs of DNA sequence and can
+deliver predictions at single base-pair resolution for most modalities.
+AlphaGenome achieves state-of-the-art performance across a range of genomic
+prediction benchmarks, including diverse variant effect prediction tasks.
+
+The Google Cloud API for AlphaGenome provides a way for Google Cloud customers
+to explore the AlphaGenome API for commercial use cases. This API is in private
+preview (Request Access above). Once allowlisted, customers can access the API
+directly or use the [colab](cloudai_alphagenome_vai_quickstart.ipynb).
+
+### Acknowledgements
+
+*Avsec, Ž., Latysheva, N., Cheng, J., Novati, G., Taylor, K. R., Ward, T., ... Kohli, P. (2025). AlphaGenome: advancing regulatory variant effect prediction with a unified DNA sequence model. bioRxiv.* [https://doi.org/10.1101/2025.06.25.661532](https://doi.org/10.1101/2025.06.25.661532)
+
+### Contact
+If you have any questions on using these models on Google Cloud please contact:
+[alphagenome-cloud-external@google.com](mailto:alphagenome-cloud-external@google.com) or join the community [Discourse](https://www.alphagenomecommunity.com/) for more generic questions on AlphaGenome.
+
+### Links
+
+*   Read our [paper](https://doi.org/10.1101/2025.06.25.661532)
+*   Read our [blog post](https://deepmind.google/discover/blog/alphagenome-ai-for-better-understanding-the-genome)
+*   Join the [community](https://www.alphagenomecommunity.com/)
+*   Check out the [AlphaGenome 101 Video](https://youtu.be/Xbvloe13nak)
+
+## Pricing
+Access to AlphaGenome on Vertex AI is currently restricted.
+To utilize these models via this service:
+
+*   You must **Request Access** using your Google contact.
+*   Your application will be reviewed, and if approved, you will be **added to
+    an allowlist**.
+*   Only allowlisted users can access the API
+*   **Pricing information** will be shared directly with users upon approval
+    and placement on the allowlist.
+
+## Quick start
+The quickest way to get started with the AlphaGenome in Google Cloud Platform is to run [our example notebook](cloudai_alphagenome_vai_quickstart.ipynb) in [Google Colab](https://colab.research.google.com/).

notebooks/community/bigquery_ml/bqml-online-prediction.ipynb

@@ -359,7 +359,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l {REGION} -p {PROJECT_ID} {BUCKET_URI}"
+        "! gcloud storage buckets create --location={REGION} --project={PROJECT_ID} {BUCKET_URI}"
       ]
     },
     {
@@ -1098,7 +1098,7 @@
         "    ! bq rm -r -f $PROJECT_ID:$BQ_DATASET_NAME\n",
         "# delete the Cloud Storage bucket\n",
         "if delete_bucket or os.getenv(\"IS_TESTING\"):\n",
-        "    ! gsutil -m rm -r $BUCKET_URI"
+        "    ! gcloud storage rm --recursive $BUCKET_URI"
       ]
     }
   ],

notebooks/community/cohere/cohere_embedding_with_matching_engine.ipynb

@@ -449,7 +449,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION $BUCKET_NAME"
+        "! gcloud storage buckets create --location=$REGION $BUCKET_NAME"
       ]
     },
     {
@@ -470,7 +470,7 @@
       "outputs": [],
       "source": [
         "# this will not return anything if the bucket is empty\n",
-        "! gsutil ls -al $BUCKET_NAME"
+        "! gcloud storage ls --all-versions --long $BUCKET_NAME"
       ]
     },
     {
@@ -588,7 +588,7 @@
         "# NOTE: Everything in this GCS DIR will be DELETED before uploading the data.\n",
         "# A CommandException is expected if no data is present\n",
         "\n",
-        "! gsutil rm -rf {BUCKET_NAME}/*"
+        "! gcloud storage rm --recursive --continue-on-error {BUCKET_NAME}/*"
       ]
     },
     {
@@ -599,7 +599,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil cp cohere_embeddings.json {BUCKET_NAME}/cohere_embeddings.json"
+        "! gcloud storage cp cohere_embeddings.json {BUCKET_NAME}/cohere_embeddings.json"
       ]
     },
     {
@@ -610,7 +610,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls {BUCKET_NAME}"
+        "! gcloud storage ls {BUCKET_NAME}"
       ]
     },
     {

notebooks/community/experiments/vertex_ai_model_experimentation.ipynb

@@ -537,7 +537,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION -p $PROJECT_ID $BUCKET_URI"
+        "! gcloud storage buckets create --location=$REGION --project=$PROJECT_ID $BUCKET_URI"
       ]
     },
     {
@@ -557,7 +557,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_URI"
+        "! gcloud storage ls --all-versions --long $BUCKET_URI"
       ]
     },
     {
@@ -627,9 +627,9 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil iam ch serviceAccount:{SERVICE_ACCOUNT}:roles/storage.objectCreator $BUCKET_URI\n",
+        "! gcloud storage buckets add-iam-policy-binding $BUCKET_URI --member=serviceAccount:{SERVICE_ACCOUNT} --role=roles/storage.objectCreator\n",
         "\n",
-        "! gsutil iam ch serviceAccount:{SERVICE_ACCOUNT}:roles/storage.objectViewer $BUCKET_URI"
+        "! gcloud storage buckets add-iam-policy-binding $BUCKET_URI --member=serviceAccount:{SERVICE_ACCOUNT} --role=roles/storage.objectViewer"
       ]
     },
     {
@@ -1736,7 +1736,7 @@
         "delete_bucket = False\n",
         "\n",
         "if delete_bucket or os.getenv(\"IS_TESTING\"):\n",
-        "    ! gsutil rm -rf {BUCKET_URI}"
+        "    ! gcloud storage rm --recursive --continue-on-error {BUCKET_URI}"
       ]
     }
   ],

notebooks/community/explainable_ai/SDK_Custom_Container_XAI.ipynb

@@ -405,7 +405,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION -p $PROJECT_ID $BUCKET_URI"
+        "! gcloud storage buckets create --location=$REGION --project=$PROJECT_ID $BUCKET_URI"
       ]
     },
     {
@@ -425,7 +425,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_URI"
+        "! gcloud storage ls --all-versions --long $BUCKET_URI"
       ]
     },
     {
@@ -698,7 +698,7 @@
       },
       "outputs": [],
       "source": [
-        "!gsutil cp app/model.joblib {BUCKET_URI}/{MODEL_ARTIFACT_DIR}/"
+        "!gcloud storage cp app/model.joblib {BUCKET_URI}/{MODEL_ARTIFACT_DIR}/"
       ]
     },
     {
@@ -1516,7 +1516,7 @@
         "\n",
         "delete_bucket = False\n",
         "if delete_bucket or os.getenv(\"IS_TESTING\"):\n",
-        "    ! gsutil rm -rf {BUCKET_URI}"
+        "    ! gcloud storage rm --recursive --continue-on-error {BUCKET_URI}"
       ]
     }
   ],

notebooks/community/exploratory_data_analysis/eda_with_r_and_bigquery.ipynb

@@ -637,20 +637,20 @@
    },
    "outputs": [],
    "source": [
-    "# Upload CSV data to Cloud Storage by passing gsutil commands to system\n",
+    "# Upload CSV data to Cloud Storage by passing gcloud storage commands to system\n",
     "gcs_url <- paste0(\"gs://\", BUCKET_NAME, \"/\")\n",
     "\n",
-    "command <- paste(\"gsutil mb\", gcs_url)\n",
+    "command <- paste(\"gcloud storage buckets create\", gcs_url)\n",
     "\n",
     "system(command)\n",
     "\n",
     "gcs_data_dir <- paste0(\"gs://\", BUCKET_NAME, \"/data\")\n",
     "\n",
-    "command <- paste(\"gsutil cp data/*_data.csv\", gcs_data_dir)\n",
+    "command <- paste(\"gcloud storage cp data/*_data.csv\", gcs_data_dir)\n",
     "\n",
     "system(command)\n",
     "\n",
-    "command <- paste(\"gsutil ls -l\", gcs_data_dir)\n",
+    "command <- paste(\"gcloud storage ls --long\", gcs_data_dir)\n",
     "\n",
     "system(command, intern = TRUE)"
    ]
@@ -679,4 +679,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 4
-}
+}

notebooks/community/feature_store/get_started_vertex_feature_store.ipynb

@@ -471,8 +471,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION $BUCKET_URI"
-      ]
+        "! gcloud storage buckets create --location=$REGION $BUCKET_URI"      ]
     },
     {
       "cell_type": "markdown",
@@ -491,8 +490,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_URI"
-      ]
+        "! gcloud storage ls --all-versions --long $BUCKET_URI"      ]
     },
     {
       "cell_type": "markdown",
@@ -511,8 +509,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil uniformbucketlevelaccess set on {BUCKET_URI}"
-      ]
+        "! gcloud storage buckets update --uniform-bucket-level-access {BUCKET_URI}"      ]
     },
     {
       "cell_type": "markdown",
@@ -1910,9 +1907,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil -m rm -r $BUCKET_URI\n",
-        "! gsutil rb $BUCKET_URI"
-      ]
+        "! gcloud storage rm --recursive $BUCKET_URI\n",        "! gcloud storage buckets delete $BUCKET_URI"      ]
     }
   ],
   "metadata": {

notebooks/community/gapic/automl/showcase_automl_image_classification_batch.ipynb

@@ -421,7 +421,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION $BUCKET_NAME"
+        "! gcloud storage buckets create --location=$REGION $BUCKET_NAME"
       ]
     },
     {
@@ -441,7 +441,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_NAME"
+        "! gcloud storage ls --all-versions --long $BUCKET_NAME"
       ]
     },
     {
@@ -478,9 +478,7 @@
         "import time\n",
         "\n",
         "from google.cloud.aiplatform import gapic as aip\n",
-        "from google.protobuf import json_format\n",
-        "from google.protobuf.json_format import MessageToJson, ParseDict\n",
-        "from google.protobuf.struct_pb2 import Struct, Value"
+        "from google.protobuf import json_format"
       ]
     },
     {
@@ -886,11 +884,11 @@
         "else:\n",
         "    FILE = IMPORT_FILE\n",
         "\n",
-        "count = ! gsutil cat $FILE | wc -l\n",
+        "count = ! gcloud storage cat $FILE | wc -l\n",
         "print(\"Number of Examples\", int(count[0]))\n",
         "\n",
         "print(\"First 10 rows\")\n",
-        "! gsutil cat $FILE | head"
+        "! gcloud storage cat $FILE | head"
       ]
     },
     {
@@ -1329,7 +1327,7 @@
       },
       "outputs": [],
       "source": [
-        "test_items = !gsutil cat $IMPORT_FILE | head -n2\n",
+        "test_items = !gcloud storage cat $IMPORT_FILE | head -n2\n",
         "if len(str(test_items[0]).split(\",\")) == 3:\n",
         "    _, test_item_1, test_label_1 = str(test_items[0]).split(\",\")\n",
         "    _, test_item_2, test_label_2 = str(test_items[1]).split(\",\")\n",
@@ -1363,8 +1361,8 @@
         "file_1 = test_item_1.split(\"/\")[-1]\n",
         "file_2 = test_item_2.split(\"/\")[-1]\n",
         "\n",
-        "! gsutil cp $test_item_1 $BUCKET_NAME/$file_1\n",
-        "! gsutil cp $test_item_2 $BUCKET_NAME/$file_2\n",
+        "! gcloud storage cp $test_item_1 $BUCKET_NAME/$file_1\n",
+        "! gcloud storage cp $test_item_2 $BUCKET_NAME/$file_2\n",
         "\n",
         "test_item_1 = BUCKET_NAME + \"/\" + file_1\n",
         "test_item_2 = BUCKET_NAME + \"/\" + file_2"
@@ -1408,7 +1406,7 @@
         "    f.write(json.dumps(data) + \"\\n\")\n",
         "\n",
         "print(gcs_input_uri)\n",
-        "! gsutil cat $gcs_input_uri"
+        "! gcloud storage cat $gcs_input_uri"
       ]
     },
     {
@@ -1692,8 +1690,8 @@
       "outputs": [],
       "source": [
         "def get_latest_predictions(gcs_out_dir):\n",
-        "    \"\"\" Get the latest prediction subfolder using the timestamp in the subfolder name\"\"\"\n",
-        "    folders = !gsutil ls $gcs_out_dir\n",
+        "    \"\"\"Get the latest prediction subfolder using the timestamp in the subfolder name\"\"\"\n",
+        "    folders = !gcloud storage ls $gcs_out_dir\n",
         "    latest = \"\"\n",
         "    for folder in folders:\n",
         "        subfolder = folder.split(\"/\")[-2]\n",
@@ -1711,9 +1709,9 @@
         "            raise Exception(\"Batch Job Failed\")\n",
         "    else:\n",
         "        folder = get_latest_predictions(predictions)\n",
-        "        ! gsutil ls $folder/prediction*.jsonl\n",
+        "        ! gcloud storage ls $folder/prediction*.jsonl\n",
         "\n",
-        "        ! gsutil cat $folder/prediction*.jsonl\n",
+        "        ! gcloud storage cat $folder/prediction*.jsonl\n",
         "        break\n",
         "    time.sleep(60)"
       ]
@@ -1808,7 +1806,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"
       ]
     }
   ],

notebooks/community/gapic/automl/showcase_automl_image_classification_export_edge.ipynb

@@ -416,7 +416,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION $BUCKET_NAME"
+        "! gcloud storage buckets create --location=$REGION $BUCKET_NAME"
       ]
     },
     {
@@ -436,7 +436,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_NAME"
+        "! gcloud storage ls --all-versions --long $BUCKET_NAME"
       ]
     },
     {
@@ -474,7 +474,6 @@
         "\n",
         "from google.cloud.aiplatform import gapic as aip\n",
         "from google.protobuf import json_format\n",
-        "from google.protobuf.json_format import MessageToJson, ParseDict\n",
         "from google.protobuf.struct_pb2 import Struct, Value"
       ]
     },
@@ -784,11 +783,11 @@
         "else:\n",
         "    FILE = IMPORT_FILE\n",
         "\n",
-        "count = ! gsutil cat $FILE | wc -l\n",
+        "count = ! gcloud storage cat $FILE | wc -l\n",
         "print(\"Number of Examples\", int(count[0]))\n",
         "\n",
         "print(\"First 10 rows\")\n",
-        "! gsutil cat $FILE | head"
+        "! gcloud storage cat $FILE | head"
       ]
     },
     {
@@ -1215,7 +1214,6 @@
         "    }\n",
         "    response = clients[\"model\"].export_model(name=name, output_config=output_config)\n",
         "    print(\"Long running operation:\", response.operation.name)\n",
-        "    result = response.result(timeout=1800)\n",
         "    metadata = response.operation.metadata\n",
         "    artifact_uri = str(metadata.value).split(\"\\\\\")[-1][4:-1]\n",
         "    print(\"Artifact Uri\", artifact_uri)\n",
@@ -1244,9 +1242,9 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls $model_package\n",
+        "! gcloud storage ls $model_package\n",
         "# Download the model artifacts\n",
-        "! gsutil cp -r $model_package tflite\n",
+        "! gcloud storage cp --recursive $model_package tflite\n",
         "\n",
         "tflite_path = \"tflite/model.tflite\""
       ]
@@ -1305,7 +1303,7 @@
       },
       "outputs": [],
       "source": [
-        "test_items = ! gsutil cat $IMPORT_FILE | head -n1\n",
+        "test_items = ! gcloud storage cat $IMPORT_FILE | head -n1\n",
         "test_item = test_items[0].split(\",\")[0]\n",
         "\n",
         "with tf.io.gfile.GFile(test_item, \"rb\") as f:\n",
@@ -1449,7 +1447,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"
       ]
     }
   ],

notebooks/community/gapic/automl/showcase_automl_image_classification_online.ipynb

@@ -721,12 +721,10 @@
         "else:\n",
         "    FILE = IMPORT_FILE\n",
         "\n",
-        "count = ! gsutil cat $FILE | wc -l\n",
-        "print(\"Number of Examples\", int(count[0]))\n",
+        "count = ! gcloud storage cat $FILE | wc -l\n",        "print(\"Number of Examples\", int(count[0]))\n",
         "\n",
         "print(\"First 10 rows\")\n",
-        "! gsutil cat $FILE | head"
-      ]
+        "! gcloud storage cat $FILE | head"      ]
     },
     {
       "cell_type": "markdown",
@@ -1342,8 +1340,7 @@
       },
       "outputs": [],
       "source": [
-        "test_item = !gsutil cat $IMPORT_FILE | head -n1\n",
-        "if len(str(test_item[0]).split(\",\")) == 3:\n",
+        "test_item = !gcloud storage cat $IMPORT_FILE | head -n1\n",        "if len(str(test_item[0]).split(\",\")) == 3:\n",
         "    _, test_item, test_label = str(test_item[0]).split(\",\")\n",
         "else:\n",
         "    test_item, test_label = str(test_item[0]).split(\",\")\n",
@@ -1568,8 +1565,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/gapic/automl/showcase_automl_image_classification_online_proxy.ipynb

@@ -721,12 +721,10 @@
         "else:\n",
         "    FILE = IMPORT_FILE\n",
         "\n",
-        "count = ! gsutil cat $FILE | wc -l\n",
-        "print(\"Number of Examples\", int(count[0]))\n",
+        "count = ! gcloud storage cat $FILE | wc -l\n",        "print(\"Number of Examples\", int(count[0]))\n",
         "\n",
         "print(\"First 10 rows\")\n",
-        "! gsutil cat $FILE | head"
-      ]
+        "! gcloud storage cat $FILE | head"      ]
     },
     {
       "cell_type": "markdown",
@@ -1342,8 +1340,7 @@
       },
       "outputs": [],
       "source": [
-        "test_item = !gsutil cat $IMPORT_FILE | head -n1\n",
-        "if len(str(test_item[0]).split(\",\")) == 3:\n",
+        "test_item = !gcloud storage cat $IMPORT_FILE | head -n1\n",        "if len(str(test_item[0]).split(\",\")) == 3:\n",
         "    _, test_item, test_label = str(test_item[0]).split(\",\")\n",
         "else:\n",
         "    test_item, test_label = str(test_item[0]).split(\",\")\n",
@@ -1747,8 +1744,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/gapic/automl/showcase_automl_image_object_detection_batch.ipynb

@@ -421,7 +421,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION $BUCKET_NAME"
+        "! gcloud storage buckets create --location=$REGION $BUCKET_NAME"
       ]
     },
     {
@@ -441,7 +441,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_NAME"
+        "! gcloud storage ls --all-versions --long $BUCKET_NAME"
       ]
     },
     {
@@ -478,9 +478,7 @@
         "import time\n",
         "\n",
         "from google.cloud.aiplatform import gapic as aip\n",
-        "from google.protobuf import json_format\n",
-        "from google.protobuf.json_format import MessageToJson, ParseDict\n",
-        "from google.protobuf.struct_pb2 import Struct, Value"
+        "from google.protobuf import json_format"
       ]
     },
     {
@@ -887,11 +885,11 @@
         "else:\n",
         "    FILE = IMPORT_FILE\n",
         "\n",
-        "count = ! gsutil cat $FILE | wc -l\n",
+        "count = ! gcloud storage cat $FILE | wc -l\n",
         "print(\"Number of Examples\", int(count[0]))\n",
         "\n",
         "print(\"First 10 rows\")\n",
-        "! gsutil cat $FILE | head"
+        "! gcloud storage cat $FILE | head"
       ]
     },
     {
@@ -1333,7 +1331,7 @@
       },
       "outputs": [],
       "source": [
-        "test_items = !gsutil cat $IMPORT_FILE | head -n2\n",
+        "test_items = !gcloud storage cat $IMPORT_FILE | head -n2\n",
         "cols_1 = str(test_items[0]).split(\",\")\n",
         "cols_2 = str(test_items[1]).split(\",\")\n",
         "if len(cols_1) == 11:\n",
@@ -1373,8 +1371,8 @@
         "file_1 = test_item_1.split(\"/\")[-1]\n",
         "file_2 = test_item_2.split(\"/\")[-1]\n",
         "\n",
-        "! gsutil cp $test_item_1 $BUCKET_NAME/$file_1\n",
-        "! gsutil cp $test_item_2 $BUCKET_NAME/$file_2\n",
+        "! gcloud storage cp $test_item_1 $BUCKET_NAME/$file_1\n",
+        "! gcloud storage cp $test_item_2 $BUCKET_NAME/$file_2\n",
         "\n",
         "test_item_1 = BUCKET_NAME + \"/\" + file_1\n",
         "test_item_2 = BUCKET_NAME + \"/\" + file_2"
@@ -1418,7 +1416,7 @@
         "    f.write(json.dumps(data) + \"\\n\")\n",
         "\n",
         "print(gcs_input_uri)\n",
-        "! gsutil cat $gcs_input_uri"
+        "! gcloud storage cat $gcs_input_uri"
       ]
     },
     {
@@ -1704,8 +1702,8 @@
       "outputs": [],
       "source": [
         "def get_latest_predictions(gcs_out_dir):\n",
-        "    \"\"\" Get the latest prediction subfolder using the timestamp in the subfolder name\"\"\"\n",
-        "    folders = !gsutil ls $gcs_out_dir\n",
+        "    \"\"\"Get the latest prediction subfolder using the timestamp in the subfolder name\"\"\"\n",
+        "    folders = !gcloud storage ls $gcs_out_dir\n",
         "    latest = \"\"\n",
         "    for folder in folders:\n",
         "        subfolder = folder.split(\"/\")[-2]\n",
@@ -1723,9 +1721,9 @@
         "            raise Exception(\"Batch Job Failed\")\n",
         "    else:\n",
         "        folder = get_latest_predictions(predictions)\n",
-        "        ! gsutil ls $folder/prediction*.jsonl\n",
+        "        ! gcloud storage ls $folder/prediction*.jsonl\n",
         "\n",
-        "        ! gsutil cat $folder/prediction*.jsonl\n",
+        "        ! gcloud storage cat $folder/prediction*.jsonl\n",
         "        break\n",
         "    time.sleep(60)"
       ]
@@ -1820,7 +1818,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"
       ]
     }
   ],

notebooks/community/gapic/automl/showcase_automl_image_object_detection_export_edge.ipynb

@@ -416,7 +416,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION $BUCKET_NAME"
+        "! gcloud storage buckets create --location $REGION $BUCKET_NAME"
       ]
     },
     {
@@ -436,7 +436,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_NAME"
+        "! gcloud storage ls --all-versions --long $BUCKET_NAME"
       ]
     },
     {
@@ -473,9 +473,7 @@
         "import time\n",
         "\n",
         "from google.cloud.aiplatform import gapic as aip\n",
-        "from google.protobuf import json_format\n",
-        "from google.protobuf.json_format import MessageToJson, ParseDict\n",
-        "from google.protobuf.struct_pb2 import Struct, Value"
+        "from google.protobuf import json_format\n"
       ]
     },
     {
@@ -785,11 +783,11 @@
         "else:\n",
         "    FILE = IMPORT_FILE\n",
         "\n",
-        "count = ! gsutil cat $FILE | wc -l\n",
+        "count = ! gcloud storage cat $FILE | wc -l\n",
         "print(\"Number of Examples\", int(count[0]))\n",
         "\n",
         "print(\"First 10 rows\")\n",
-        "! gsutil cat $FILE | head"
+        "! gcloud storage cat $FILE | head"
       ]
     },
     {
@@ -1218,7 +1216,6 @@
         "    }\n",
         "    response = clients[\"model\"].export_model(name=name, output_config=output_config)\n",
         "    print(\"Long running operation:\", response.operation.name)\n",
-        "    result = response.result(timeout=1800)\n",
         "    metadata = response.operation.metadata\n",
         "    artifact_uri = str(metadata.value).split(\"\\\\\")[-1][4:-1]\n",
         "    print(\"Artifact Uri\", artifact_uri)\n",
@@ -1247,9 +1244,9 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls $model_package\n",
+        "! gcloud storage ls $model_package\n",
         "# Download the model artifacts\n",
-        "! gsutil cp -r $model_package tflite\n",
+        "! gcloud storage cp --recursive $model_package tflite\n",
         "\n",
         "tflite_path = \"tflite/model.tflite\""
       ]
@@ -1308,7 +1305,7 @@
       },
       "outputs": [],
       "source": [
-        "test_items = ! gsutil cat $IMPORT_FILE | head -n1\n",
+        "test_items = ! gcloud storage cat $IMPORT_FILE | head -n1\n",
         "test_item = test_items[0].split(\",\")[0]\n",
         "\n",
         "with tf.io.gfile.GFile(test_item, \"rb\") as f:\n",
@@ -1452,7 +1449,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"
       ]
     }
   ],

notebooks/community/gapic/automl/showcase_automl_image_object_detection_online.ipynb

@@ -396,9 +396,7 @@
         "import time\n",
         "\n",
         "from google.cloud.aiplatform import gapic as aip\n",
-        "from google.protobuf import json_format\n",
-        "from google.protobuf.json_format import MessageToJson, ParseDict\n",
-        "from google.protobuf.struct_pb2 import Struct, Value"
+        "from google.protobuf import json_format"
       ]
     },
     {
@@ -722,11 +720,11 @@
         "else:\n",
         "    FILE = IMPORT_FILE\n",
         "\n",
-        "count = ! gsutil cat $FILE | wc -l\n",
+        "count = ! gcloud storage cat $FILE | wc -l\n",
         "print(\"Number of Examples\", int(count[0]))\n",
         "\n",
         "print(\"First 10 rows\")\n",
-        "! gsutil cat $FILE | head"
+        "! gcloud storage cat $FILE | head"
       ]
     },
     {
@@ -1345,7 +1343,7 @@
       },
       "outputs": [],
       "source": [
-        "test_items = !gsutil cat $IMPORT_FILE | head -n1\n",
+        "test_items = !gcloud storage cat $IMPORT_FILE | head -n1\n",
         "cols = str(test_items[0]).split(\",\")\n",
         "if len(cols) == 11:\n",
         "    test_item = str(cols[1])\n",
@@ -1574,7 +1572,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"
       ]
     }
   ],

notebooks/community/gapic/automl/showcase_automl_image_segmentation_batch.ipynb

@@ -421,8 +421,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION $BUCKET_NAME"
-      ]
+        "! gcloud storage buckets create --location $REGION $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -441,8 +440,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_NAME"
-      ]
+        "! gcloud storage ls --all-versions --long $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -891,12 +889,10 @@
         "else:\n",
         "    FILE = IMPORT_FILE\n",
         "\n",
-        "count = ! gsutil cat $FILE | wc -l\n",
-        "print(\"Number of Examples\", int(count[0]))\n",
+        "count = ! gcloud storage cat $FILE | wc -l\n",        "print(\"Number of Examples\", int(count[0]))\n",
         "\n",
         "print(\"First 10 rows\")\n",
-        "! gsutil cat $FILE | head"
-      ]
+        "! gcloud storage cat $FILE | head"      ]
     },
     {
       "cell_type": "markdown",
@@ -1325,8 +1321,7 @@
       "source": [
         "import json\n",
         "\n",
-        "test_items = !gsutil cat $IMPORT_FILE | head -n2\n",
-        "test_data_1 = test_items[0].replace(\"'\", '\"')\n",
+        "test_items = !gcloud storage cat $IMPORT_FILE | head -n2\n",        "test_data_1 = test_items[0].replace(\"'\", '\"')\n",
         "test_data_1 = json.loads(test_data_1)\n",
         "test_data_2 = test_items[0].replace(\"'\", '\"')\n",
         "test_data_2 = json.loads(test_data_2)\n",
@@ -1367,9 +1362,8 @@
         "file_1 = test_item_1.split(\"/\")[-1]\n",
         "file_2 = test_item_2.split(\"/\")[-1]\n",
         "\n",
-        "! gsutil cp $test_item_1 $BUCKET_NAME/$file_1\n",
-        "! gsutil cp $test_item_2 $BUCKET_NAME/$file_2\n",
-        "\n",
+        "! gcloud storage cp $test_item_1 $BUCKET_NAME/$file_1\n",
+        "! gcloud storage cp $test_item_2 $BUCKET_NAME/$file_2\n",        "\n",
         "test_item_1 = BUCKET_NAME + \"/\" + file_1\n",
         "test_item_2 = BUCKET_NAME + \"/\" + file_2"
       ]
@@ -1412,8 +1406,7 @@
         "    f.write(json.dumps(data) + \"\\n\")\n",
         "\n",
         "print(gcs_input_uri)\n",
-        "! gsutil cat $gcs_input_uri"
-      ]
+        "! gcloud storage cat $gcs_input_uri"      ]
     },
     {
       "cell_type": "markdown",
@@ -1681,8 +1674,7 @@
       "source": [
         "def get_latest_predictions(gcs_out_dir):\n",
         "    \"\"\" Get the latest prediction subfolder using the timestamp in the subfolder name\"\"\"\n",
-        "    folders = !gsutil ls $gcs_out_dir\n",
-        "    latest = \"\"\n",
+        "    folders = !gcloud storage ls $gcs_out_dir\n",        "    latest = \"\"\n",
         "    for folder in folders:\n",
         "        subfolder = folder.split(\"/\")[-2]\n",
         "        if subfolder.startswith(\"prediction-\"):\n",
@@ -1699,10 +1691,8 @@
         "            raise Exception(\"Batch Job Failed\")\n",
         "    else:\n",
         "        folder = get_latest_predictions(predictions)\n",
-        "        ! gsutil ls $folder/prediction*.jsonl\n",
-        "\n",
-        "        ! gsutil cat $folder/prediction*.jsonl\n",
-        "        break\n",
+        "        ! gcloud storage ls $folder/prediction*.jsonl\n",        "\n",
+        "        ! gcloud storage cat $folder/prediction*.jsonl\n",        "        break\n",
         "    time.sleep(60)"
       ]
     },
@@ -1796,8 +1786,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/gapic/automl/showcase_automl_image_segmentation_online.ipynb

@@ -726,12 +726,10 @@
         "else:\n",
         "    FILE = IMPORT_FILE\n",
         "\n",
-        "count = ! gsutil cat $FILE | wc -l\n",
-        "print(\"Number of Examples\", int(count[0]))\n",
+        "count = ! gcloud storage cat $FILE | wc -l\n",        "print(\"Number of Examples\", int(count[0]))\n",
         "\n",
         "print(\"First 10 rows\")\n",
-        "! gsutil cat $FILE | head"
-      ]
+        "! gcloud storage cat $FILE | head"      ]
     },
     {
       "cell_type": "markdown",
@@ -1338,8 +1336,7 @@
       "source": [
         "import json\n",
         "\n",
-        "test_items = !gsutil cat $IMPORT_FILE | head -n1\n",
-        "test_data = test_items[0].replace(\"'\", '\"')\n",
+        "test_items = !gcloud storage cat $IMPORT_FILE | head -n1\n",        "test_data = test_items[0].replace(\"'\", '\"')\n",
         "test_data = json.loads(test_data)\n",
         "try:\n",
         "    test_item = test_data[\"image_gcs_uri\"]\n",
@@ -1555,8 +1552,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/gapic/automl/showcase_automl_tabular_binary_classification_batch.ipynb

@@ -421,8 +421,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION $BUCKET_NAME"
-      ]
+        "! gcloud storage buckets create --location $REGION $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -441,8 +440,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_NAME"
-      ]
+        "! gcloud storage ls --all-versions --long $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -809,14 +807,11 @@
       },
       "outputs": [],
       "source": [
-        "count = ! gsutil cat $IMPORT_FILE | wc -l\n",
-        "print(\"Number of Examples\", int(count[0]))\n",
+        "count = ! gcloud storage cat $IMPORT_FILE | wc -l\n",        "print(\"Number of Examples\", int(count[0]))\n",
         "\n",
         "print(\"First 10 rows\")\n",
-        "! gsutil cat $IMPORT_FILE | head\n",
-        "\n",
-        "heading = ! gsutil cat $IMPORT_FILE | head -n1\n",
-        "label_column = str(heading).split(\",\")[-1].split(\"'\")[0]\n",
+        "! gcloud storage cat $IMPORT_FILE | head\n",        "\n",
+        "heading = ! gcloud storage cat $IMPORT_FILE | head -n1\n",        "label_column = str(heading).split(\",\")[-1].split(\"'\")[0]\n",
         "print(\"Label Column Name\", label_column)\n",
         "if label_column is None:\n",
         "    raise Exception(\"label column missing\")"
@@ -1377,8 +1372,7 @@
         "    f.write(str(INSTANCE_2) + \"\\n\")\n",
         "\n",
         "print(gcs_input_uri)\n",
-        "! gsutil cat $gcs_input_uri"
-      ]
+        "! gcloud storage cat $gcs_input_uri"      ]
     },
     {
       "cell_type": "markdown",
@@ -1646,8 +1640,7 @@
       "source": [
         "def get_latest_predictions(gcs_out_dir):\n",
         "    \"\"\" Get the latest prediction subfolder using the timestamp in the subfolder name\"\"\"\n",
-        "    folders = !gsutil ls $gcs_out_dir\n",
-        "    latest = \"\"\n",
+        "    folders = !gcloud storage ls $gcs_out_dir\n",        "    latest = \"\"\n",
         "    for folder in folders:\n",
         "        subfolder = folder.split(\"/\")[-2]\n",
         "        if subfolder.startswith(\"prediction-\"):\n",
@@ -1664,10 +1657,8 @@
         "            raise Exception(\"Batch Job Failed\")\n",
         "    else:\n",
         "        folder = get_latest_predictions(predictions)\n",
-        "        ! gsutil ls $folder/prediction*.csv\n",
-        "\n",
-        "        ! gsutil cat $folder/prediction*.csv\n",
-        "        break\n",
+        "        ! gcloud storage ls $folder/prediction*.csv\n",        "\n",
+        "        ! gcloud storage cat $folder/prediction*.csv\n",        "        break\n",
         "    time.sleep(60)"
       ]
     },
@@ -1761,8 +1752,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/gapic/automl/showcase_automl_tabular_binary_classification_online.ipynb

@@ -735,14 +735,11 @@
       },
       "outputs": [],
       "source": [
-        "count = ! gsutil cat $IMPORT_FILE | wc -l\n",
-        "print(\"Number of Examples\", int(count[0]))\n",
+        "count = ! gcloud storage cat $IMPORT_FILE | wc -l\n",        "print(\"Number of Examples\", int(count[0]))\n",
         "\n",
         "print(\"First 10 rows\")\n",
-        "! gsutil cat $IMPORT_FILE | head\n",
-        "\n",
-        "heading = ! gsutil cat $IMPORT_FILE | head -n1\n",
-        "label_column = str(heading).split(\",\")[-1].split(\"'\")[0]\n",
+        "! gcloud storage cat $IMPORT_FILE | head\n",        "\n",
+        "heading = ! gcloud storage cat $IMPORT_FILE | head -n1\n",        "label_column = str(heading).split(\",\")[-1].split(\"'\")[0]\n",
         "print(\"Label Column Name\", label_column)\n",
         "if label_column is None:\n",
         "    raise Exception(\"label column missing\")"
@@ -1668,8 +1665,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/gapic/automl/showcase_automl_tabular_classification_batch.ipynb

@@ -421,8 +421,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION $BUCKET_NAME"
-      ]
+        "! gcloud storage buckets create --location $REGION $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -441,8 +440,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_NAME"
-      ]
+        "! gcloud storage ls --all-versions --long $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -810,14 +808,11 @@
       },
       "outputs": [],
       "source": [
-        "count = ! gsutil cat $IMPORT_FILE | wc -l\n",
-        "print(\"Number of Examples\", int(count[0]))\n",
+        "count = ! gcloud storage cat $IMPORT_FILE | wc -l\n",        "print(\"Number of Examples\", int(count[0]))\n",
         "\n",
         "print(\"First 10 rows\")\n",
-        "! gsutil cat $IMPORT_FILE | head\n",
-        "\n",
-        "heading = ! gsutil cat $IMPORT_FILE | head -n1\n",
-        "label_column = str(heading).split(\",\")[-1].split(\"'\")[0]\n",
+        "! gcloud storage cat $IMPORT_FILE | head\n",        "\n",
+        "heading = ! gcloud storage cat $IMPORT_FILE | head -n1\n",        "label_column = str(heading).split(\",\")[-1].split(\"'\")[0]\n",
         "print(\"Label Column Name\", label_column)\n",
         "if label_column is None:\n",
         "    raise Exception(\"label column missing\")"
@@ -1363,8 +1358,7 @@
         "    f.write(str(INSTANCE_2) + \"\\n\")\n",
         "\n",
         "print(gcs_input_uri)\n",
-        "! gsutil cat $gcs_input_uri"
-      ]
+        "! gcloud storage cat $gcs_input_uri"      ]
     },
     {
       "cell_type": "markdown",
@@ -1632,8 +1626,7 @@
       "source": [
         "def get_latest_predictions(gcs_out_dir):\n",
         "    \"\"\" Get the latest prediction subfolder using the timestamp in the subfolder name\"\"\"\n",
-        "    folders = !gsutil ls $gcs_out_dir\n",
-        "    latest = \"\"\n",
+        "    folders = !gcloud storage ls $gcs_out_dir\n",        "    latest = \"\"\n",
         "    for folder in folders:\n",
         "        subfolder = folder.split(\"/\")[-2]\n",
         "        if subfolder.startswith(\"prediction-\"):\n",
@@ -1650,10 +1643,8 @@
         "            raise Exception(\"Batch Job Failed\")\n",
         "    else:\n",
         "        folder = get_latest_predictions(predictions)\n",
-        "        ! gsutil ls $folder/prediction*.csv\n",
-        "\n",
-        "        ! gsutil cat $folder/prediction*.csv\n",
-        "        break\n",
+        "        ! gcloud storage ls $folder/prediction*.csv\n",        "\n",
+        "        ! gcloud storage cat $folder/prediction*.csv\n",        "        break\n",
         "    time.sleep(60)"
       ]
     },
@@ -1747,8 +1738,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/gapic/automl/showcase_automl_tabular_classification_batch_explain.ipynb

@@ -421,8 +421,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION $BUCKET_NAME"
-      ]
+        "! gcloud storage buckets create --location $REGION $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -441,8 +440,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_NAME"
-      ]
+        "! gcloud storage ls --all-versions --long $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -810,14 +808,11 @@
       },
       "outputs": [],
       "source": [
-        "count = ! gsutil cat $IMPORT_FILE | wc -l\n",
-        "print(\"Number of Examples\", int(count[0]))\n",
+        "count = ! gcloud storage cat $IMPORT_FILE | wc -l\n",        "print(\"Number of Examples\", int(count[0]))\n",
         "\n",
         "print(\"First 10 rows\")\n",
-        "! gsutil cat $IMPORT_FILE | head\n",
-        "\n",
-        "heading = ! gsutil cat $IMPORT_FILE | head -n1\n",
-        "label_column = str(heading).split(\",\")[-1].split(\"'\")[0]\n",
+        "! gcloud storage cat $IMPORT_FILE | head\n",        "\n",
+        "heading = ! gcloud storage cat $IMPORT_FILE | head -n1\n",        "label_column = str(heading).split(\",\")[-1].split(\"'\")[0]\n",
         "print(\"Label Column Name\", label_column)\n",
         "if label_column is None:\n",
         "    raise Exception(\"label column missing\")"
@@ -1363,8 +1358,7 @@
         "    f.write(str(INSTANCE_2) + \"\\n\")\n",
         "\n",
         "print(gcs_input_uri)\n",
-        "! gsutil cat $gcs_input_uri"
-      ]
+        "! gcloud storage cat $gcs_input_uri"      ]
     },
     {
       "cell_type": "markdown",
@@ -1631,8 +1625,7 @@
       "source": [
         "def get_latest_predictions(gcs_out_dir):\n",
         "    \"\"\" Get the latest prediction subfolder using the timestamp in the subfolder name\"\"\"\n",
-        "    folders = !gsutil ls $gcs_out_dir\n",
-        "    latest = \"\"\n",
+        "    folders = !gcloud storage ls $gcs_out_dir\n",        "    latest = \"\"\n",
         "    for folder in folders:\n",
         "        subfolder = folder.split(\"/\")[-2]\n",
         "        if subfolder.startswith(\"prediction-\"):\n",
@@ -1649,10 +1642,8 @@
         "            raise Exception(\"Batch Job Failed\")\n",
         "    else:\n",
         "        folder = get_latest_predictions(predictions)\n",
-        "        ! gsutil ls $folder/explanation*.csv\n",
-        "\n",
-        "        ! gsutil cat $folder/explanation*.csv\n",
-        "        break\n",
+        "        ! gcloud storage ls $folder/explanation*.csv\n",        "\n",
+        "        ! gcloud storage cat $folder/explanation*.csv\n",        "        break\n",
         "    time.sleep(60)"
       ]
     },
@@ -1746,8 +1737,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/gapic/automl/showcase_automl_tabular_classification_export_cloud.ipynb

@@ -416,8 +416,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION $BUCKET_NAME"
-      ]
+        "! gcloud storage buckets create --location $REGION $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -436,8 +435,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_NAME"
-      ]
+        "! gcloud storage ls --all-versions --long $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -749,14 +747,11 @@
       },
       "outputs": [],
       "source": [
-        "count = ! gsutil cat $IMPORT_FILE | wc -l\n",
-        "print(\"Number of Examples\", int(count[0]))\n",
+        "count = ! gcloud storage cat $IMPORT_FILE | wc -l\n",        "print(\"Number of Examples\", int(count[0]))\n",
         "\n",
         "print(\"First 10 rows\")\n",
-        "! gsutil cat $IMPORT_FILE | head\n",
-        "\n",
-        "heading = ! gsutil cat $IMPORT_FILE | head -n1\n",
-        "label_column = str(heading).split(\",\")[-1].split(\"'\")[0]\n",
+        "! gcloud storage cat $IMPORT_FILE | head\n",        "\n",
+        "heading = ! gcloud storage cat $IMPORT_FILE | head -n1\n",        "label_column = str(heading).split(\",\")[-1].split(\"'\")[0]\n",
         "print(\"Label Column Name\", label_column)\n",
         "if label_column is None:\n",
         "    raise Exception(\"label column missing\")"
@@ -1283,15 +1278,12 @@
       "source": [
         "print(\"Model Package:\", model_package)\n",
         "print(\"Contents:\")\n",
-        "! gsutil ls $model_package\n",
-        "\n",
+        "! gcloud storage ls $model_package\n",        "\n",
         "print(\"\\nTF Saved Model\")\n",
         "path = model_package + \"/predict\"\n",
-        "files = ! gsutil ls $path\n",
-        "saved_dir = files[1]\n",
+        "files = ! gcloud storage ls $path\n",        "saved_dir = files[1]\n",
         "print(saved_dir)\n",
-        "! gsutil ls $saved_dir"
-      ]
+        "! gcloud storage ls $saved_dir"      ]
     },
     {
       "cell_type": "markdown",
@@ -1312,8 +1304,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil cp -r $model_package ."
-      ]
+        "! gcloud storage cp --recursive $model_package ."      ]
     },
     {
       "cell_type": "markdown",
@@ -1599,8 +1590,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/gapic/automl/showcase_automl_tabular_classification_online.ipynb

@@ -735,14 +735,11 @@
       },
       "outputs": [],
       "source": [
-        "count = ! gsutil cat $IMPORT_FILE | wc -l\n",
-        "print(\"Number of Examples\", int(count[0]))\n",
+        "count = ! gcloud storage cat $IMPORT_FILE | wc -l\n",        "print(\"Number of Examples\", int(count[0]))\n",
         "\n",
         "print(\"First 10 rows\")\n",
-        "! gsutil cat $IMPORT_FILE | head\n",
-        "\n",
-        "heading = ! gsutil cat $IMPORT_FILE | head -n1\n",
-        "label_column = str(heading).split(\",\")[-1].split(\"'\")[0]\n",
+        "! gcloud storage cat $IMPORT_FILE | head\n",        "\n",
+        "heading = ! gcloud storage cat $IMPORT_FILE | head -n1\n",        "label_column = str(heading).split(\",\")[-1].split(\"'\")[0]\n",
         "print(\"Label Column Name\", label_column)\n",
         "if label_column is None:\n",
         "    raise Exception(\"label column missing\")"
@@ -1645,8 +1642,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/gapic/automl/showcase_automl_tabular_classification_online_explain.ipynb

@@ -397,7 +397,6 @@
         "\n",
         "import google.cloud.aiplatform_v1beta1 as aip\n",
         "from google.protobuf import json_format\n",
-        "from google.protobuf.json_format import MessageToJson, ParseDict\n",
         "from google.protobuf.struct_pb2 import Struct, Value"
       ]
     },
@@ -735,13 +734,13 @@
       },
       "outputs": [],
       "source": [
-        "count = ! gsutil cat $IMPORT_FILE | wc -l\n",
+        "count = ! gcloud storage cat $IMPORT_FILE | wc -l\n",
         "print(\"Number of Examples\", int(count[0]))\n",
         "\n",
         "print(\"First 10 rows\")\n",
-        "! gsutil cat $IMPORT_FILE | head\n",
+        "! gcloud storage cat $IMPORT_FILE | head\n",
         "\n",
-        "heading = ! gsutil cat $IMPORT_FILE | head -n1\n",
+        "heading = ! gcloud storage cat $IMPORT_FILE | head -n1\n",
         "label_column = str(heading).split(\",\")[-1].split(\"'\")[0]\n",
         "print(\"Label Column Name\", label_column)\n",
         "if label_column is None:\n",
@@ -1820,7 +1819,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"
       ]
     }
   ],

notebooks/community/gapic/automl/showcase_automl_tabular_forecasting_batch.ipynb

@@ -421,8 +421,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION $BUCKET_NAME"
-      ]
+        "! gcloud storage buckets create --location=$REGION $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -441,8 +440,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_NAME"
-      ]
+        "! gcloud storage ls --all-versions --long $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -779,14 +777,11 @@
       },
       "outputs": [],
       "source": [
-        "count = ! gsutil cat $IMPORT_FILE | wc -l\n",
-        "print(\"Number of Examples\", int(count[0]))\n",
+        "count = ! gcloud storage cat $IMPORT_FILE | wc -l\n",        "print(\"Number of Examples\", int(count[0]))\n",
         "\n",
         "print(\"First 10 rows\")\n",
-        "! gsutil cat $IMPORT_FILE | head\n",
-        "\n",
-        "heading = ! gsutil cat $IMPORT_FILE | head -n1\n",
-        "label_column = \"deaths\"  # @param {type:\"string\"}\n",
+        "! gcloud storage cat $IMPORT_FILE | head\n",        "\n",
+        "heading = ! gcloud storage cat $IMPORT_FILE | head -n1\n",        "label_column = \"deaths\"  # @param {type:\"string\"}\n",
         "time_column = \"date\"  # @param {type:\"string\"}\n",
         "time_series_identifier_column = \"county\"  # @param {type:\"string\"}\n",
         "print(\"Label Column Name\", label_column)\n",
@@ -1358,8 +1353,7 @@
         "    f.write(str(INSTANCE_2) + \"\\n\")\n",
         "\n",
         "print(gcs_input_uri)\n",
-        "! gsutil cat $gcs_input_uri"
-      ]
+        "! gcloud storage cat $gcs_input_uri"      ]
     },
     {
       "cell_type": "markdown",
@@ -1627,8 +1621,7 @@
       "source": [
         "def get_latest_predictions(gcs_out_dir):\n",
         "    \"\"\" Get the latest prediction subfolder using the timestamp in the subfolder name\"\"\"\n",
-        "    folders = !gsutil ls $gcs_out_dir\n",
-        "    latest = \"\"\n",
+        "    folders = !gcloud storage ls $gcs_out_dir\n",        "    latest = \"\"\n",
         "    for folder in folders:\n",
         "        subfolder = folder.split(\"/\")[-2]\n",
         "        if subfolder.startswith(\"prediction-\"):\n",
@@ -1645,10 +1638,8 @@
         "            raise Exception(\"Batch Job Failed\")\n",
         "    else:\n",
         "        folder = get_latest_predictions(predictions)\n",
-        "        ! gsutil ls $folder/prediction*.csv\n",
-        "\n",
-        "        ! gsutil cat $folder/prediction*.csv\n",
-        "        break\n",
+        "        ! gcloud storage ls $folder/prediction*.csv\n",        "\n",
+        "        ! gcloud storage cat $folder/prediction*.csv\n",        "        break\n",
         "    time.sleep(60)"
       ]
     },
@@ -1742,8 +1733,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/gapic/automl/showcase_automl_tabular_regression_online_bq.ipynb

@@ -397,7 +397,6 @@
         "\n",
         "from google.cloud.aiplatform import gapic as aip\n",
         "from google.protobuf import json_format\n",
-        "from google.protobuf.json_format import MessageToJson, ParseDict\n",
         "from google.protobuf.struct_pb2 import Struct, Value"
       ]
     },
@@ -1614,7 +1613,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"
       ]
     }
   ],

notebooks/community/gapic/automl/showcase_automl_text_classification_batch.ipynb

@@ -421,8 +421,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION $BUCKET_NAME"
-      ]
+        "! gcloud storage buckets create --location $REGION $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -441,8 +440,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_NAME"
-      ]
+        "! gcloud storage ls --all-versions --long $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -881,12 +879,10 @@
         "else:\n",
         "    FILE = IMPORT_FILE\n",
         "\n",
-        "count = ! gsutil cat $FILE | wc -l\n",
-        "print(\"Number of Examples\", int(count[0]))\n",
+        "count = ! gcloud storage cat $FILE | wc -l\n",        "print(\"Number of Examples\", int(count[0]))\n",
         "\n",
         "print(\"First 10 rows\")\n",
-        "! gsutil cat $FILE | head"
-      ]
+        "! gcloud storage cat $FILE | head"      ]
     },
     {
       "cell_type": "markdown",
@@ -1314,8 +1310,7 @@
       },
       "outputs": [],
       "source": [
-        "test_items = ! gsutil cat $IMPORT_FILE | head -n2\n",
-        "if len(test_items[0]) == 3:\n",
+        "test_items = ! gcloud storage cat $IMPORT_FILE | head -n2\n",        "if len(test_items[0]) == 3:\n",
         "    _, test_item_1, test_label_1 = str(test_items[0]).split(\",\")\n",
         "    _, test_item_2, test_label_2 = str(test_items[1]).split(\",\")\n",
         "else:\n",
@@ -1371,8 +1366,7 @@
         "    f.write(json.dumps(data) + \"\\n\")\n",
         "\n",
         "print(gcs_input_uri)\n",
-        "! gsutil cat $gcs_input_uri"
-      ]
+        "! gcloud storage cat $gcs_input_uri"      ]
     },
     {
       "cell_type": "markdown",
@@ -1644,8 +1638,7 @@
       "source": [
         "def get_latest_predictions(gcs_out_dir):\n",
         "    \"\"\" Get the latest prediction subfolder using the timestamp in the subfolder name\"\"\"\n",
-        "    folders = !gsutil ls $gcs_out_dir\n",
-        "    latest = \"\"\n",
+        "    folders = !gcloud storage ls $gcs_out_dir\n",        "    latest = \"\"\n",
         "    for folder in folders:\n",
         "        subfolder = folder.split(\"/\")[-2]\n",
         "        if subfolder.startswith(\"prediction-\"):\n",
@@ -1662,10 +1655,8 @@
         "            raise Exception(\"Batch Job Failed\")\n",
         "    else:\n",
         "        folder = get_latest_predictions(predictions)\n",
-        "        ! gsutil ls $folder/prediction*.jsonl\n",
-        "\n",
-        "        ! gsutil cat $folder/prediction*.jsonl\n",
-        "        break\n",
+        "        ! gcloud storage ls $folder/prediction*.jsonl\n",        "\n",
+        ! gcloud storage cat $folder/prediction*.jsonl\n",        "        break\n",
         "    time.sleep(60)"
       ]
     },
@@ -1759,8 +1750,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/gapic/automl/showcase_automl_text_classification_online.ipynb

@@ -716,12 +716,10 @@
         "else:\n",
         "    FILE = IMPORT_FILE\n",
         "\n",
-        "count = ! gsutil cat $FILE | wc -l\n",
-        "print(\"Number of Examples\", int(count[0]))\n",
+        "count = ! gcloud storage cat $FILE | wc -l\n",        "print(\"Number of Examples\", int(count[0]))\n",
         "\n",
         "print(\"First 10 rows\")\n",
-        "! gsutil cat $FILE | head"
-      ]
+        "! gcloud storage cat $FILE | head"      ]
     },
     {
       "cell_type": "markdown",
@@ -1327,7 +1325,7 @@
       },
       "outputs": [],
       "source": [
-        "test_item = ! gsutil cat $IMPORT_FILE | head -n1\n",
+        "test_item = ! gcloud storage cat $IMPORT_FILE | head -n1\n",
         "if len(test_item[0]) == 3:\n",
         "    _, test_item, test_label = str(test_item[0]).split(\",\")\n",
         "else:\n",
@@ -1533,8 +1531,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/gapic/automl/showcase_automl_text_entity_extraction_batch.ipynb

@@ -421,7 +421,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION $BUCKET_NAME"
+        "! gcloud storage buckets create --location $REGION $BUCKET_NAME"
       ]
     },
     {
@@ -441,7 +441,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_NAME"
+        "! gcloud storage ls --all-versions --long $BUCKET_NAME"
       ]
     },
     {
@@ -478,9 +478,7 @@
         "import time\n",
         "\n",
         "from google.cloud.aiplatform import gapic as aip\n",
-        "from google.protobuf import json_format\n",
-        "from google.protobuf.json_format import MessageToJson, ParseDict\n",
-        "from google.protobuf.struct_pb2 import Struct, Value"
+        "from google.protobuf import json_format"
       ]
     },
     {
@@ -888,11 +886,11 @@
         "else:\n",
         "    FILE = IMPORT_FILE\n",
         "\n",
-        "count = ! gsutil cat $FILE | wc -l\n",
+        "count = ! gcloud storage cat $FILE | wc -l\n",
         "print(\"Number of Examples\", int(count[0]))\n",
         "\n",
         "print(\"First 10 rows\")\n",
-        "! gsutil cat $FILE | head"
+        "! gcloud storage cat $FILE | head"
       ]
     },
     {
@@ -1377,7 +1375,7 @@
         "    f.write(json.dumps(data) + \"\\n\")\n",
         "\n",
         "print(gcs_input_uri)\n",
-        "! gsutil cat $gcs_input_uri"
+        "! gcloud storage cat $gcs_input_uri"
       ]
     },
     {
@@ -1652,8 +1650,8 @@
       "outputs": [],
       "source": [
         "def get_latest_predictions(gcs_out_dir):\n",
-        "    \"\"\" Get the latest prediction subfolder using the timestamp in the subfolder name\"\"\"\n",
-        "    folders = !gsutil ls $gcs_out_dir\n",
+        "    \"\"\"Get the latest prediction subfolder using the timestamp in the subfolder name\"\"\"\n",
+        "    folders = !gcloud storage ls $gcs_out_dir\n",
         "    latest = \"\"\n",
         "    for folder in folders:\n",
         "        subfolder = folder.split(\"/\")[-2]\n",
@@ -1671,9 +1669,9 @@
         "            raise Exception(\"Batch Job Failed\")\n",
         "    else:\n",
         "        folder = get_latest_predictions(predictions)\n",
-        "        ! gsutil ls $folder/prediction*.jsonl\n",
+        "        ! gcloud storage ls $folder/prediction*.jsonl\n",
         "\n",
-        "        ! gsutil cat $folder/prediction*.jsonl\n",
+        "        ! gcloud storage cat $folder/prediction*.jsonl\n",
         "        break\n",
         "    time.sleep(60)"
       ]
@@ -1768,7 +1766,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"
       ]
     }
   ],

notebooks/community/gapic/automl/showcase_automl_text_entity_extraction_online.ipynb

@@ -723,12 +723,10 @@
         "else:\n",
         "    FILE = IMPORT_FILE\n",
         "\n",
-        "count = ! gsutil cat $FILE | wc -l\n",
-        "print(\"Number of Examples\", int(count[0]))\n",
+        "count = ! gcloud storage cat $FILE | wc -l\n",        "print(\"Number of Examples\", int(count[0]))\n",
         "\n",
         "print(\"First 10 rows\")\n",
-        "! gsutil cat $FILE | head"
-      ]
+        "! gcloud storage cat $FILE | head"      ]
     },
     {
       "cell_type": "markdown",
@@ -1544,8 +1542,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/gapic/automl/showcase_automl_text_multi-label_classification_batch.ipynb

@@ -421,8 +421,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION $BUCKET_NAME"
-      ]
+        "! gcloud storage buckets create --location=$REGION $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -441,8 +440,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_NAME"
-      ]
+        "! gcloud storage ls --all-versions --long $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -881,12 +879,10 @@
         "else:\n",
         "    FILE = IMPORT_FILE\n",
         "\n",
-        "count = ! gsutil cat $FILE | wc -l\n",
-        "print(\"Number of Examples\", int(count[0]))\n",
+        "count = ! gcloud storage cat $FILE | wc -l\n",        "print(\"Number of Examples\", int(count[0]))\n",
         "\n",
         "print(\"First 10 rows\")\n",
-        "! gsutil cat $FILE | head"
-      ]
+        "! gcloud storage cat $FILE | head"      ]
     },
     {
       "cell_type": "markdown",
@@ -1314,8 +1310,7 @@
       },
       "outputs": [],
       "source": [
-        "test_items = ! gsutil cat $IMPORT_FILE | head -n2\n",
-        "\n",
+        "test_items = ! gcloud storage cat $IMPORT_FILE | head -n2\n",        "\n",
         "cols_1 = str(test_items[0]).split(\",\")\n",
         "cols_2 = str(test_items[1]).split(\",\")\n",
         "test_item_1 = cols_1[0]\n",
@@ -1372,8 +1367,7 @@
         "    f.write(json.dumps(data) + \"\\n\")\n",
         "\n",
         "print(gcs_input_uri)\n",
-        "! gsutil cat $gcs_input_uri"
-      ]
+        "! gcloud storage cat $gcs_input_uri"      ]
     },
     {
       "cell_type": "markdown",
@@ -1645,8 +1639,7 @@
       "source": [
         "def get_latest_predictions(gcs_out_dir):\n",
         "    \"\"\" Get the latest prediction subfolder using the timestamp in the subfolder name\"\"\"\n",
-        "    folders = !gsutil ls $gcs_out_dir\n",
-        "    latest = \"\"\n",
+        "    folders = !gcloud storage ls $gcs_out_dir\n",        "    latest = \"\"\n",
         "    for folder in folders:\n",
         "        subfolder = folder.split(\"/\")[-2]\n",
         "        if subfolder.startswith(\"prediction-\"):\n",
@@ -1663,10 +1656,8 @@
         "            raise Exception(\"Batch Job Failed\")\n",
         "    else:\n",
         "        folder = get_latest_predictions(predictions)\n",
-        "        ! gsutil ls $folder/prediction*.jsonl\n",
-        "\n",
-        "        ! gsutil cat $folder/prediction*.jsonl\n",
-        "        break\n",
+        "        ! gcloud storage ls $folder/prediction*.jsonl\n",        "\n",
+        "        ! gcloud storage cat $folder/prediction*.jsonl\n",        "        break\n",
         "    time.sleep(60)"
       ]
     },
@@ -1760,8 +1751,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/gapic/automl/showcase_automl_text_multi-label_classification_online.ipynb

@@ -716,12 +716,10 @@
         "else:\n",
         "    FILE = IMPORT_FILE\n",
         "\n",
-        "count = ! gsutil cat $FILE | wc -l\n",
-        "print(\"Number of Examples\", int(count[0]))\n",
+        "count = ! gcloud storage cat $FILE | wc -l\n",        "print(\"Number of Examples\", int(count[0]))\n",
         "\n",
         "print(\"First 10 rows\")\n",
-        "! gsutil cat $FILE | head"
-      ]
+        "! gcloud storage cat $FILE | head"      ]
     },
     {
       "cell_type": "markdown",
@@ -1327,8 +1325,7 @@
       },
       "outputs": [],
       "source": [
-        "test_item = ! gsutil cat $IMPORT_FILE | head -n1\n",
-        "\n",
+        "test_item = ! gcloud storage cat $IMPORT_FILE | head -n1\n",        "\n",
         "cols = str(test_item[0]).split(\",\")\n",
         "test_item = cols[0]\n",
         "test_label = cols[1:]\n",
@@ -1533,8 +1530,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/gapic/automl/showcase_automl_text_sentiment_analysis_batch.ipynb

@@ -421,8 +421,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION $BUCKET_NAME"
-      ]
+        "! gcloud storage buckets create --location $REGION $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -441,8 +440,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_NAME"
-      ]
+        "! gcloud storage ls --all-versions --long $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -883,12 +881,10 @@
         "else:\n",
         "    FILE = IMPORT_FILE\n",
         "\n",
-        "count = ! gsutil cat $FILE | wc -l\n",
-        "print(\"Number of Examples\", int(count[0]))\n",
+        "count = ! gcloud storage cat $FILE | wc -l\n",        "print(\"Number of Examples\", int(count[0]))\n",
         "\n",
         "print(\"First 10 rows\")\n",
-        "! gsutil cat $FILE | head"
-      ]
+        "! gcloud storage cat $FILE | head"      ]
     },
     {
       "cell_type": "markdown",
@@ -1316,8 +1312,7 @@
       },
       "outputs": [],
       "source": [
-        "test_items = ! gsutil cat $IMPORT_FILE | head -n2\n",
-        "\n",
+        "test_items = ! gcloud storage cat $IMPORT_FILE | head -n2\n",        "\n",
         "if len(test_items[0]) == 4:\n",
         "    _, test_item_1, test_label_1, _ = str(test_items[0]).split(\",\")\n",
         "    _, test_item_2, test_label_2, _ = str(test_items[1]).split(\",\")\n",
@@ -1375,8 +1370,7 @@
         "    f.write(json.dumps(data) + \"\\n\")\n",
         "\n",
         "print(gcs_input_uri)\n",
-        "! gsutil cat $gcs_input_uri"
-      ]
+        "! gcloud storage cat $gcs_input_uri"      ]
     },
     {
       "cell_type": "markdown",
@@ -1643,8 +1637,7 @@
       "source": [
         "def get_latest_predictions(gcs_out_dir):\n",
         "    \"\"\" Get the latest prediction subfolder using the timestamp in the subfolder name\"\"\"\n",
-        "    folders = !gsutil ls $gcs_out_dir\n",
-        "    latest = \"\"\n",
+        "    folders = !gcloud storage ls $gcs_out_dir\n",        "    latest = \"\"\n",
         "    for folder in folders:\n",
         "        subfolder = folder.split(\"/\")[-2]\n",
         "        if subfolder.startswith(\"prediction-\"):\n",
@@ -1661,10 +1654,8 @@
         "            raise Exception(\"Batch Job Failed\")\n",
         "    else:\n",
         "        folder = get_latest_predictions(predictions)\n",
-        "        ! gsutil ls $folder/prediction*.jsonl\n",
-        "\n",
-        "        ! gsutil cat $folder/prediction*.jsonl\n",
-        "        break\n",
+        "        ! gcloud storage ls $folder/prediction*.jsonl\n",        "\n",
+        "        ! gcloud storage cat $folder/prediction*.jsonl\n",        "        break\n",
         "    time.sleep(60)"
       ]
     },
@@ -1758,8 +1749,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/gapic/automl/showcase_automl_text_sentiment_analysis_online.ipynb

@@ -718,12 +718,10 @@
         "else:\n",
         "    FILE = IMPORT_FILE\n",
         "\n",
-        "count = ! gsutil cat $FILE | wc -l\n",
-        "print(\"Number of Examples\", int(count[0]))\n",
+        "count = ! gcloud storage cat $FILE | wc -l\n",        "print(\"Number of Examples\", int(count[0]))\n",
         "\n",
         "print(\"First 10 rows\")\n",
-        "! gsutil cat $FILE | head"
-      ]
+        "! gcloud storage cat $FILE | head"      ]
     },
     {
       "cell_type": "markdown",
@@ -1329,8 +1327,7 @@
       },
       "outputs": [],
       "source": [
-        "test_item = ! gsutil cat $IMPORT_FILE | head -n1\n",
-        "if len(test_item[0]) == 3:\n",
+        "test_item = ! gcloud storage cat $IMPORT_FILE | head -n1\n",        "if len(test_item[0]) == 3:\n",
         "    _, test_item, test_label, max = str(test_item[0]).split(\",\")\n",
         "else:\n",
         "    test_item, test_label, max = str(test_item[0]).split(\",\")\n",
@@ -1534,8 +1531,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/gapic/automl/showcase_automl_video_action_recognition_batch.ipynb

@@ -420,8 +420,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION $BUCKET_NAME"
-      ]
+        "! gcloud storage buckets create --location=$REGION $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -440,8 +439,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_NAME"
-      ]
+        "! gcloud storage ls --all-versions --long $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -888,12 +886,10 @@
         "else:\n",
         "    FILE = IMPORT_FILE\n",
         "\n",
-        "count = ! gsutil cat $FILE | wc -l\n",
-        "print(\"Number of Examples\", int(count[0]))\n",
+        "count = ! gcloud storage cat $FILE | wc -l\n",        "print(\"Number of Examples\", int(count[0]))\n",
         "\n",
         "print(\"First 10 rows\")\n",
-        "! gsutil cat $FILE | head"
-      ]
+        "! gcloud storage cat $FILE | head"      ]
     },
     {
       "cell_type": "markdown",
@@ -1310,8 +1306,7 @@
         "import json\n",
         "\n",
         "import_file = IMPORT_FILES[0]\n",
-        "test_items = ! gsutil cat $import_file | head -n2\n",
-        "\n",
+        "test_items = ! gcloud storage cat $import_file | head -n2\n",        "\n",
         "cols = str(test_items[0]).split(',')\n",
         "test_item_1 = str(cols[0])\n",
         "test_label_1 = str(cols[-1])\n",
@@ -1360,8 +1355,7 @@
         "    f.write(json.dumps(data) + '\\n')\n",
         "\n",
         "print(gcs_input_uri)\n",
-        "! gsutil cat $gcs_input_uri"
-      ]
+        "! gcloud storage cat $gcs_input_uri"      ]
     },
     {
       "cell_type": "markdown",
@@ -1637,8 +1631,7 @@
       "source": [
         "def get_latest_predictions(gcs_out_dir):\n",
         "    ''' Get the latest prediction subfolder using the timestamp in the subfolder name'''\n",
-        "    folders = !gsutil ls $gcs_out_dir\n",
-        "    latest = \"\"\n",
+        "    folders = !gcloud storage ls $gcs_out_dir\n",        "    latest = \"\"\n",
         "    for folder in folders:\n",
         "        subfolder = folder.split('/')[-2]\n",
         "        if subfolder.startswith('prediction-'):\n",
@@ -1655,10 +1648,8 @@
         "            raise Exception(\"Batch Job Failed\")\n",
         "    else:\n",
         "        folder = get_latest_predictions(predictions)\n",
-        "        ! gsutil ls $folder/prediction*.jsonl\n",
-        "\n",
-        "        ! gsutil cat $folder/prediction*.jsonl\n",
-        "        break\n",
+        "        ! gcloud storage ls $folder/prediction*.jsonl\n",        "\n",
+        "        ! gcloud storage cat $folder/prediction*.jsonl\n",        "        break\n",
         "    time.sleep(60)"
       ]
     },
@@ -1752,8 +1743,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and 'BUCKET_NAME' in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/gapic/automl/showcase_automl_video_classification_batch.ipynb

@@ -420,8 +420,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION $BUCKET_NAME"
-      ]
+        "! gcloud storage buckets create --location $REGION $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -440,8 +439,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_NAME"
-      ]
+        "! gcloud storage ls --all-versions --long $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -885,12 +883,10 @@
         "else:\n",
         "    FILE = IMPORT_FILE\n",
         "\n",
-        "count = ! gsutil cat $FILE | wc -l\n",
-        "print(\"Number of Examples\", int(count[0]))\n",
+        "count = ! gcloud storage cat $FILE | wc -l\n",        "print(\"Number of Examples\", int(count[0]))\n",
         "\n",
         "print(\"First 10 rows\")\n",
-        "! gsutil cat $FILE | head"
-      ]
+        "! gcloud storage cat $FILE | head"      ]
     },
     {
       "cell_type": "markdown",
@@ -1301,8 +1297,7 @@
       },
       "outputs": [],
       "source": [
-        "test_items = ! gsutil cat $IMPORT_FILE | head -n2\n",
-        "\n",
+        "test_items = ! gcloud storage cat $IMPORT_FILE | head -n2\n",        "\n",
         "if len(test_items[0]) == 5:\n",
         "    _, test_item_1, test_label_1, _, _ = str(test_items[0]).split(',')\n",
         "    _, test_item_2, test_label_2, _, _ = str(test_items[1]).split(',')\n",
@@ -1351,8 +1346,7 @@
         "    f.write(json.dumps(data) + '\\n')\n",
         "\n",
         "print(gcs_input_uri)\n",
-        "! gsutil cat $gcs_input_uri"
-      ]
+        "! gcloud storage cat $gcs_input_uri"      ]
     },
     {
       "cell_type": "markdown",
@@ -1630,8 +1624,7 @@
       "source": [
         "def get_latest_predictions(gcs_out_dir):\n",
         "    ''' Get the latest prediction subfolder using the timestamp in the subfolder name'''\n",
-        "    folders = !gsutil ls $gcs_out_dir\n",
-        "    latest = \"\"\n",
+        "    folders = !gcloud storage ls $gcs_out_dir\n",        "    latest = \"\"\n",
         "    for folder in folders:\n",
         "        subfolder = folder.split('/')[-2]\n",
         "        if subfolder.startswith('prediction-'):\n",
@@ -1648,10 +1641,8 @@
         "            raise Exception(\"Batch Job Failed\")\n",
         "    else:\n",
         "        folder = get_latest_predictions(predictions)\n",
-        "        ! gsutil ls $folder/prediction*.jsonl\n",
-        "\n",
-        "        ! gsutil cat $folder/prediction*.jsonl\n",
-        "        break\n",
+        "        ! gcloud storage ls $folder/prediction*.jsonl\n",        "\n",
+        "! gcloud storage cat $folder/prediction*.jsonl\n",        "        break\n",
         "    time.sleep(60)"
       ]
     },
@@ -1745,8 +1736,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and 'BUCKET_NAME' in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/gapic/automl/showcase_automl_video_object_tracking_batch.ipynb

@@ -420,8 +420,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION $BUCKET_NAME"
-      ]
+        "! gcloud storage buckets create --location $REGION $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -440,8 +439,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_NAME"
-      ]
+        "! gcloud storage ls --all-versions --long $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -890,12 +888,10 @@
         "else:\n",
         "    FILE = IMPORT_FILE\n",
         "\n",
-        "count = ! gsutil cat $FILE | wc -l\n",
-        "print(\"Number of Examples\", int(count[0]))\n",
+        "count = ! gcloud storage cat $FILE | wc -l\n",        "print(\"Number of Examples\", int(count[0]))\n",
         "\n",
         "print(\"First 10 rows\")\n",
-        "! gsutil cat $FILE | head"
-      ]
+        "! gcloud storage cat $FILE | head"      ]
     },
     {
       "cell_type": "markdown",
@@ -1309,8 +1305,7 @@
       },
       "outputs": [],
       "source": [
-        "test_items = ! gsutil cat $IMPORT_FILE | head -n2\n",
-        "\n",
+        "test_items = ! gcloud storage cat $IMPORT_FILE | head -n2\n",        "\n",
         "cols_1 = test_items[0].split(',')\n",
         "cols_2 = test_items[1].split(',')\n",
         "if len(cols_1) > 12:\n",
@@ -1365,8 +1360,7 @@
         "    f.write(json.dumps(data) + '\\n')\n",
         "\n",
         "print(gcs_input_uri)\n",
-        "! gsutil cat $gcs_input_uri"
-      ]
+        "! gcloud storage cat $gcs_input_uri"      ]
     },
     {
       "cell_type": "markdown",
@@ -1638,8 +1632,7 @@
       "source": [
         "def get_latest_predictions(gcs_out_dir):\n",
         "    ''' Get the latest prediction subfolder using the timestamp in the subfolder name'''\n",
-        "    folders = !gsutil ls $gcs_out_dir\n",
-        "    latest = \"\"\n",
+        "    folders = !gcloud storage ls $gcs_out_dir\n",        "    latest = \"\"\n",
         "    for folder in folders:\n",
         "        subfolder = folder.split('/')[-2]\n",
         "        if subfolder.startswith('prediction-'):\n",
@@ -1656,10 +1649,8 @@
         "            raise Exception(\"Batch Job Failed\")\n",
         "    else:\n",
         "        folder = get_latest_predictions(predictions)\n",
-        "        ! gsutil ls $folder/prediction*.jsonl\n",
-        "\n",
-        "        ! gsutil cat $folder/prediction*.jsonl\n",
-        "        break\n",
+        "        ! gcloud storage ls $folder/prediction*.jsonl\n",        "\n",
+        "        ! gcloud storage cat $folder/prediction*.jsonl\n",        "        break\n",
         "    time.sleep(60)"
       ]
     },
@@ -1753,8 +1744,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and 'BUCKET_NAME' in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/gapic/custom/showcase_custom_text_classification_online_exported_ds.ipynb

@@ -426,8 +426,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION $BUCKET_NAME"
-      ]
+        "! gcloud storage buckets create --location=$REGION $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -446,8 +445,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_NAME"
-      ]
+        "! gcloud storage ls --all-versions --long $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -483,9 +481,6 @@
         "import time\n",
         "\n",
         "from google.cloud.aiplatform import gapic as aip\n",
-        "from google.protobuf import json_format\n",
-        "from google.protobuf.json_format import MessageToJson, ParseDict\n",
-        "from google.protobuf.struct_pb2 import Struct, Value"
       ]
     },
     {
@@ -991,12 +986,10 @@
         "else:\n",
         "    FILE = IMPORT_FILE\n",
         "\n",
-        "count = ! gsutil cat $FILE | wc -l\n",
-        "print(\"Number of Examples\", int(count[0]))\n",
+        "count = ! gcloud storage cat $FILE | wc -l\n",        "print(\"Number of Examples\", int(count[0]))\n",
         "\n",
         "print(\"First 10 rows\")\n",
-        "! gsutil cat $FILE | head"
-      ]
+        "! gcloud storage cat $FILE | head"      ]
     },
     {
       "cell_type": "markdown",
@@ -1153,8 +1146,7 @@
       "source": [
         "jsonl_index = result.exported_files[0]\n",
         "\n",
-        "! gsutil cat $jsonl_index | head"
-      ]
+        "! gcloud storage cat $jsonl_index | head"      ]
     },
     {
       "cell_type": "markdown",
@@ -1286,8 +1278,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/gapic/custom/showcase_hyperparmeter_tuning_image_classification.ipynb

@@ -419,8 +419,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION $BUCKET_NAME"
-      ]
+        "! gcloud storage buckets create --location=$REGION $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -439,8 +438,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_NAME"
-      ]
+"! gcloud storage ls --all-versions --long $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -1119,8 +1117,7 @@
         "! rm -f custom.tar custom.tar.gz\n",
         "! tar cvf custom.tar custom\n",
         "! gzip custom.tar\n",
-        "! gsutil cp custom.tar.gz $BUCKET_NAME/trainer_cifar10.tar.gz"
-      ]
+        "! gcloud storage cp custom.tar.gz $BUCKET_NAME/trainer_cifar10.tar.gz"      ]
     },
     {
       "cell_type": "markdown",
@@ -1617,8 +1614,7 @@
         "! rm -f custom.tar custom.tar.gz\n",
         "! tar cvf custom.tar custom\n",
         "! gzip custom.tar\n",
-        "! gsutil cp custom.tar.gz $BUCKET_NAME/trainer_cifar10.tar.gz"
-      ]
+        "! gcloud storage cp custom.tar.gz $BUCKET_NAME/trainer_cifar10.tar.gz"      ]
     },
     {
       "cell_type": "markdown",
@@ -2062,8 +2058,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/gapic/custom/showcase_hyperparmeter_tuning_tabular_regression.ipynb

@@ -419,8 +419,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION $BUCKET_NAME"
-      ]
+        "! gcloud storage buckets create --location $REGION $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -439,8 +438,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_NAME"
-      ]
+        "! gcloud storage ls --all-versions --long $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -1116,8 +1114,7 @@
         "! rm -f custom.tar custom.tar.gz\n",
         "! tar cvf custom.tar custom\n",
         "! gzip custom.tar\n",
-        "! gsutil cp custom.tar.gz $BUCKET_NAME/trainer_boston.tar.gz"
-      ]
+        "! gcloud storage cp custom.tar.gz $BUCKET_NAME/trainer_boston.tar.gz"      ]
     },
     {
       "cell_type": "markdown",
@@ -1626,8 +1623,7 @@
         "! rm -f custom.tar custom.tar.gz\n",
         "! tar cvf custom.tar custom\n",
         "! gzip custom.tar\n",
-        "! gsutil cp custom.tar.gz $BUCKET_NAME/trainer_boston.tar.gz"
-      ]
+"! gcloud storage cp custom.tar.gz $BUCKET_NAME/trainer_boston.tar.gz"      ]
     },
     {
       "cell_type": "markdown",
@@ -2085,8 +2081,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/gapic/custom/showcase_hyperparmeter_tuning_text_binary_classification.ipynb

@@ -419,8 +419,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION $BUCKET_NAME"
-      ]
+        "! gcloud storage buckets create --location=$REGION $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -439,8 +438,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_NAME"
-      ]
+        "! gcloud storage ls --all-versions --long $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -1116,8 +1114,7 @@
         "! rm -f custom.tar custom.tar.gz\n",
         "! tar cvf custom.tar custom\n",
         "! gzip custom.tar\n",
-        "! gsutil cp custom.tar.gz $BUCKET_NAME/trainer_imdb.tar.gz"
-      ]
+"! gcloud storage cp custom.tar.gz $BUCKET_NAME/trainer_imdb.tar.gz"      ]
     },
     {
       "cell_type": "markdown",
@@ -1618,8 +1615,7 @@
         "! rm -f custom.tar custom.tar.gz\n",
         "! tar cvf custom.tar custom\n",
         "! gzip custom.tar\n",
-        "! gsutil cp custom.tar.gz $BUCKET_NAME/trainer_imdb.tar.gz"
-      ]
+        "! gcloud storage cp custom.tar.gz $BUCKET_NAME/trainer_imdb.tar.gz"      ]
     },
     {
       "cell_type": "markdown",
@@ -2060,8 +2056,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/gapic/custom/showcase_local_image_classification_online.ipynb

@@ -423,8 +423,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION $BUCKET_NAME"
-      ]
+        "! gcloud storage buckets create --location=$REGION $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -443,8 +442,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_NAME"
-      ]
+        "! gcloud storage ls --all-versions --long $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -1718,8 +1716,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/gapic/custom/showcase_local_tabular_regression_online.ipynb

@@ -423,7 +423,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION $BUCKET_NAME"
+        "! gcloud storage buckets create --location $REGION $BUCKET_NAME"
       ]
     },
     {
@@ -443,7 +443,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_NAME"
+        "! gcloud storage ls --all-versions --long $BUCKET_NAME"
       ]
     },
     {
@@ -477,12 +477,8 @@
       },
       "outputs": [],
       "source": [
-        "import time\n",
-        "\n",
         "from google.cloud.aiplatform import gapic as aip\n",
-        "from google.protobuf import json_format\n",
-        "from google.protobuf.json_format import MessageToJson, ParseDict\n",
-        "from google.protobuf.struct_pb2 import Struct, Value"
+        "from google.protobuf import json_format"
       ]
     },
     {
@@ -1639,7 +1635,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"
       ]
     }
   ],

notebooks/community/gapic/custom/showcase_local_text_binary_classification_online.ipynb

@@ -423,7 +423,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION $BUCKET_NAME"
+        "! gcloud storage buckets create --location=$REGION $BUCKET_NAME"
       ]
     },
     {
@@ -443,7 +443,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_NAME"
+        "! gcloud storage ls --all-versions --long $BUCKET_NAME"
       ]
     },
     {
@@ -477,12 +477,8 @@
       },
       "outputs": [],
       "source": [
-        "import time\n",
-        "\n",
         "from google.cloud.aiplatform import gapic as aip\n",
-        "from google.protobuf import json_format\n",
-        "from google.protobuf.json_format import MessageToJson, ParseDict\n",
-        "from google.protobuf.struct_pb2 import Struct, Value"
+        "from google.protobuf import json_format"
       ]
     },
     {
@@ -1616,7 +1612,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"
       ]
     }
   ],

notebooks/community/gapic/custom/showcase_tfhub_image_classification_online.ipynb

@@ -422,8 +422,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION $BUCKET_NAME"
-      ]
+        "! gcloud storage buckets create --location=$REGION $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -442,8 +441,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_NAME"
-      ]
+        "! gcloud storage ls --all-versions --long $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -1244,8 +1242,7 @@
       "source": [
         "FLOWERS_CSV = \"gs://cloud-ml-data/img/flower_photos/all_data.csv\"\n",
         "\n",
-        "test_images = ! gsutil cat $FLOWERS_CSV | head -n1\n",
-        "test_image = test_images[0].split(\",\")[0]\n",
+        "test_images = ! gcloud storage cat $FLOWERS_CSV | head -n1\n",        "test_image = test_images[0].split(\",\")[0]\n",
         "print(test_image)"
       ]
     },
@@ -1471,8 +1468,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r $BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/generative_ai/bq_dataframes_llm_code_generation.ipynb

@@ -761,7 +761,7 @@
         "\n",
         "BUCKET_ID = \"code-samples-\" + str(uuid.uuid1())\n",
         "\n",
-        "!gsutil mb gs://{BUCKET_ID}"
+        "!gcloud storage buckets create gs://{BUCKET_ID}"
       ]
     },
     {
@@ -874,7 +874,7 @@
       "outputs": [],
       "source": [
         "# # Delete the Google Cloud Storage bucket and files\n",
-        "# ! gsutil rm -r gs://{BUCKET_ID}\n",
+        "# ! gcloud storage rm --recursive gs://{BUCKET_ID}\n",
         "# print(f\"Deleted bucket '{BUCKET_ID}'.\")"
       ]
     }

notebooks/community/hyperparameter_tuning/distributed-hyperparameter-tuning.ipynb

@@ -499,7 +499,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION $BUCKET_URI"
+        "! gcloud storage buckets create --location=$REGION $BUCKET_URI"
       ]
     },
     {
@@ -519,7 +519,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_URI"
+        "! gcloud storage ls --all-versions --long $BUCKET_URI"
       ]
     },
     {
@@ -955,7 +955,7 @@
         "delete_bucket = False\n",
         "\n",
         "if delete_bucket or os.getenv(\"IS_TESTING\"):\n",
-        "    ! gsutil rm -r $BUCKET_URI"
+        "    ! gcloud storage rm --recursive $BUCKET_URI"
       ]
     }
   ],

notebooks/community/managed_notebooks/recommender_systems/recommender-system-on-retail-data.ipynb

@@ -117,7 +117,7 @@
         "\n",
         "# Get your Google Cloud project ID from gcloud\n",
         "if not os.getenv(\"IS_TESTING\"):\n",
-        "    shell_output=!gcloud config list --format 'value(core.project)' 2>/dev/null\n",
+        "    shell_output = !gcloud config list --format 'value(core.project)' 2>/dev/null\n",
         "    PROJECT_ID = shell_output[0]\n",
         "    print(\"Project ID: \", PROJECT_ID)"
       ]
@@ -234,7 +234,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION $BUCKET_NAME"
+        "! gcloud storage buckets create --location $REGION $BUCKET_NAME"
       ]
     },
     {
@@ -254,7 +254,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_NAME"
+        "! gcloud storage ls --all-versions --long $BUCKET_NAME"
       ]
     },
     {
@@ -932,7 +932,7 @@
         "! bq rm -r -f -d $PROJECT:$DATASET\n",
         "\n",
         "# remove the Cloud Storage bucket created and all of its tables\n",
-        "! gsutil rm -r gs://$BUCKET_NAME"
+        "! gcloud storage rm --recursive $BUCKET_NAME"
       ]
     },
     {

notebooks/community/matching_engine/matching_engine_for_indexing.ipynb

@@ -477,8 +477,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION -p $PROJECT_ID $BUCKET_NAME"
-      ]
+        "! gcloud storage buckets create --location=$REGION --project=$PROJECT_ID $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -497,8 +496,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_NAME"
-      ]
+        "! gcloud storage ls --all-versions --long $BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -579,8 +577,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil cp gs://cloud-samples-data/vertex-ai/matching_engine/glove-100-angular.hdf5 ."
-      ]
+        "! gcloud storage cp gs://cloud-samples-data/vertex-ai/matching_engine/glove-100-angular.hdf5 ."      ]
     },
     {
       "cell_type": "markdown",
@@ -661,8 +658,7 @@
       "source": [
         "# NOTE: Everything in this Google Cloud Storage directory will be DELETED before uploading the data\n",
         "\n",
-        "! gsutil rm -raf {BUCKET_NAME}/** 2> /dev/null || true"
-      ]
+        "! gcloud storage rm --recursive --all-versions --continue-on-error {BUCKET_NAME}/** 2> /dev/null || true"      ]
     },
     {
       "cell_type": "code",
@@ -672,8 +668,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil cp glove100.json {BUCKET_NAME}/glove100.json"
-      ]
+        "! gcloud storage cp glove100.json {BUCKET_NAME}/glove100.json"      ]
     },
     {
       "cell_type": "code",
@@ -683,8 +678,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls {BUCKET_NAME}"
-      ]
+        "! gcloud storage ls {BUCKET_NAME}"      ]
     },
     {
       "cell_type": "markdown",
@@ -966,8 +960,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil cp glove100_incremental.json {BUCKET_NAME}/incremental/glove100.json"
-      ]
+        "! gcloud storage cp glove100_incremental.json {BUCKET_NAME}/incremental/glove100.json"      ]
     },
     {
       "cell_type": "markdown",
@@ -2049,8 +2042,7 @@
         "\n",
         "delete_bucket = False\n",
         "if delete_bucket or os.getenv(\"IS_TESTING\"):\n",
-        "    ! gsutil -m rm -r $BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive $BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/matching_engine/stream_update_for_matching_engine.ipynb

@@ -352,7 +352,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION $BUCKET_NAME"
+        "! gcloud storage buckets create --location $REGION $BUCKET_NAME"
       ]
     },
     {
@@ -372,7 +372,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al $BUCKET_NAME"
+        "! gcloud storage ls --all-versions --long $BUCKET_NAME"
       ]
     },
     {
@@ -460,7 +460,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil cp gs://cloud-samples-data/vertex-ai/matching_engine/glove-100-angular.hdf5 ."
+        "! gcloud storage cp gs://cloud-samples-data/vertex-ai/matching_engine/glove-100-angular.hdf5 ."
       ]
     },
     {
@@ -550,7 +550,7 @@
       "source": [
         "# NOTE: Everything in this GCS DIR will be DELETED before uploading the data.\n",
         "\n",
-        "! gsutil rm -rf {BUCKET_NAME}/*"
+        "! gcloud storage rm --recursive --continue-on-error {BUCKET_NAME}/*"
       ]
     },
     {
@@ -561,7 +561,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil cp glove100.json {BUCKET_NAME}/glove100.json"
+        "! gcloud storage cp glove100.json {BUCKET_NAME}/glove100.json"
       ]
     },
     {
@@ -572,7 +572,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls {BUCKET_NAME}"
+        "! gcloud storage ls {BUCKET_NAME}"
       ]
     },
     {

notebooks/community/migration/UJ10 Custom Training Prebuilt Container SKLearn.ipynb

@@ -325,8 +325,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION gs://$BUCKET_NAME"
-      ]
+        "! gcloud storage buckets create --location=$REGION gs://$BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -345,8 +344,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al gs://$BUCKET_NAME"
-      ]
+        "! gcloud storage ls --all-versions --long gs://$BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -722,8 +720,7 @@
         "! rm -f custom.tar custom.tar.gz\n",
         "! tar cvf custom.tar custom\n",
         "! gzip custom.tar\n",
-        "! gsutil cp custom.tar.gz gs://$BUCKET_NAME/census.tar.gz"
-      ]
+        "! gcloud storage cp custom.tar.gz gs://$BUCKET_NAME/census.tar.gz"      ]
     },
     {
       "cell_type": "markdown",
@@ -1379,8 +1376,7 @@
         "    for i in INSTANCES:\n",
         "        f.write(json.dumps(i) + \"\\n\")\n",
         "\n",
-        "! gsutil cat $gcs_input_uri"
-      ]
+        "! gcloud storage cat $gcs_input_uri"      ]
     },
     {
       "cell_type": "markdown",
@@ -1718,8 +1714,7 @@
       "source": [
         "def get_latest_predictions(gcs_out_dir):\n",
         "    \"\"\" Get the latest prediction subfolder using the timestamp in the subfolder name\"\"\"\n",
-        "    folders = !gsutil ls $gcs_out_dir\n",
-        "    latest = \"\"\n",
+        "    folders = !gcloud storage ls $gcs_out_dir\n",        "    latest = \"\"\n",
         "    for folder in folders:\n",
         "        subfolder = folder.split(\"/\")[-2]\n",
         "        if subfolder.startswith(\"prediction-\"):\n",
@@ -1738,10 +1733,8 @@
         "        folder = get_latest_predictions(\n",
         "            response.output_config.gcs_destination.output_uri_prefix\n",
         "        )\n",
-        "        ! gsutil ls $folder/prediction*\n",
-        "\n",
-        "        ! gsutil cat -h $folder/prediction*\n",
-        "        break\n",
+        "        ! gcloud storage ls $folder/prediction*\n",        "\n",
+        "        ! gcloud storage cat --display-url $folder/prediction*\n",        "        break\n",
         "    time.sleep(60)"
       ]
     },
@@ -2630,8 +2623,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r gs://$BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive gs://$BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/migration/UJ10 legacy Custom Training Prebuilt Container SKLearn.ipynb

@@ -312,7 +312,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION gs://$BUCKET_NAME"
+        "! gcloud storage buckets create --location $REGION gs://$BUCKET_NAME"
       ]
     },
     {
@@ -332,7 +332,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al gs://$BUCKET_NAME"
+        "! gcloud storage ls --all-versions --long gs://$BUCKET_NAME"
       ]
     },
     {
@@ -668,7 +668,7 @@
         "! rm -f custom.tar custom.tar.gz\n",
         "! tar cvf custom.tar custom\n",
         "! gzip custom.tar\n",
-        "! gsutil cp custom.tar.gz gs://$BUCKET_NAME/census.tar.gz"
+        "! gcloud storage cp custom.tar.gz gs://$BUCKET_NAME/census.tar.gz"
       ]
     },
     {
@@ -1923,7 +1923,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r gs://$BUCKET_NAME"
+        "    ! gcloud storage rm --recursive gs://$BUCKET_NAME"
       ]
     }
   ],

notebooks/community/migration/UJ11 HyperParameter Tuning Training Job with TensorFlow.ipynb

@@ -325,7 +325,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION gs://$BUCKET_NAME"
+        "! gcloud storage buckets create --location=$REGION gs://$BUCKET_NAME"
       ]
     },
     {
@@ -345,7 +345,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al gs://$BUCKET_NAME"
+        "! gcloud storage ls --all-versions --long gs://$BUCKET_NAME"
       ]
     },
     {
@@ -383,10 +383,7 @@
         "import sys\n",
         "import time\n",
         "\n",
-        "from google.cloud.aiplatform import gapic as aip\n",
-        "from google.protobuf import json_format\n",
-        "from google.protobuf.json_format import MessageToJson, ParseDict\n",
-        "from google.protobuf.struct_pb2 import Struct, Value"
+        "from google.cloud.aiplatform import gapic as aip"
       ]
     },
     {
@@ -671,7 +668,7 @@
         "! rm -f custom.tar custom.tar.gz\n",
         "! tar cvf custom.tar custom\n",
         "! gzip custom.tar\n",
-        "! gsutil cp custom.tar.gz gs://$BUCKET_NAME/hpt_boston_housing.tar.gz"
+        "! gcloud storage cp custom.tar.gz gs://$BUCKET_NAME/hpt_boston_housing.tar.gz"
       ]
     },
     {
@@ -1354,13 +1351,13 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r gs://$BUCKET_NAME"
+        "    ! gcloud storage rm --recursive gs://$BUCKET_NAME"
       ]
     }
   ],
   "metadata": {
     "colab": {
-      "name": "UJ11 unified HyperParameter Tuning Training Job with TensorFlow.ipynb",
+      "name": "UJ11 HyperParameter Tuning Training Job with TensorFlow.ipynb",
       "toc_visible": true
     },
     "kernelspec": {

notebooks/community/migration/UJ11 legacy HyperParameter Tuning Training Job with TensorFlow.ipynb

@@ -312,7 +312,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION gs://$BUCKET_NAME"
+        "! gcloud storage buckets create --location $REGION gs://$BUCKET_NAME"
       ]
     },
     {
@@ -332,7 +332,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al gs://$BUCKET_NAME"
+        "! gcloud storage ls --all-versions --long gs://$BUCKET_NAME"
       ]
     },
     {
@@ -614,7 +614,7 @@
         "! rm -f custom.tar custom.tar.gz\n",
         "! tar cvf custom.tar custom\n",
         "! gzip custom.tar\n",
-        "! gsutil cp custom.tar.gz gs://$BUCKET_NAME/hpt_boston_housing.tar.gz"
+        "! gcloud storage cp custom.tar.gz gs://$BUCKET_NAME/hpt_boston_housing.tar.gz"
       ]
     },
     {
@@ -1370,7 +1370,7 @@
         "delete_bucket = True\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r gs://$BUCKET_NAME"
+        "    ! gcloud storage rm --recursive gs://$BUCKET_NAME"
       ]
     }
   ],

notebooks/community/migration/UJ13 Data Labeling task.ipynb

@@ -325,7 +325,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION gs://$BUCKET_NAME"
+        "! gcloud storage buckets create --location $REGION gs://$BUCKET_NAME"
       ]
     },
     {
@@ -345,7 +345,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al gs://$BUCKET_NAME"
+        "! gcloud storage ls --all-versions --long gs://$BUCKET_NAME"
       ]
     },
     {
@@ -384,9 +384,7 @@
         "import time\n",
         "\n",
         "from google.cloud.aiplatform import gapic as aip\n",
-        "from google.protobuf import json_format\n",
-        "from google.protobuf.json_format import MessageToJson, ParseDict\n",
-        "from google.protobuf.struct_pb2 import Struct, Value"
+        "from google.protobuf import json_format\n"
       ]
     },
     {
@@ -513,7 +511,7 @@
         "IMPORT_FILE = \"gs://\" + BUCKET_NAME + \"/labeling.csv\"\n",
         "with tf.io.gfile.GFile(IMPORT_FILE, \"w\") as f:\n",
         "    for lf in LABELING_FILES:\n",
-        "        ! wget {lf} | gsutil cp {lf.split(\"/\")[-1]} gs://{BUCKET_NAME}\n",
+        "        ! wget {lf} | gcloud storage cp {lf.split(\"/\")[-1]} gs://{BUCKET_NAME}\n",
         "        f.write(\"gs://\" + BUCKET_NAME + \"/\" + lf.split(\"/\")[-1] + \"\\n\")"
       ]
     },
@@ -525,7 +523,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil cat $IMPORT_FILE"
+        "! gcloud storage cat $IMPORT_FILE"
       ]
     },
     {
@@ -1007,7 +1005,7 @@
       "outputs": [],
       "source": [
         "# create placeholder file for valid PDF file with instruction for data labeling\n",
-        "! echo \"this is instruction\" >> instruction.txt | gsutil cp instruction.txt gs://$BUCKET_NAME"
+        "! echo \"this is instruction\" >> instruction.txt | gcloud storage cp instruction.txt gs://$BUCKET_NAME"
       ]
     },
     {
@@ -1382,7 +1380,7 @@
         "\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r gs://$BUCKET_NAME"
+        "    ! gcloud storage rm --recursive gs://$BUCKET_NAME"
       ]
     }
   ],
@@ -1450,7 +1448,7 @@
         "v6isqzPQ_jAw",
         "ZCyd1qAb_jAx"
       ],
-      "name": "UJ13 unified Data Labeling task.ipynb",
+      "name": "UJ13 Data Labeling task.ipynb",
       "toc_visible": true
     },
     "kernelspec": {

notebooks/community/migration/UJ14 AutoML for vision with Vertex AI Video Classification.ipynb

@@ -325,8 +325,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION gs://$BUCKET_NAME"
-      ]
+        "! gcloud storage buckets create --location $REGION gs://$BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -345,8 +344,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al gs://$BUCKET_NAME"
-      ]
+        "! gcloud storage ls --all-versions --long gs://$BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -542,8 +540,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil cat $IMPORT_FILE | head -n 10"
-      ]
+        "! gcloud storage cat $IMPORT_FILE | head -n 10"      ]
     },
     {
       "cell_type": "markdown",
@@ -1435,8 +1432,7 @@
       },
       "outputs": [],
       "source": [
-        "test_items = ! gsutil cat $IMPORT_FILE | head -n2\n",
-        "\n",
+        "test_items = ! gcloud storage cat $IMPORT_FILE | head -n2\n",        "\n",
         "cols = str(test_items[0]).split(\",\")\n",
         "test_item_1 = str(cols[0])\n",
         "test_label_1 = str(cols[1])\n",
@@ -1510,8 +1506,7 @@
         "\n",
         "print(gcs_input_uri)\n",
         "\n",
-        "!gsutil cat $gcs_input_uri"
-      ]
+        "!gcloud storage cat $gcs_input_uri"      ]
     },
     {
       "cell_type": "markdown",
@@ -1842,8 +1837,7 @@
       "source": [
         "def get_latest_predictions(gcs_out_dir):\n",
         "    \"\"\" Get the latest prediction subfolder using the timestamp in the subfolder name\"\"\"\n",
-        "    folders = !gsutil ls $gcs_out_dir\n",
-        "    latest = \"\"\n",
+        "    folders = !gcloud storage ls $gcs_out_dir\n",        "    latest = \"\"\n",
         "    for folder in folders:\n",
         "        subfolder = folder.split(\"/\")[-2]\n",
         "        if subfolder.startswith(\"prediction-\"):\n",
@@ -1862,10 +1856,8 @@
         "        folder = get_latest_predictions(\n",
         "            response.output_config.gcs_destination.output_uri_prefix\n",
         "        )\n",
-        "        ! gsutil ls $folder/prediction*.jsonl\n",
-        "\n",
-        "        ! gsutil cat $folder/prediction*.jsonl\n",
-        "        break\n",
+        "        ! gcloud storage ls $folder/prediction*.jsonl\n",        "\n",
+        "        ! gcloud storage cat $folder/prediction*.jsonl\n",        "        break\n",
         "    time.sleep(60)"
       ]
     },
@@ -1941,8 +1933,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r gs://$BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive gs://$BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/migration/UJ15 AutoML for vision with Vertex AI Video Object Tracking.ipynb

@@ -325,8 +325,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION gs://$BUCKET_NAME"
-      ]
+        "! gcloud storage buckets create --location=$REGION gs://$BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -345,8 +344,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al gs://$BUCKET_NAME"
-      ]
+        "! gcloud storage ls --all-versions --long gs://$BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -542,8 +540,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil cat $IMPORT_FILE | head -n 10"
-      ]
+        "! gcloud storage cat $IMPORT_FILE | head -n 10"      ]
     },
     {
       "cell_type": "markdown",
@@ -1386,8 +1383,7 @@
       },
       "outputs": [],
       "source": [
-        "test_items = ! gsutil cat $IMPORT_FILE | head -n25\n",
-        "\n",
+        "test_items = ! gcloud storage cat $IMPORT_FILE | head -n25\n",        "\n",
         "cols_1 = test_items[0].split(\",\")\n",
         "cols_2 = test_items[-1].split(\",\")\n",
         "\n",
@@ -1466,8 +1462,7 @@
         "    f.write(json.dumps(data) + \"\\n\")\n",
         "\n",
         "print(gcs_input_uri)\n",
-        "!gsutil cat $gcs_input_uri"
-      ]
+        "!gcloud storage cat $gcs_input_uri"      ]
     },
     {
       "cell_type": "markdown",
@@ -1783,8 +1778,7 @@
       "source": [
         "def get_latest_predictions(gcs_out_dir):\n",
         "    \"\"\" Get the latest prediction subfolder using the timestamp in the subfolder name\"\"\"\n",
-        "    folders = !gsutil ls $gcs_out_dir\n",
-        "    latest = \"\"\n",
+        "    folders = !gcloud storage ls $gcs_out_dir\n",        "    latest = \"\"\n",
         "    for folder in folders:\n",
         "        subfolder = folder.split(\"/\")[-2]\n",
         "        if subfolder.startswith(\"prediction-\"):\n",
@@ -1803,10 +1797,8 @@
         "        folder = get_latest_predictions(\n",
         "            response.output_config.gcs_destination.output_uri_prefix\n",
         "        )\n",
-        "        ! gsutil ls $folder/prediction**\n",
-        "\n",
-        "        ! gsutil cat $folder/prediction**\n",
-        "        break\n",
+        "        ! gcloud storage ls $folder/prediction**\n",        "\n",
+        "        ! gcloud storage cat $folder/prediction**\n",        "        break\n",
         "    time.sleep(60)"
       ]
     },
@@ -1882,8 +1874,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r gs://$BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive gs://$BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/migration/UJ2,12 Custom Training Prebuilt Container TF Keras.ipynb

@@ -325,8 +325,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION gs://$BUCKET_NAME"
-      ]
+        "! gcloud storage buckets create --location $REGION gs://$BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -345,8 +344,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al gs://$BUCKET_NAME"
-      ]
+        "! gcloud storage ls --all-versions --long gs://$BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -659,8 +657,7 @@
         "! rm -f cifar.tar cifar.tar.gz\n",
         "! tar cvf cifar.tar cifar\n",
         "! gzip cifar.tar\n",
-        "! gsutil cp cifar.tar.gz gs://$BUCKET_NAME/trainer_cifar.tar.gz"
-      ]
+        "! gcloud storage cp cifar.tar.gz gs://$BUCKET_NAME/trainer_cifar.tar.gz"      ]
     },
     {
       "cell_type": "markdown",
@@ -1318,8 +1315,7 @@
         "    b64str = base64.b64encode(bytes.numpy()).decode(\"utf-8\")\n",
         "    f.write(json.dumps({input_name: {\"b64\": b64str}}) + \"\\n\")\n",
         "\n",
-        "! gsutil cat $gcs_input_uri"
-      ]
+        "! gcloud storage cat $gcs_input_uri"      ]
     },
     {
       "cell_type": "markdown",
@@ -1643,8 +1639,7 @@
       "source": [
         "def get_latest_predictions(gcs_out_dir):\n",
         "    \"\"\" Get the latest prediction subfolder using the timestamp in the subfolder name\"\"\"\n",
-        "    folders = !gsutil ls $gcs_out_dir\n",
-        "    latest = \"\"\n",
+        "    folders = !gcloud storage ls $gcs_out_dir\n",        "    latest = \"\"\n",
         "    for folder in folders:\n",
         "        subfolder = folder.split(\"/\")[-2]\n",
         "        if subfolder.startswith(\"prediction-\"):\n",
@@ -1663,10 +1658,8 @@
         "        folder = get_latest_predictions(\n",
         "            response.output_config.gcs_destination.output_uri_prefix\n",
         "        )\n",
-        "        ! gsutil ls $folder/prediction*\n",
-        "\n",
-        "        ! gsutil cat $folder/prediction*\n",
-        "        break\n",
+        "        ! gcloud storage ls $folder/prediction*\n",        "\n",
+        "        ! gcloud storage cat $folder/prediction*\n",        "        break\n",
         "    time.sleep(60)"
       ]
     },
@@ -2234,8 +2227,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r gs://$BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive gs://$BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/migration/UJ2,12 legacy Custom Training Prebuilt Container TF Keras.ipynb

@@ -308,8 +308,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION gs://$BUCKET_NAME"
-      ]
+        "! gcloud storage buckets create --location=$REGION gs://$BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -328,8 +327,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al gs://$BUCKET_NAME"
-      ]
+        "! gcloud storage ls --all-versions --long gs://$BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -586,8 +584,7 @@
         "! rm -f cifar.tar cifar.tar.gz\n",
         "! tar cvf cifar.tar cifar\n",
         "! gzip cifar.tar\n",
-        "! gsutil cp cifar.tar.gz gs://$BUCKET_NAME/trainer_cifar.tar.gz"
-      ]
+        "! gcloud storage cp cifar.tar.gz gs://$BUCKET_NAME/trainer_cifar.tar.gz"      ]
     },
     {
       "cell_type": "markdown",
@@ -1071,8 +1068,7 @@
         "        b64str = base64.b64encode(bytes.numpy()).decode(\"utf-8\")\n",
         "        f.write(json.dumps({\"key\": img, input_name: {\"b64\": b64str}}) + \"\\n\")\n",
         "\n",
-        "! gsutil cat $gcs_input_uri"
-      ]
+        "! gcloud storage cat $gcs_input_uri"      ]
     },
     {
       "cell_type": "markdown",
@@ -1361,10 +1357,8 @@
         "            break\n",
         "    else:\n",
         "        folder = response[\"predictionInput\"][\"outputPath\"][:-1]\n",
-        "        ! gsutil ls $folder/prediction*\n",
-        "\n",
-        "        ! gsutil cat $folder/prediction*\n",
-        "        break\n",
+        "        ! gcloud storage ls $folder/prediction*\n",        "\n",
+        "        ! gcloud storage cat $folder/prediction*\n",        "        break\n",
         "    time.sleep(60)"
       ]
     },
@@ -2046,8 +2040,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r gs://$BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive gs://$BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/migration/UJ3 Custom Training Custom Container TF Keras.ipynb

@@ -325,8 +325,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION gs://$BUCKET_NAME"
-      ]
+        "! gcloud storage buckets create --location=$REGION gs://$BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -345,8 +344,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al gs://$BUCKET_NAME"
-      ]
+        "! gcloud storage ls --all-versions --long gs://$BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -1338,9 +1336,7 @@
         "cv2.imwrite(\"tmp1.jpg\", (test_image_1 * 255).astype(np.uint8))\n",
         "cv2.imwrite(\"tmp2.jpg\", (test_image_2 * 255).astype(np.uint8))\n",
         "\n",
-        "! gsutil cp tmp1.jpg gs://$BUCKET_NAME/tmp1.jpg\n",
-        "! gsutil cp tmp2.jpg gs://$BUCKET_NAME/tmp2.jpg\n",
-        "\n",
+        "! gcloud storage cp tmp1.jpg gs://$BUCKET_NAME/tmp1.jpg\n",        "! gcloud storage cp tmp2.jpg gs://$BUCKET_NAME/tmp2.jpg\n",        "\n",
         "test_item_1 = \"gs://\" + BUCKET_NAME + \"/\" + \"tmp1.jpg\"\n",
         "test_item_2 = \"gs://\" + BUCKET_NAME + \"/\" + \"tmp2.jpg\""
       ]
@@ -1382,8 +1378,7 @@
         "    data = {input_name: {\"b64\": b64str}}\n",
         "    f.write(json.dumps(data) + \"\\n\")\n",
         "\n",
-        "! gsutil cat $gcs_input_uri"
-      ]
+        "! gcloud storage cat $gcs_input_uri"      ]
     },
     {
       "cell_type": "markdown",
@@ -1706,8 +1701,7 @@
       "source": [
         "def get_latest_predictions(gcs_out_dir):\n",
         "    \"\"\" Get the latest prediction subfolder using the timestamp in the subfolder name\"\"\"\n",
-        "    folders = !gsutil ls $gcs_out_dir\n",
-        "    latest = \"\"\n",
+        "    folders = !gcloud storage ls $gcs_out_dir\n",        "    latest = \"\"\n",
         "    for folder in folders:\n",
         "        subfolder = folder.split(\"/\")[-2]\n",
         "        if subfolder.startswith(\"prediction-\"):\n",
@@ -1726,10 +1720,8 @@
         "        folder = get_latest_predictions(\n",
         "            response.output_config.gcs_destination.output_uri_prefix\n",
         "        )\n",
-        "        ! gsutil ls $folder/prediction*\n",
-        "\n",
-        "        ! gsutil cat $folder/prediction*\n",
-        "        break\n",
+        ! gcloud storage ls $folder/prediction*\n",        "\n",
+        ! gcloud storage cat $folder/prediction*\n",        "        break\n",
         "    time.sleep(60)"
       ]
     },
@@ -2306,8 +2298,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r gs://$BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive gs://$BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/migration/UJ3 legacy Custom Training Custom Container TF Keras.ipynb

@@ -289,8 +289,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION gs://$BUCKET_NAME"
-      ]
+        "! gcloud storage buckets create gs://$BUCKET_NAME --location $REGION"      ]
     },
     {
       "cell_type": "markdown",
@@ -309,8 +308,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al gs://$BUCKET_NAME"
-      ]
+        "! gcloud storage ls --all-versions --long gs://$BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -1016,8 +1014,7 @@
         "        b64str = base64.b64encode(bytes.numpy()).decode(\"utf-8\")\n",
         "        f.write(json.dumps({\"key\": img, input_name: {\"b64\": b64str}}) + \"\\n\")\n",
         "\n",
-        "! gsutil cat $gcs_input_uri"
-      ]
+        "! gcloud storage cat $gcs_input_uri"      ]
     },
     {
       "cell_type": "markdown",
@@ -1300,10 +1297,9 @@
         "            break\n",
         "    else:\n",
         "        folder = response[\"predictionInput\"][\"outputPath\"][:-1]\n",
-        "        ! gsutil ls $folder/prediction*\n",
+        "        ! gcloud storage ls $folder/prediction*\n",
         "\n",
-        "        ! gsutil cat $folder/prediction*\n",
-        "        break\n",
+        "        ! gcloud storage cat $folder/prediction*\n",        "        break\n",
         "    time.sleep(60)"
       ]
     },
@@ -1982,8 +1978,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r gs://$BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive gs://$BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/migration/UJ4 AutoML for structured data with Vertex AI Regression.ipynb

@@ -325,7 +325,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION gs://$BUCKET_NAME"
+        "! gcloud storage buckets create --location $REGION gs://$BUCKET_NAME"
       ]
     },
     {
@@ -345,7 +345,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al gs://$BUCKET_NAME"
+        "! gcloud storage ls --all-versions --long gs://$BUCKET_NAME"
       ]
     },
     {
@@ -385,7 +385,6 @@
         "\n",
         "from google.cloud.aiplatform import gapic as aip\n",
         "from google.protobuf import json_format\n",
-        "from google.protobuf.json_format import MessageToJson, ParseDict\n",
         "from google.protobuf.struct_pb2 import Struct, Value"
       ]
     },
@@ -545,7 +544,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil cat $IMPORT_FILE | head -n 10"
+        "! gcloud storage cat $IMPORT_FILE | head -n 10"
       ]
     },
     {
@@ -1493,14 +1492,14 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil cat $IMPORT_FILE | head -n 1 > tmp.csv\n",
-        "! gsutil cat $IMPORT_FILE | tail -n 10 >> tmp.csv\n",
+        "! gcloud storage cat $IMPORT_FILE | head -n 1 > tmp.csv\n",
+        "! gcloud storage cat $IMPORT_FILE | tail -n 10 >> tmp.csv\n",
         "\n",
         "! cut -d, -f1-16 tmp.csv > batch.csv\n",
         "\n",
         "gcs_input_uri = \"gs://\" + BUCKET_NAME + \"/test.csv\"\n",
         "\n",
-        "! gsutil cp batch.csv $gcs_input_uri"
+        "! gcloud storage cp batch.csv $gcs_input_uri"
       ]
     },
     {
@@ -1511,7 +1510,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil cat $gcs_input_uri"
+        "! gcloud storage cat $gcs_input_uri"
       ]
     },
     {
@@ -1818,8 +1817,8 @@
       "outputs": [],
       "source": [
         "def get_latest_predictions(gcs_out_dir):\n",
-        "    \"\"\" Get the latest prediction subfolder using the timestamp in the subfolder name\"\"\"\n",
-        "    folders = !gsutil ls $gcs_out_dir\n",
+        "    \"\"\"Get the latest prediction subfolder using the timestamp in the subfolder name\"\"\"\n",
+        "    folders = !gcloud storage ls $gcs_out_dir\n",
         "    latest = \"\"\n",
         "    for folder in folders:\n",
         "        subfolder = folder.split(\"/\")[-2]\n",
@@ -1839,9 +1838,9 @@
         "        folder = get_latest_predictions(\n",
         "            response.output_config.gcs_destination.output_uri_prefix\n",
         "        )\n",
-        "        ! gsutil ls $folder/prediction*\n",
+        "        ! gcloud storage ls $folder/prediction*\n",
         "\n",
-        "        ! gsutil cat $folder/prediction*\n",
+        "        ! gcloud storage cat $folder/prediction*\n",
         "        break\n",
         "    time.sleep(60)"
       ]
@@ -2452,7 +2451,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r gs://$BUCKET_NAME"
+        "    ! gcloud storage rm --recursive gs://$BUCKET_NAME"
       ]
     }
   ],
@@ -2469,7 +2468,7 @@
         "call:migration",
         "response:migration"
       ],
-      "name": "UJ4 unified AutoML for structured data with Vertex AI Regression.ipynb",
+      "name": "UJ4 AutoML for structured data with Vertex AI Regression.ipynb",
       "toc_visible": true
     },
     "kernelspec": {

notebooks/community/migration/UJ5 AutoML for vision with Vertex AI Video Classification.ipynb

@@ -325,7 +325,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION gs://$BUCKET_NAME"
+        "! gcloud storage buckets create --location $REGION gs://$BUCKET_NAME"
       ]
     },
     {
@@ -345,7 +345,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al gs://$BUCKET_NAME"
+        "! gcloud storage ls --all-versions --long gs://$BUCKET_NAME"
       ]
     },
     {
@@ -385,7 +385,6 @@
         "\n",
         "from google.cloud.aiplatform import gapic as aip\n",
         "from google.protobuf import json_format\n",
-        "from google.protobuf.json_format import MessageToJson, ParseDict\n",
         "from google.protobuf.struct_pb2 import Struct, Value"
       ]
     },
@@ -542,7 +541,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil cat $IMPORT_FILE | head -n 10"
+        "! gcloud storage cat $IMPORT_FILE | head -n 10"
       ]
     },
     {
@@ -1428,7 +1427,7 @@
       },
       "outputs": [],
       "source": [
-        "test_items = ! gsutil cat $IMPORT_FILE | head -n2\n",
+        "test_items = ! gcloud storage cat $IMPORT_FILE | head -n2\n",
         "\n",
         "test_item_1, test_label_1 = test_items[0].split(\",\")[1], test_items[0].split(\",\")[2]\n",
         "test_item_2, test_label_2 = test_items[0].split(\",\")[1], test_items[0].split(\",\")[2]\n",
@@ -1436,8 +1435,8 @@
         "file_1 = test_item_1.split(\"/\")[-1]\n",
         "file_2 = test_item_2.split(\"/\")[-1]\n",
         "\n",
-        "! gsutil cp $test_item_1 gs://$BUCKET_NAME/$file_1\n",
-        "! gsutil cp $test_item_2 gs://$BUCKET_NAME/$file_2\n",
+        "! gcloud storage cp $test_item_1 gs://$BUCKET_NAME/$file_1\n",
+        "! gcloud storage cp $test_item_2 gs://$BUCKET_NAME/$file_2\n",
         "\n",
         "test_item_1 = \"gs://\" + BUCKET_NAME + \"/\" + file_1\n",
         "test_item_2 = \"gs://\" + BUCKET_NAME + \"/\" + file_2\n",
@@ -1478,7 +1477,7 @@
         "    data = {\"content\": test_item_2, \"mime_type\": \"image/jpeg\"}\n",
         "    f.write(json.dumps(data) + \"\\n\")\n",
         "\n",
-        "!gsutil cat $gcs_input_uri"
+        "!gcloud storage cat $gcs_input_uri"
       ]
     },
     {
@@ -1799,8 +1798,8 @@
       "outputs": [],
       "source": [
         "def get_latest_predictions(gcs_out_dir):\n",
-        "    \"\"\" Get the latest prediction subfolder using the timestamp in the subfolder name\"\"\"\n",
-        "    folders = !gsutil ls $gcs_out_dir\n",
+        "    \"\"\"Get the latest prediction subfolder using the timestamp in the subfolder name\"\"\"\n",
+        "    folders = !gcloud storage ls $gcs_out_dir\n",
         "    latest = \"\"\n",
         "    for folder in folders:\n",
         "        subfolder = folder.split(\"/\")[-2]\n",
@@ -1820,9 +1819,9 @@
         "        folder = get_latest_predictions(\n",
         "            response.output_config.gcs_destination.output_uri_prefix\n",
         "        )\n",
-        "        ! gsutil ls $folder/prediction*.jsonl\n",
+        "        ! gcloud storage ls $folder/prediction*.jsonl\n",
         "\n",
-        "        ! gsutil cat $folder/prediction*.jsonl\n",
+        "        ! gcloud storage cat $folder/prediction*.jsonl\n",
         "        break\n",
         "    time.sleep(60)"
       ]
@@ -2172,7 +2171,7 @@
         "\n",
         "import tensorflow as tf\n",
         "\n",
-        "single_file = ! gsutil cat $IMPORT_FILE | head -n 1\n",
+        "single_file = ! gcloud storage cat $IMPORT_FILE | head -n 1\n",
         "single_file = single_file[0].split(\",\")[1]\n",
         "\n",
         "with tf.io.gfile.GFile(single_file, \"rb\") as f:\n",
@@ -2443,7 +2442,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r gs://$BUCKET_NAME"
+        "    ! gcloud storage rm --recursive gs://$BUCKET_NAME"
       ]
     }
   ],
@@ -2467,7 +2466,7 @@
         "_RXG0aaSV2HS",
         "EDuJAyzbV2HW"
       ],
-      "name": "UJ5 unified AutoML for vision with Vertex AI Video Classification.ipynb",
+      "name": "UJ5 AutoML for vision with Vertex AI Video Classification.ipynb",
       "toc_visible": true
     },
     "kernelspec": {

notebooks/community/migration/UJ6 AutoML for natural language with Vertex AI Text Classification.ipynb

@@ -325,7 +325,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION gs://$BUCKET_NAME"
+        "! gcloud storage buckets create --location $REGION gs://$BUCKET_NAME"
       ]
     },
     {
@@ -345,7 +345,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al gs://$BUCKET_NAME"
+        "! gcloud storage ls --all-versions --long gs://$BUCKET_NAME"
       ]
     },
     {
@@ -379,16 +379,13 @@
       },
       "outputs": [],
       "source": [
-        "import base64\n",
         "import json\n",
         "import os\n",
         "import sys\n",
         "import time\n",
         "\n",
         "from google.cloud.aiplatform import gapic as aip\n",
-        "from google.protobuf import json_format\n",
-        "from google.protobuf.json_format import MessageToJson, ParseDict\n",
-        "from google.protobuf.struct_pb2 import Struct, Value"
+        "from google.protobuf import json_format"
       ]
     },
     {
@@ -543,7 +540,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil cat $IMPORT_FILE | head -n 10"
+        "! gcloud storage cat $IMPORT_FILE | head -n 10"
       ]
     },
     {
@@ -1552,7 +1549,7 @@
       },
       "outputs": [],
       "source": [
-        "test_item = ! gsutil cat $IMPORT_FILE | head -n1\n",
+        "test_item = ! gcloud storage cat $IMPORT_FILE | head -n1\n",
         "test_item, test_label = str(test_item[0]).split(\",\")\n",
         "\n",
         "print(test_item, test_label)"
@@ -1614,8 +1611,8 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil cat $gcs_input_uri\n",
-        "! gsutil cat $test_item_uri"
+        "! gcloud storage cat $gcs_input_uri\n",
+        "! gcloud storage cat $test_item_uri"
       ]
     },
     {
@@ -1916,8 +1913,8 @@
       "outputs": [],
       "source": [
         "def get_latest_predictions(gcs_out_dir):\n",
-        "    \"\"\" Get the latest prediction subfolder using the timestamp in the subfolder name\"\"\"\n",
-        "    folders = !gsutil ls $gcs_out_dir\n",
+        "    \"\"\"Get the latest prediction subfolder using the timestamp in the subfolder name\"\"\"\n",
+        "    folders = !gcloud storage ls $gcs_out_dir\n",
         "    latest = \"\"\n",
         "    for folder in folders:\n",
         "        subfolder = folder.split(\"/\")[-2]\n",
@@ -1937,9 +1934,9 @@
         "        folder = get_latest_predictions(\n",
         "            response.output_config.gcs_destination.output_uri_prefix\n",
         "        )\n",
-        "        ! gsutil ls $folder/prediction*.jsonl\n",
+        "        ! gcloud storage ls $folder/prediction*.jsonl\n",
         "\n",
-        "        ! gsutil cat $folder/prediction*.jsonl\n",
+        "        ! gcloud storage cat $folder/prediction*.jsonl\n",
         "        break\n",
         "    time.sleep(60)"
       ]
@@ -2260,7 +2257,7 @@
       },
       "outputs": [],
       "source": [
-        "test_item = ! gsutil cat $IMPORT_FILE | head -n1\n",
+        "test_item = ! gcloud storage cat $IMPORT_FILE | head -n1\n",
         "test_item, test_label = str(test_item[0]).split(\",\")\n",
         "\n",
         "instances_list = [{\"content\": test_item}]\n",
@@ -2510,7 +2507,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r gs://$BUCKET_NAME"
+        "    ! gcloud storage rm --recursive gs://$BUCKET_NAME"
       ]
     }
   ],
@@ -2522,7 +2519,7 @@
         "hIHTX-pkJjkO",
         "4x_t-MWnJjkQ"
       ],
-      "name": "UJ6 unified AutoML for natural language with Vertex AI Text Classification.ipynb",
+      "name": "UJ6 AutoML for natural language with Vertex AI Text Classification.ipynb",
       "toc_visible": true
     },
     "kernelspec": {

notebooks/community/migration/UJ6 legacy AutoML Natural Language Text Classification.ipynb

@@ -109,27 +109,27 @@
         "id": "Af0jTPSgl9yh"
       },
       "source": [
-        "## Before you begin\r\n",
-        "\r\n",
-        "### GPU run-time\r\n",
-        "\r\n",
-        "*Make sure you're running this notebook in a GPU runtime if you have that option. In Colab, select* **Runtime > Change Runtime Type > GPU**\r\n",
-        "\r\n",
-        "### Set up your GCP project\r\n",
-        "\r\n",
-        "**The following steps are required, regardless of your notebook environment.**\r\n",
-        "\r\n",
-        "1. [Select or create a GCP project](https://console.cloud.google.com/cloud-resource-manager). When you first create an account, you get a $300 free credit towards your compute/storage costs.\r\n",
-        "\r\n",
-        "2. [Make sure that billing is enabled for your project.](https://cloud.google.com/billing/docs/how-to/modify-project)\r\n",
-        "\r\n",
-        "3. [Enable the AutoML APIs and Compute Engine APIs.](https://console.cloud.google.com/flows/enableapi?apiid=ml.googleapis.com,compute_component)\r\n",
-        "\r\n",
-        "4. [Google Cloud SDK](https://cloud.google.com/sdk) is already installed in AutoML Notebooks.\r\n",
-        "\r\n",
-        "5. Enter your project ID in the cell below. Then run the  cell to make sure the\r\n",
-        "Cloud SDK uses the right project for all the commands in this notebook.\r\n",
-        "\r\n",
+        "## Before you begin\n",
+        "\n",
+        "### GPU run-time\n",
+        "\n",
+        "*Make sure you're running this notebook in a GPU runtime if you have that option. In Colab, select* **Runtime > Change Runtime Type > GPU**\n",
+        "\n",
+        "### Set up your GCP project\n",
+        "\n",
+        "**The following steps are required, regardless of your notebook environment.**\n",
+        "\n",
+        "1. [Select or create a GCP project](https://console.cloud.google.com/cloud-resource-manager). When you first create an account, you get a $300 free credit towards your compute/storage costs.\n",
+        "\n",
+        "2. [Make sure that billing is enabled for your project.](https://cloud.google.com/billing/docs/how-to/modify-project)\n",
+        "\n",
+        "3. [Enable the AutoML APIs and Compute Engine APIs.](https://console.cloud.google.com/flows/enableapi?apiid=ml.googleapis.com,compute_component)\n",
+        "\n",
+        "4. [Google Cloud SDK](https://cloud.google.com/sdk) is already installed in AutoML Notebooks.\n",
+        "\n",
+        "5. Enter your project ID in the cell below. Then run the  cell to make sure the\n",
+        "Cloud SDK uses the right project for all the commands in this notebook.\n",
+        "\n",
         "**Note**: Jupyter runs lines prefixed with `!` as shell commands, and it interpolates Python variables prefixed with `$` into these commands."
       ]
     },
@@ -240,11 +240,11 @@
         "id": "h_L3MRsOmYED"
       },
       "source": [
-        "### Authenticate your GCP account\r\n",
-        "\r\n",
-        "**If you are using AutoML Notebooks**, your environment is already\r\n",
-        "authenticated. Skip this step.\r\n",
-        "\r\n",
+        "### Authenticate your GCP account\n",
+        "\n",
+        "**If you are using AutoML Notebooks**, your environment is already\n",
+        "authenticated. Skip this step.\n",
+        "\n",
         "*Note: If you are on an AutoML notebook and run the cell, the cell knows to skip executing the authentication steps.*"
       ]
     },
@@ -336,7 +336,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION gs://$BUCKET_NAME"
+        "! gcloud storage buckets create --location=$REGION gs://$BUCKET_NAME"
       ]
     },
     {
@@ -356,7 +356,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al gs://$BUCKET_NAME"
+        "! gcloud storage ls --all-versions --long gs://$BUCKET_NAME"
       ]
     },
     {
@@ -391,7 +391,6 @@
       "outputs": [],
       "source": [
         "import json\n",
-        "import time\n",
         "\n",
         "from google.cloud import automl\n",
         "from google.protobuf.json_format import MessageToJson"
@@ -483,7 +482,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil cat $IMPORT_FILE | head -n 10"
+        "! gcloud storage cat $IMPORT_FILE | head -n 10"
       ]
     },
     {
@@ -1140,7 +1139,7 @@
       },
       "outputs": [],
       "source": [
-        "test_item = ! gsutil cat $IMPORT_FILE | head -n1\n",
+        "test_item = ! gcloud storage cat $IMPORT_FILE | head -n1\n",
         "test_item, test_label = str(test_item[0]).split(\",\")\n",
         "\n",
         "print(test_item, test_label)"
@@ -1175,8 +1174,8 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil cat $gcs_input_uri\n",
-        "! gsutil cat $test_item_uri"
+        "! gcloud storage cat $gcs_input_uri\n",
+        "! gcloud storage cat $test_item_uri"
       ]
     },
     {
@@ -1309,9 +1308,9 @@
         "id": "771dDuKzg8Mk"
       },
       "source": [
-        "*Example output*:\r\n",
-        "```\r\n",
-        "{}\r\n",
+        "*Example output*:\n",
+        "```\n",
+        "{}\n",
         "```"
       ]
     },
@@ -1325,8 +1324,8 @@
       "source": [
         "destination_uri = output_config[\"gcs_destination\"][\"output_uri_prefix\"][:-1]\n",
         "\n",
-        "! gsutil ls $destination_uri/*\n",
-        "! gsutil cat $destination_uri/prediction*/*.jsonl"
+        "! gcloud storage ls $destination_uri/*\n",
+        "! gcloud storage cat $destination_uri/prediction*/*.jsonl"
       ]
     },
     {
@@ -1409,9 +1408,9 @@
         "id": "CZ-62obNmBNc"
       },
       "source": [
-        "*Example output*:\r\n",
-        "```\r\n",
-        "{}\r\n",
+        "*Example output*:\n",
+        "```\n",
+        "{}\n",
         "```"
       ]
     },
@@ -1441,7 +1440,7 @@
       },
       "outputs": [],
       "source": [
-        "test_item = ! gsutil cat $IMPORT_FILE | head -n1\n",
+        "test_item = ! gcloud storage cat $IMPORT_FILE | head -n1\n",
         "test_item, test_label = str(test_item[0]).split(\",\")"
       ]
     },
@@ -1599,11 +1598,11 @@
         "id": "bQ-VVaSxJjkd"
       },
       "source": [
-        "# Cleaning up\r\n",
-        "\r\n",
-        "To clean up all GCP resources used in this project, you can [delete the GCP\r\n",
-        "project](https://cloud.google.com/resource-manager/docs/creating-managing-projects#shutting_down_projects) you used for the tutorial.\r\n",
-        "\r\n",
+        "# Cleaning up\n",
+        "\n",
+        "To clean up all GCP resources used in this project, you can [delete the GCP\n",
+        "project](https://cloud.google.com/resource-manager/docs/creating-managing-projects#shutting_down_projects) you used for the tutorial.\n",
+        "\n",
         "Otherwise, you can delete the individual resources you created in this tutorial."
       ]
     },
@@ -1635,7 +1634,7 @@
         "\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r gs://$BUCKET_NAME"
+        "    ! gcloud storage rm --recursive gs://$BUCKET_NAME"
       ]
     }
   ],

notebooks/community/migration/UJ7 AutoML for natural language with Vertex AI Text Entity Extraction.ipynb

@@ -336,8 +336,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION gs://$BUCKET_NAME"
-      ]
+        "! gcloud storage buckets create --location=$REGION gs://$BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -356,8 +355,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al gs://$BUCKET_NAME"
-      ]
+        "! gcloud storage ls --all-versions --long gs://$BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -554,8 +552,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil cat $IMPORT_FILE | head -n 1"
-      ]
+        "! gcloud storage cat $IMPORT_FILE | head -n 1"      ]
     },
     {
       "cell_type": "markdown",
@@ -1484,9 +1481,7 @@
         "with tf.io.gfile.GFile(gcs_input_uri, \"w\") as f:\n",
         "    f.write(json.dumps({\"content\": gcs_test_item, \"mime_type\": \"text/plain\"}) + \"\\n\")\n",
         "\n",
-        "! gsutil cat $gcs_input_uri\n",
-        "! gsutil cat $gcs_test_item"
-      ]
+        "! gcloud storage cat $gcs_input_uri\n",        "! gcloud storage cat $gcs_test_item"      ]
     },
     {
       "cell_type": "markdown",
@@ -1666,10 +1661,8 @@
         "            break\n",
         "    else:\n",
         "        folder = response.output_config.gcs_destination.output_uri_prefix[:-1]\n",
-        "        ! gsutil ls $folder/prediction*/*.jsonl\n",
-        "\n",
-        "        ! gsutil cat $folder/prediction*/*.jsonl\n",
-        "        break\n",
+        "        ! gcloud storage ls $folder/prediction*/*.jsonl\n",        "\n",
+        "        ! gcloud storage cat $folder/prediction*/*.jsonl\n",        "        break\n",
         "    time.sleep(60)"
       ]
     },
@@ -2260,7 +2253,7 @@
         "\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r gs://$BUCKET_NAME"
+        "    ! gcloud storage rm --recursive gs://$BUCKET_NAME"
       ]
     }
   ],

notebooks/community/migration/UJ7 legacy AutoML Natural Language Text Entity Extraction.ipynb

@@ -326,8 +326,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION gs://$BUCKET_NAME"
-      ]
+        "! gcloud storage buckets create --location=$REGION gs://$BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -346,8 +345,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al gs://$BUCKET_NAME"
-      ]
+        "! gcloud storage ls --all-versions --long gs://$BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -380,14 +378,11 @@
       },
       "outputs": [],
       "source": [
-        "import json\n",
         "import os\n",
         "import sys\n",
-        "import time\n",
         "\n",
         "from google.cloud import automl\n",
-        "from google.protobuf.json_format import MessageToJson\n",
-        "from google.protobuf.struct_pb2 import Value"
+        "from google.protobuf.json_format import MessageToJson\n"
       ]
     },
     {
@@ -476,8 +471,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil cat $IMPORT_FILE | head -n 10"
-      ]
+        "! gcloud storage cat $IMPORT_FILE | head -n 10"      ]
     },
     {
       "cell_type": "markdown",
@@ -1132,8 +1126,7 @@
         "    data = {\"id\": 0, \"text_snippet\": {\"content\": test_item}}\n",
         "    f.write(json.dumps(data) + \"\\n\")\n",
         "\n",
-        "! gsutil cat $gcs_input_uri"
-      ]
+        "! gcloud storage cat $gcs_input_uri"      ]
     },
     {
       "cell_type": "markdown",
@@ -1280,9 +1273,7 @@
       "source": [
         "destination_uri = output_config[\"gcs_destination\"][\"output_uri_prefix\"][:-1]\n",
         "\n",
-        "! gsutil ls $destination_uri/*\n",
-        "! gsutil cat $destination_uri/prediction*/*.jsonl"
-      ]
+        "! gcloud storage ls $destination_uri/*\n",        "! gcloud storage cat $destination_uri/prediction*/*.jsonl"      ]
     },
     {
       "cell_type": "markdown",
@@ -1614,8 +1605,7 @@
         "\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r gs://$BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive gs://$BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/migration/UJ8 AutoML for natural language with Vertex AI - Text Sentiment Analysis.ipynb

@@ -318,8 +318,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION gs://$BUCKET_NAME"
-      ]
+        "! gcloud storage buckets create --location $REGION gs://$BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -338,8 +337,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al gs://$BUCKET_NAME"
-      ]
+        "! gcloud storage ls --all-versions --long gs://$BUCKET_NAME"      ]
     },
     {
       "cell_type": "markdown",
@@ -536,8 +534,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil cat $IMPORT_FILE | head -n 10"
-      ]
+        "! gcloud storage cat $IMPORT_FILE | head -n 10"      ]
     },
     {
       "cell_type": "markdown",
@@ -1435,8 +1432,7 @@
         "\n",
         "import tensorflow as tf\n",
         "\n",
-        "test_data = ! gsutil cat $IMPORT_FILE | head -n1\n",
-        "\n",
+        "test_data = ! gcloud storage cat $IMPORT_FILE | head -n1\n",        "\n",
         "test_item = str(test_data[0]).split(\",\")[1]\n",
         "test_label = str(test_data[0]).split(\",\")[2]\n",
         "\n",
@@ -1449,9 +1445,7 @@
         "    data = {\"content\": gcs_test_item, \"mime_type\": \"text/plain\"}\n",
         "    f.write(json.dumps(data) + \"\\n\")\n",
         "\n",
-        "! gsutil cat $gcs_input_uri\n",
-        "! gsutil cat $gcs_test_item"
-      ]
+        "! gcloud storage cat $gcs_input_uri\n",        "! gcloud storage cat $gcs_test_item"      ]
     },
     {
       "cell_type": "markdown",
@@ -1749,8 +1743,7 @@
       "source": [
         "def get_latest_predictions(gcs_out_dir):\n",
         "    \"\"\" Get the latest prediction subfolder using the timestamp in the subfolder name\"\"\"\n",
-        "    folders = !gsutil ls $gcs_out_dir\n",
-        "    latest = \"\"\n",
+        "    folders = !gcloud storage ls $gcs_out_dir\n",        "    latest = \"\"\n",
         "    for folder in folders:\n",
         "        subfolder = folder.split(\"/\")[-2]\n",
         "        if subfolder.startswith(\"prediction-\"):\n",
@@ -1769,10 +1762,8 @@
         "        folder = get_latest_predictions(\n",
         "            response.output_config.gcs_destination.output_uri_prefix\n",
         "        )\n",
-        "        ! gsutil ls $folder/prediction*.jsonl\n",
-        "\n",
-        "        ! gsutil cat $folder/prediction*.jsonl\n",
-        "        break\n",
+        "        ! gcloud storage ls $folder/prediction*.jsonl\n",        "\n",
+        "        ! gcloud storage cat $folder/prediction*.jsonl\n",        "        break\n",
         "    time.sleep(60)"
       ]
     },
@@ -1815,8 +1806,7 @@
       },
       "outputs": [],
       "source": [
-        "test_data = ! gsutil cat $IMPORT_FILE | head -n1\n",
-        "\n",
+        "test_data = ! gcloud storage cat $IMPORT_FILE | head -n1\n",        "\n",
         "test_item = str(test_data[0]).split(\",\")[1]\n",
         "test_label = str(test_data[0]).split(\",\")[2]\n",
         "\n",
@@ -2336,8 +2326,7 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r gs://$BUCKET_NAME"
-      ]
+        "    ! gcloud storage rm --recursive gs://$BUCKET_NAME"      ]
     }
   ],
   "metadata": {

notebooks/community/migration/UJ8 legacy AutoML Natural Language Text Sentiment Analysis.ipynb

@@ -326,7 +326,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION gs://$BUCKET_NAME"
+        "! gcloud storage buckets create --location=$REGION gs://$BUCKET_NAME"
       ]
     },
     {
@@ -346,7 +346,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil ls -al gs://$BUCKET_NAME"
+        "! gcloud storage ls --all-versions --long gs://$BUCKET_NAME"
       ]
     },
     {
@@ -383,11 +383,9 @@
         "import json\n",
         "import os\n",
         "import sys\n",
-        "import time\n",
         "\n",
         "from google.cloud import automl\n",
-        "from google.protobuf.json_format import MessageToJson\n",
-        "from google.protobuf.struct_pb2 import Value"
+        "from google.protobuf.json_format import MessageToJson"
       ]
     },
     {
@@ -485,7 +483,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil cat $IMPORT_FILE | head -n 10"
+        "! gcloud storage cat $IMPORT_FILE | head -n 10"
       ]
     },
     {
@@ -1209,14 +1207,15 @@
         "gcs_input_uri = \"gs://\" + BUCKET_NAME + \"/test.csv\"\n",
         "with tf.io.gfile.GFile(gcs_input_uri, \"w\") as f:\n",
         "    item_1 = \"gs://cloud-samples-data/language/sentiment-positive.txt\"\n",
-        "    ! gsutil cp $item_1 gs://$BUCKET_NAME\n",
+        "    ! gcloud storage cp $item_1 gs://$BUCKET_NAME\n",
+        "    ! gcloud storage cp $item_1 gs://$BUCKET_NAME\n",
         "    f.write(\"gs://\" + BUCKET_NAME + \"/sentiment-positive.txt\" + \"\\n\")\n",
         "\n",
         "    item_2 = \"gs://cloud-samples-data/language/sentiment-negative.txt\"\n",
-        "    ! gsutil cp $item_2 gs://$BUCKET_NAME\n",
+        "    ! gcloud storage cp $item_2 gs://$BUCKET_NAME\n",
         "    f.write(\"gs://\" + BUCKET_NAME + \"/sentiment-negative.txt\")\n",
         "\n",
-        "! gsutil cat $gcs_input_uri"
+        "! gcloud storage cat $gcs_input_uri"
       ]
     },
     {
@@ -1381,7 +1380,7 @@
       },
       "outputs": [],
       "source": [
-        "test_data = ! gsutil cat $IMPORT_FILE | head -n1\n",
+        "test_data = ! gcloud storage cat $IMPORT_FILE | head -n1\n",
         "\n",
         "test_item = str(test_data[0]).split(\",\")[0]\n",
         "test_label = str(test_data[0]).split(\",\")[1]\n",
@@ -1615,13 +1614,13 @@
         "    print(e)\n",
         "\n",
         "if delete_bucket and \"BUCKET_NAME\" in globals():\n",
-        "    ! gsutil rm -r gs://$BUCKET_NAME"
+        "    ! gcloud storage rm --recursive gs://$BUCKET_NAME"
       ]
     }
   ],
   "metadata": {
     "colab": {
-      "name": "UJ8 legacy AutoML Natural Language - Text Sentiment Analysis.ipynb",
+      "name": "UJ8 legacy AutoML Natural Language Text Sentiment Analysis.ipynb",
       "toc_visible": true
     },
     "kernelspec": {

notebooks/community/ml_ops/setup.py

@@ -89,7 +89,7 @@ print("UUID", UUID)
 if args.bucket_required:
     BUCKET_NAME = PROJECT_ID + "aip-" + UUID
     BUCKET_URI = f"gs://{BUCKET_NAME}"
-    os.system(f"gsutil mb -l {REGION} {BUCKET_URI}")
+    os.system(f"gcloud storage buckets create --location={REGION} {BUCKET_URI}")
     print("BUCKET_URI", BUCKET_URI)