GoogleCloudPlatform · googlyrahman · Oct 27, 2025 · Oct 31, 2025
diff --git a/blogs/batch_normalization/estimator_batch_normalization.ipynb b/blogs/batch_normalization/estimator_batch_normalization.ipynb
@@ -91,7 +91,7 @@
     "        JOBNAME=mnist$netname_$(date -u +%y%m%d_%H%M%S)\n",
     "        OUTDIR=gs://${BUCKET}/mnist_models/mnist_model$netname/trained_model\n",
     "        echo $OUTDIR $REGION $JOBNAME\n",
-    "        gsutil -m rm -rf $OUTDIR\n",
+    "        gcloud storage rm --recursive --continue-on-error $OUTDIR\n",
     "        submitMLEngineJob\n",
     "        net=$net,    \n",
     "    done \n",

diff --git a/blogs/explainable_ai/AI_Explanations_on_CAIP.ipynb b/blogs/explainable_ai/AI_Explanations_on_CAIP.ipynb
@@ -256,17 +256,14 @@
       },
       "source": [
         "%%bash\n",
-        "exists=$(gsutil ls -d | grep -w gs://${BUCKET_NAME}/)\n",
-        "\n",
+        "exists=$(gcloud storage ls | grep -w gs://${BUCKET_NAME}/)\n",        "\n",
         "if [ -n \"$exists\" ]; then\n",
         "   echo -e \"Bucket gs://${BUCKET_NAME} already exists.\"\n",
         "    \n",
         "else\n",
         "   echo \"Creating a new GCS bucket.\"\n",
-        "   gsutil mb -l ${REGION} gs://${BUCKET_NAME}\n",
-        "   echo -e \"\\nHere are your current buckets:\"\n",
-        "   gsutil ls\n",
-        "fi"
+        "   gcloud storage buckets create --location=${REGION} gs://${BUCKET_NAME}\n",        "   echo -e \"\\nHere are your current buckets:\"\n",
+        "   gcloud storage ls\n",        "fi"
       ],
       "execution_count": 0,
       "outputs": []
@@ -330,8 +327,7 @@
         "%%bash\n",
         "# Copy the data to your notebook instance\n",
         "mkdir taxi_preproc\n",
-        "gsutil cp -r gs://cloud-training/bootcamps/serverlessml/taxi_preproc/*_xai.csv ./taxi_preproc\n",
-        "ls -l taxi_preproc"
+        "gcloud storage cp --recursive gs://cloud-training/bootcamps/serverlessml/taxi_preproc/*_xai.csv ./taxi_preproc\n",        "ls -l taxi_preproc"
       ],
       "execution_count": 0,
       "outputs": []
@@ -812,8 +808,7 @@
         "colab": {}
       },
       "source": [
-        "!gsutil cp explanation_metadata.json $export_path"
-      ],
+        "!gcloud storage cp explanation_metadata.json $export_path"      ],
       "execution_count": 0,
       "outputs": []
     },
@@ -1107,4 +1102,4 @@
       "outputs": []
     }
   ]
-}
+}
diff --git a/blogs/gcp_forecasting/gcp_time_series_forecasting.ipynb b/blogs/gcp_forecasting/gcp_time_series_forecasting.ipynb
@@ -1488,8 +1488,7 @@
    },
    "outputs": [],
    "source": [
-    "!gsutil -m cp gs://asl-testing-bucket/forecasting/nyc_real_estate/data/*.csv ."
-   ]
+"!gcloud storage cp gs://asl-testing-bucket/forecasting/nyc_real_estate/data/*.csv ."   ]
   },
   {
    "cell_type": "code",
@@ -1551,8 +1550,7 @@
     "OUTDIR=gs://$BUCKET/forecasting/nyc_real_estate/trained_model\n",
     "JOBNAME=nyc_real_estate$(date -u +%y%m%d_%H%M%S)\n",
     "echo $OUTDIR $REGION $JOBNAME\n",
-    "gsutil -m rm -rf $OUTDIR\n",
-    "gcloud ai-platform jobs submit training $JOBNAME \\\n",
+    "gcloud storage rm --recursive --continue-on-error $OUTDIR\n",    "gcloud ai-platform jobs submit training $JOBNAME \\\n",
     "  --region=$REGION \\\n",
     "  --module-name=trainer.task \\\n",
     "  --package-path=$PWD/tf_module/trainer \\\n",

diff --git a/blogs/lightning/1_explore.ipynb b/blogs/lightning/1_explore.ipynb
@@ -1142,8 +1142,7 @@
     "LABEL_RADIUS=2\n",
     "STRIDE=4 # use 2*label_patch_radius\n",
     "OUTDIR=gs://${BUCKET}/lightning/preproc_${LATLONRES}_${TRAIN_RADIUS}_${LABEL_RADIUS}\n",
-    "gsutil -m rm -rf $OUTDIR\n",
-    "\n",
+    "gcloud storage rm --recursive --continue-on-error $OUTDIR\n",    "\n",
     "python3 -m ltgpred.preproc.create_dataset \\\n",
     "   --outdir=$OUTDIR \\\n",
     "   --startday 2018-45 --endday 2019-111 --project=$PROJECT \\\n",
@@ -1172,8 +1171,7 @@
     "STRIDE=2 # use 2*label_patch_radius\n",
     "LTG_VALID_TIME=5\n",
     "OUTDIR=gs://${BUCKET}/lightning/preproc_${LATLONRES}_${TRAIN_RADIUS}_${LABEL_RADIUS}\n",
-    "gsutil -m rm -rf $OUTDIR\n",
-    "\n",
+    "gcloud storage rm --recursive --continue-on-error $OUTDIR\n",    "\n",
     "python3 -m ltgpred.preproc.create_dataset \\\n",
     "   --outdir=$OUTDIR \\\n",
     "   --startday 2018-45 --endday 2019-111 --project=$PROJECT \\\n",
@@ -1197,8 +1195,7 @@
    ],
    "source": [
     "%%bash\n",
-    "gsutil cat gs://cloud-training-demos-ml/lightning/preproc_0.02_32_1/stats*"
-   ]
+    "gcloud storage cat gs://cloud-training-demos-ml/lightning/preproc_0.02_32_1/stats*"   ]
   },
   {
    "cell_type": "markdown",

diff --git a/blogs/lightning/2_sklearn.ipynb b/blogs/lightning/2_sklearn.ipynb
@@ -108,7 +108,7 @@
    ],
    "source": [
     "!mkdir -p preproc/csv\n",
-    "!gsutil cp gs://$BUCKET/lightning/preproc_0.02_32_2/csv/*-00000-* preproc/csv"
+    "!gcloud storage cp gs://$BUCKET/lightning/preproc_0.02_32_2/csv/*-00000-* preproc/csv"
    ]
   },
   {
@@ -336,7 +336,7 @@
     "OUTDIR=gs://${BUCKET}/lightning/skl_trained\n",
     "DATADIR=gs://$BUCKET/lightning/preproc_0.02_32_2/csv\n",
     "JOBNAME=ltgpred_skl_$(date -u +%y%m%d_%H%M%S)\n",
-    "gsutil -m rm -rf $OUTDIR\n",
+    "gcloud storage rm --recursive --continue-on-error $OUTDIR\n",
     "gcloud ml-engine jobs submit training $JOBNAME \\\n",
     "    --module-name=ltgpred.trainer.train_skl --package-path=${PWD}/ltgpred --job-dir=$OUTDIR \\\n",
     "    --region=${REGION} --scale-tier=custom --config=largemachine.yaml \\\n",

diff --git a/blogs/lightning/3_convnet.ipynb b/blogs/lightning/3_convnet.ipynb
@@ -125,7 +125,7 @@
    ],
    "source": [
     "!mkdir -p preproc/tfrecord\n",
-    "!gsutil cp gs://$BUCKET/lightning/preproc_0.02_32_2/tfrecord/*-00000-* preproc/tfrecord"
+    "!gcloud storage cp gs://$BUCKET/lightning/preproc_0.02_32_2/tfrecord/*-00000-* preproc/tfrecord"
    ]
   },
   {
@@ -275,7 +275,7 @@
     "for ARCH in convnet; do\n",
     "  JOBNAME=ltgpred_${ARCH}_$(date -u +%y%m%d_%H%M%S)\n",
     "  OUTDIR=gs://${BUCKET}/lightning/${ARCH}_trained_gpu\n",
-    "  gsutil -m rm -rf $OUTDIR\n",
+    "  gcloud storage rm --recursive --continue-on-error $OUTDIR\n",
     "  gcloud ml-engine jobs submit training $JOBNAME \\\n",
     "      --module-name trainer.train_cnn --package-path ${PWD}/ltgpred/trainer --job-dir=$OUTDIR \\\n",
     "      --region=${REGION} --scale-tier CUSTOM --config largemachine.yaml \\\n",
@@ -383,7 +383,7 @@
     "OUTDIR=gs://${BUCKET}/lightning/convnet_trained_gpu_hparam\n",
     "DATADIR=gs://$BUCKET/lightning/preproc_0.02_32_2/tfrecord\n",
     "JOBNAME=ltgpred_hparam_$(date -u +%y%m%d_%H%M%S)\n",
-    "gsutil -m rm -rf $OUTDIR\n",
+    "gcloud storage rm --recursive --continue-on-error $OUTDIR\n",
     "gcloud ml-engine jobs submit training $JOBNAME \\\n",
     "    --module-name=ltgpred.trainer.train_cnn --package-path=${PWD}/ltgpred --job-dir=$OUTDIR \\\n",
     "    --region=${REGION} --scale-tier=CUSTOM --config=hyperparam_gpu.yaml \\\n",
@@ -440,7 +440,7 @@
     "OUTDIR=gs://${BUCKET}/lightning/cnn_trained_tpu\n",
     "DATADIR=gs://$BUCKET/lightning/preproc_0.02_32_2/tfrecord\n",
     "JOBNAME=ltgpred_cnn_$(date -u +%y%m%d_%H%M%S)\n",
-    "gsutil -m rm -rf $OUTDIR\n",
+    "gcloud storage rm --recursive --continue-on-error $OUTDIR\n",
     "gcloud ml-engine jobs submit training $JOBNAME \\\n",
     "    --module-name ltgpred.trainer.train_cnn --package-path ${PWD}/ltgpred --job-dir=$OUTDIR \\\n",
     "    --region ${REGION} --scale-tier BASIC_TPU \\\n",
@@ -481,7 +481,7 @@
     "for ARCH in feateng; do\n",
     "  JOBNAME=ltgpred_${ARCH}_$(date -u +%y%m%d_%H%M%S)\n",
     "  OUTDIR=gs://${BUCKET}/lightning/${ARCH}_trained_gpu\n",
-    "  gsutil -m rm -rf $OUTDIR\n",
+    "  gcloud storage rm --recursive --continue-on-error $OUTDIR\n",
     "  gcloud ml-engine jobs submit training $JOBNAME \\\n",
     "      --module-name ltgpred.trainer.train_cnn --package-path ${PWD}/ltgpred --job-dir=$OUTDIR \\\n",
     "      --region=${REGION} --scale-tier CUSTOM --config largemachine.yaml \\\n",

diff --git a/blogs/lightning/README.md b/blogs/lightning/README.md
@@ -30,7 +30,7 @@ LABEL_RADIUS=1
 STRIDE=2 # use 2*label_patch_radius
 LTG_VALID_TIME=5
 OUTDIR=gs://${BUCKET}/lightning/preproc_${LATLONRES}_${TRAIN_RADIUS}_${LABEL_RADIUS}
-gsutil -m rm -rf $OUTDIR
+gcloud storage rm --recursive --continue-on-error $OUTDIR
 
 python -m ltgpred.preproc.create_dataset \
    --outdir=$OUTDIR \
@@ -52,7 +52,7 @@ DATADIR=gs://${BUCKET}/lightning/preproc_${LATLONRES}_${TRAIN_RADIUS}_${LABEL_RA
 for ARCH in convnet; do
   JOBNAME=ltgpred_${ARCH}_$(date -u +%y%m%d_%H%M%S)
   OUTDIR=gs://${BUCKET}/lightning/${ARCH}_trained_gpu
-  gsutil -m rm -rf $OUTDIR
+  gcloud storage rm --recursive --continue-on-error $OUTDIR
   gcloud ml-engine jobs submit training $JOBNAME \
       --module-name trainer.train_cnn --package-path ${PWD}/ltgpred/trainer --job-dir=$OUTDIR \
       --region=${REGION} --scale-tier CUSTOM --config largemachine.yaml \

diff --git a/blogs/lightning/ltgpred/trainer/train_skl.py b/blogs/lightning/ltgpred/trainer/train_skl.py
@@ -107,7 +107,7 @@ def save_model(model_tosave, gcspath, name):  # pylint: disable=unused-argument
   model_path = os.path.join(
       gcspath,
       datetime.datetime.now().strftime('export_%Y%m%d_%H%M%S'), filename)
-  subprocess.check_call(['gsutil', 'cp', filename, model_path])
+  subprocess.check_call(['gcloud', 'storage', 'cp', filename, model_path])
   return model_path
 
 

diff --git a/blogs/sklearn/babyweight/trainer/model.py b/blogs/sklearn/babyweight/trainer/model.py
@@ -138,5 +138,5 @@ def save_model(estimator, gcspath, name):
   joblib.dump(estimator, model)
   model_path = os.path.join(gcspath, datetime.datetime.now().strftime(
     'export_%Y%m%d_%H%M%S'), model)
-  subprocess.check_call(['gsutil', 'cp', model, model_path])
+  subprocess.check_call(['gcloud', 'storage', 'cp', model, model_path])
   return model_path
diff --git a/blogs/sklearn/babyweight_skl.ipynb b/blogs/sklearn/babyweight_skl.ipynb
@@ -103,9 +103,7 @@
    "outputs": [],
    "source": [
     "%%bash\n",
-    "if ! gsutil ls | grep -q gs://${BUCKET}/; then\n",
-    "  gsutil mb -l ${REGION} gs://${BUCKET}\n",
-    "fi"
+    "if ! gcloud storage ls | grep -q gs://${BUCKET}/; then\n",    "  gcloud storage buckets create --location ${REGION} gs://${BUCKET}\n",    "fi"
    ]
   },
   {
@@ -840,8 +838,7 @@
     "  joblib.dump(estimator, model)\n",
     "  model_path = os.path.join(gcspath, datetime.datetime.now().strftime(\n",
     "    'export_%Y%m%d_%H%M%S'), model)\n",
-    "  subprocess.check_call(['gsutil', 'cp', model, model_path])\n",
-    "  return model_path"
+    "  subprocess.check_call(['gcloud', 'storage', 'cp', model, model_path])\n",    "  return model_path"
    ]
   },
   {
@@ -1199,8 +1196,7 @@
    ],
    "source": [
     "%bash\n",
-    "gsutil ls gs://${BUCKET}/babyweight/sklearn/ | tail -1"
-   ]
+    "gcloud storage ls gs://${BUCKET}/babyweight/sklearn/ | tail -1"   ]
   },
   {
    "cell_type": "code",
@@ -1218,8 +1214,7 @@
     "%bash\n",
     "MODEL_NAME=\"babyweight\"\n",
     "MODEL_VERSION=\"skl\"\n",
-    "MODEL_LOCATION=$(gsutil ls gs://${BUCKET}/babyweight/sklearn/ | tail -1)\n",
-    "echo \"Deleting and deploying $MODEL_NAME $MODEL_VERSION from $MODEL_LOCATION ... this will take a few minutes\"\n",
+    "MODEL_LOCATION=$(gcloud storage ls gs://${BUCKET}/babyweight/sklearn/ | tail -1)\n",    "echo \"Deleting and deploying $MODEL_NAME $MODEL_VERSION from $MODEL_LOCATION ... this will take a few minutes\"\n",
     "#gcloud ml-engine versions delete ${MODEL_VERSION} --model ${MODEL_NAME}\n",
     "#gcloud ml-engine models delete ${MODEL_NAME}\n",
     "#gcloud ml-engine models create ${MODEL_NAME} --regions $REGION\n",