Use Workload Identity Federation for GCP auth

Revisa primero .github/workflows/weekly_run.yml y el workflow pr_validation; después, confirma el GCP Workload Identity Pool/Provider y los dos secretos de repositorio indicados. Actualiza todos los workflows de GitHub para que utilicen credenciales de federación de corta duración, configura gcloud explícitamente solo donde sea necesario y elimina GCP_SERVICE_ACCOUNT_KEY después de confirmar que la integración funciona.

This comment came up as part of a Copilot review in https://github.com/oppia/analytics-data-platform/pull/1#discussion_r3790752232:

This workflow relies on a long-lived service account JSON key and assumes gcloud is available on the runner. Prefer GitHub’s recommended GCP auth approach (Workload Identity Federation via google-github-actions/auth) and, if gcloud is needed, install/configure it explicitly (e.g., google-github-actions/setup-gcloud). This reduces key-leak risk and avoids failures on runners without gcloud.

If we go this route, this would need to be done for all our github workflows (e.g. pr_validation and weekly_run). It requires setting up a Workload Identity Pool/Provider in GCP and adding two new repo secrets, GCP_WORKLOAD_IDENTITY_PROVIDER and GCP_SERVICE_ACCOUNT_EMAIL, then removing the old GCP_SERVICE_ACCOUNT_KEY secret once the integration is confirmed working.

Sample patch file with expected changes:

--- a/.github/workflows/weekly_run.yml
+++ b/.github/workflows/weekly_run.yml
@@ -9,7 +9,7 @@ name: Weekly Production Analytics Run
 #
 # Environment Target: Production (oppia-analytics-prod)
 # Key Operations:
-#   1. Authenticates to GCP using an automated service account.
+#   1. Authenticates to GCP via Workload Identity Federation (no long-lived keys).
 #   2. Dynamically isolates database credentials to prevent local Git leaks.
 #   3. Runs data quality assertions and transforms fresh production analytics logs.
 # ==============================================================================
@@ -25,6 +25,9 @@ jobs:
   dbt_run:
     name: Execute dbt Production Pipeline
     runs-on: ubuntu-latest
+    permissions:
+      contents: read
+      id-token: write # required to mint the OIDC token for Workload Identity Federation
 
     steps:
       # Clone the repository codebase onto the temporary GitHub virtual runner
@@ -43,21 +46,14 @@ jobs:
           pip install --upgrade pip
           pip install dbt-bigquery
 
-      # Exchange GitHub secret tokens for active, authenticated Google Cloud sessions
-      - name: Authenticate to GCP Natively
-        run: |
-          # Write the secret JSON token safely as a raw literal string
-          cat << 'EOF' > ${HOME}/gcp_key.json
-          ${{ secrets.GCP_SERVICE_ACCOUNT_KEY }}
-          EOF
-
-          # Activate the service account using the pre-installed gcloud CLI
-          gcloud auth activate-service-account --key-file=${HOME}/gcp_key.json
-
-          # Set the application default credentials environment variable for dbt
-          echo "GOOGLE_APPLICATION_CREDENTIALS=${HOME}/gcp_key.json" >> $GITHUB_ENV
+      # Keyless auth: exchanges a GitHub OIDC token for short-lived GCP credentials
+      - name: Authenticate to GCP via Workload Identity Federation
+        uses: google-github-actions/auth@v2
+        with:
+          workload_identity_provider: ${{ secrets.GCP_WORKLOAD_IDENTITY_PROVIDER }}
+          service_account: ${{ secrets.GCP_SERVICE_ACCOUNT_EMAIL }}
 
-      # Generate a production connection profile using service-account credentials
+      # Generate a production connection profile using the ADC credentials from the auth step
       - name: Create dynamic profiles.yml for dbt
         run: |
           cat << EOF > profiles.yml
@@ -66,8 +62,7 @@ jobs:
             outputs:
               prod:
                 type: bigquery
-                method: service-account
-                keyfile: ${{ env.GOOGLE_APPLICATION_CREDENTIALS }}
+                method: oauth
                 project: oppia-analytics-prod
                 dataset: analytics_production
                 threads: 4