From 93192da461971561848dd4adeb76daf0b07ca53f Mon Sep 17 00:00:00 2001
From: bhandarivijay <bhandarivijay@google.com>
Date: Mon, 29 Dec 2025 15:03:32 +0000
Subject: [PATCH] chore:Migrate gsutil usage to gcloud storage

---
 README.md                  | 6 +++---
 sample_identify_and_tag.md | 8 ++++----
 2 files changed, 7 insertions(+), 7 deletions(-)

diff --git a/README.md b/README.md
index 82821b0..b693e56 100644
--- a/README.md
+++ b/README.md
@@ -267,7 +267,7 @@ it.
 Create a Cloud Storage bucket for storing test data and Dataflow staging location.
 
 ```shell script
-gsutil mb -p ${PROJECT_ID} -l ${REGION_ID} "gs://${TEMP_GCS_BUCKET}"
+gcloud storage buckets create "gs://${TEMP_GCS_BUCKET}" --project=${PROJECT_ID} --location=${REGION_ID}
 ```
 
 ### Copy test data to Cloud Storage
@@ -275,7 +275,7 @@ gsutil mb -p ${PROJECT_ID} -l ${REGION_ID} "gs://${TEMP_GCS_BUCKET}"
 You can use your own file datasets or copy the included demo dataset (`userdata.avro` or `userdata.parquet`).
 
 ```shell script
-gsutil cp userdata.avro gs://${TEMP_GCS_BUCKET}
+gcloud storage cp userdata.avro gs://${TEMP_GCS_BUCKET}
 ```
 
 ## Compile modules
@@ -381,7 +381,7 @@ The sample & identify pipeline outputs the Avro schema (or converted for Parquet
 
 ```shell script
 mkdir -p dlp_report/ && rm dlp_report/*.json
-gsutil -m cp "gs://${TEMP_GCS_BUCKET}/dlp_report/*.json" dlp_report/
+gcloud storage cp "gs://${TEMP_GCS_BUCKET}/dlp_report/*.json" dlp_report/
 ```
 
 List all the column names that have been identified.
diff --git a/sample_identify_and_tag.md b/sample_identify_and_tag.md
index 2542a1a..2e509d3 100644
--- a/sample_identify_and_tag.md
+++ b/sample_identify_and_tag.md
@@ -161,7 +161,7 @@ page in the Cloud Console.
 
 Create a Cloud Storage bucket for storing test data and Dataflow staging location:
 
-    gsutil mb -p ${PROJECT_ID} -l ${REGION_ID} "gs://${TEMP_GCS_BUCKET}"
+    gcloud storage buckets create "gs://${TEMP_GCS_BUCKET}" --project="${PROJECT_ID}" --location="${REGION_ID}"
 
 ### Create Inspection Tag tempalte
 
@@ -195,7 +195,7 @@ You can use your own file datasets or copy the included demonstration dataset (`
 
 1.  Copy the sample dataset to Cloud Storage for staging into Cloud SQL:
 
-        gsutil cp contacts5k.sql.gz gs://${TEMP_GCS_BUCKET}
+        gcloud storage cp contacts5k.sql.gz gs://${TEMP_GCS_BUCKET}
 
 1.  Create a new Database in the Cloud SQL instance:
 
@@ -208,7 +208,7 @@ You can use your own file datasets or copy the included demonstration dataset (`
 
         export SQL_SERVICE_ACCOUNT=$(gcloud sql instances describe "${SQL_INSTANCE}" --project="${PROJECT_ID}" | grep serviceAccountEmailAddress: | sed "s/serviceAccountEmailAddress: //g")
 
-        gsutil iam ch "serviceAccount:${SQL_SERVICE_ACCOUNT}:objectAdmin" gs://${TEMP_GCS_BUCKET}
+        gcloud storage buckets add-iam-policy-binding gs://${TEMP_GCS_BUCKET} --member="serviceAccount:${SQL_SERVICE_ACCOUNT}" --role="roles/storage.objectAdmin"
 
     Learn more about [Importing data into Cloud SQL](https://cloud.google.com/sql/docs/mysql/import-export/importing#mysqldump).
 
@@ -368,7 +368,7 @@ sensitive information.
 1.  Retrieve the report to your local machine:
 
         mkdir -p auto_dlp_report/ && rm auto_dlp_report/*.json
-        gsutil -m cp "gs://${TEMP_GCS_BUCKET}/auto_dlp_report/*.json" auto_dlp_report/
+        gcloud storage cp "gs://${TEMP_GCS_BUCKET}/auto_dlp_report/*.json" auto_dlp_report/
 
 1.  List all the column names that have been identified: