Collect Salesforce Commerce Cloud logs

Supported in:

This document explains how to ingest Salesforce Commerce Cloud logs to Google Security Operations using Google Cloud Storage V2.

Salesforce Commerce Cloud is an e-commerce platform that generates transaction, access, and security audit logs. A Cloud Run function connects to the Salesforce Commerce Cloud WebDAV endpoint on a schedule, downloads log files, writes them to a GCS bucket in NDJSON format, and Google SecOps ingests them through a GCS V2 feed.

Before you begin

Mkae sure you have the following prerequisites:

  • A Google SecOps instance
  • A GCP project with Cloud Storage API enabled
  • Permissions to create and manage GCS buckets
  • Permissions to manage IAM policies on GCS buckets
  • Permissions to create Cloud Run services, Pub/Sub topics, and Cloud Scheduler jobs
  • Privileged access to Salesforce Commerce Cloud Business Manager with WebDAV access permission

Create Google Cloud Storage bucket

  1. Go to the Google Cloud Console.
  2. Select your project or create a new one.
  3. In the navigation menu, go to Cloud Storage > Buckets.
  4. Click Create bucket.

  5. Provide the following configuration details:

    Setting Value
    Name your bucket Enter a globally unique name (for example, sfcc-logs)
    Location type Choose based on your needs (Region, Dual-region, Multi-region)
    Location Select the location (for example, us-central1)
    Storage class Standard (recommended for frequently accessed logs)
    Access control Uniform (recommended)
    Protection tools Optional: Enable object versioning or retention policy

  6. Click Create.

Collect Salesforce Commerce Cloud credentials

Configure WebDAV access

  1. Sign in to Business Manager for your Salesforce Commerce Cloud instance.
  2. Go to Administration > Organization > Roles & Permissions.
  3. Verify that your user account has the WebDAV File Access permission enabled.
  4. Note your SFCC instance hostname (for example, development-yoursite-dw.demandware.net).

  5. Save the following credentials in a secure location:

    • SFCC Host: Your instance hostname (for example, development-yoursite-dw.demandware.net).
    • Username: Your Business Manager username.
    • Password: Your Business Manager password.

Verify permissions

To verify the account has the required permissions:

  1. Sign in to Business Manager for your Salesforce Commerce Cloud instance.
  2. Go to Administration > Site Development > Development Setup.
  3. Click Log Files under the WebDAV section.
  4. If you can see log file directories, you have the required permissions.
  5. If you cannot see this option, contact your SFCC administrator to grant WebDAV access.

Test API access

  • Test your credentials before proceeding with the integration:

    # Replace with your actual credentials
SFCC_HOST="development-yoursite-dw.demandware.net"
USERNAME="your-username"
PASSWORD="your-password"

# Test WebDAV access to log directory
curl -v -u "${USERNAME}:${PASSWORD}" \
  "https://${SFCC_HOST}/on/demandware.servlet/webdav/Sites/Logs/"

Create service account for Cloud Run function

The Cloud Run function needs a service account with permissions to write to GCS bucket and be invoked by Pub/Sub.

Create service account

  1. In the GCP Console, go to IAM & Admin > Service Accounts.
  2. Click Create Service Account.
  3. Provide the following configuration details:
    • Service account name: Enter sfcc-logs-collector-sa.
    • Service account description: Enter Service account for Cloud Run function to collect Salesforce Commerce Cloud logs.
  4. Click Create and Continue.
  5. In the Grant this service account access to project section, add the following roles:
    1. Click Select a role.
    2. Search for and select Storage Object Admin.
    3. Click + Add another role.
    4. Search for and select Cloud Run Invoker.
    5. Click + Add another role.
    6. Search for and select Cloud Functions Invoker.
  6. Click Continue.
  7. Click Done.

These roles are required for:

  • Storage Object Admin: Write logs to GCS bucket and manage state files
  • Cloud Run Invoker: Allow Pub/Sub to invoke the function
  • Cloud Functions Invoker: Allow function invocation

Grant IAM permissions on GCS bucket

Grant the service account write permissions on the GCS bucket:

  1. Go to Cloud Storage > Buckets.
  2. Click your bucket name (for example, sfcc-logs).
  3. Go to the Permissions tab.
  4. Click Grant access.
  5. Provide the following configuration details:
    • Add principals: Enter the service account email (for example, sfcc-logs-collector-sa@your-project.iam.gserviceaccount.com).
    • Assign roles: Select Storage Object Admin.
  6. Click Save.

Create Pub/Sub topic

Create a Pub/Sub topic that Cloud Scheduler will publish to and the Cloud Run function will subscribe to.

  1. In the GCP Console, go to Pub/Sub > Topics.
  2. Click Create topic.
  3. Provide the following configuration details:
    • Topic ID: Enter sfcc-logs-trigger.
    • Leave other settings as default.
  4. Click Create.

Create Cloud Run function to collect logs

The Cloud Run function will be triggered by Pub/Sub messages from Cloud Scheduler to fetch logs from Salesforce Commerce Cloud WebDAV and write them to GCS.

  1. In the GCP Console, go to Cloud Run.
  2. Click Create service.
  3. Select Function (use an inline editor to create a function).

  4. In the Configure section, provide the following configuration details:

    Setting Value
    Service name sfcc-logs-collector
    Region Select region matching your GCS bucket (for example, us-central1)
    Runtime Select Python 3.12 or later

  5. In the Trigger (optional) section:

    1. Click + Add trigger.
    2. Select Cloud Pub/Sub.
    3. In Select a Cloud Pub/Sub topic, choose the topic sfcc-logs-trigger.
    4. Click Save.

  6. In the Authentication section:

    1. Select Require authentication.
    2. Check Identity and Access Management (IAM).

  7. Scroll down and expand Containers, Networking, Security.

  8. Go to the Security tab:

    • Service account: Select the service account sfcc-logs-collector-sa.

  9. Go to the Containers tab:

    1. Click Variables & Secrets.
    2. Click + Add variable for each environment variable:
    Variable Name Example Value Description
    GCS_BUCKET sfcc-logs GCS bucket name
    GCS_PREFIX sfcc Prefix for log files
    STATE_KEY sfcc/state.json State file path
    SFCC_HOST development-yoursite-dw.demandware.net SFCC instance hostname
    SFCC_USERNAME your-username Business Manager username
    SFCC_PASSWORD your-password Business Manager password
    LOG_DIRS security,error,warn,customerror Comma-separated log directories
    LOOKBACK_HOURS 24 Initial lookback period

  10. Scroll down in the Variables & Secrets tab to Requests:

    • Request timeout: Enter 600 seconds (10 minutes).

  11. Go to the Settings tab in Containers:

    • In the Resources section:
      • Memory: Select 512 MiB or higher.
      • CPU: Select 1.
    • Click Done.

  12. Scroll down to Execution environment:

    • Select Default (recommended).

  13. In the Revision scaling section:

    • Minimum number of instances: Enter 0.
    • Maximum number of instances: Enter 100 (or adjust based on expected load).

  14. Click Create.

  15. Wait for the service to be created (1-2 minutes).

  16. After the service is created, the inline code editor will open automatically.

Add function code

  1. Enter main in Function entry point.

  2. In the inline code editor, create two files:

    • First file - main.py:

      import functions_framework
from google.cloud import storage
import json
import os
import urllib3
from datetime import datetime, timezone, timedelta
import time
import base64
import re

# Initialize HTTP client with timeouts
http = urllib3.PoolManager(
  timeout=urllib3.Timeout(connect=10.0, read=60.0),
  retries=False,
)

# Initialize Storage client
storage_client = storage.Client()

# Environment variables
GCS_BUCKET = os.environ.get('GCS_BUCKET')
GCS_PREFIX = os.environ.get('GCS_PREFIX', 'sfcc')
STATE_KEY = os.environ.get('STATE_KEY', 'sfcc/state.json')
SFCC_HOST = os.environ.get('SFCC_HOST')
SFCC_USERNAME = os.environ.get('SFCC_USERNAME')
SFCC_PASSWORD = os.environ.get('SFCC_PASSWORD')
LOG_DIRS = [d.strip() for d in os.environ.get('LOG_DIRS', 'security,error,warn,customerror').split(',') if d.strip()]
LOOKBACK_HOURS = int(os.environ.get('LOOKBACK_HOURS', '24'))

def parse_datetime(value: str) -> datetime:
  """Parse ISO datetime string to datetime object."""
  if value.endswith("Z"):
    value = value[:-1] + "+00:00"
  return datetime.fromisoformat(value)

@functions_framework.cloud_event
def main(cloud_event):
  """
  Cloud Run function triggered by Pub/Sub to fetch Salesforce Commerce Cloud
  logs via WebDAV and write to GCS.

  Args:
    cloud_event: CloudEvent object containing Pub/Sub message
  """

  if not all([GCS_BUCKET, SFCC_HOST, SFCC_USERNAME, SFCC_PASSWORD]):
    print('Error: Missing required environment variables')
    return

  try:
    bucket = storage_client.bucket(GCS_BUCKET)

    # Load state
    state = load_state(bucket, STATE_KEY)

    now = datetime.now(timezone.utc)
    last_time = None

    if isinstance(state, dict) and state.get("last_event_time"):
      try:
        last_time = parse_datetime(state["last_event_time"])
      except Exception as e:
        print(f"Warning: Could not parse last_event_time: {e}")

    if last_time is None:
      last_time = now - timedelta(hours=LOOKBACK_HOURS)

    print(f"Fetching logs since {last_time.isoformat()}")

    # Build auth header
    credentials = f"{SFCC_USERNAME}:{SFCC_PASSWORD}"
    encoded_credentials = base64.b64encode(credentials.encode('utf-8')).decode('utf-8')
    headers = {
      'Authorization': f'Basic {encoded_credentials}',
      'User-Agent': 'GoogleSecOps-SFCCCollector/1.0'
    }

    total_files = 0
    webdav_base = f"https://{SFCC_HOST}/on/demandware.servlet/webdav/Sites/Logs"

    for log_dir in LOG_DIRS:
      print(f"Processing log directory: {log_dir}")
      files_processed = fetch_and_upload_logs(
        bucket=bucket,
        webdav_base=webdav_base,
        log_dir=log_dir,
        headers=headers,
        since=last_time,
        now=now,
      )
      total_files += files_processed

    if total_files == 0:
      print("No new log files found.")
    else:
      print(f"Successfully processed {total_files} log files")

    save_state(bucket, STATE_KEY, now.isoformat())

  except Exception as e:
    print(f'Error processing logs: {str(e)}')
    raise

def load_state(bucket, key):
  """Load state from GCS."""
  try:
    blob = bucket.blob(key)
    if blob.exists():
      state_data = blob.download_as_text()
      return json.loads(state_data)
  except Exception as e:
    print(f"Warning: Could not load state: {e}")

  return {}

def save_state(bucket, key, last_event_time_iso: str):
  """Save the last event timestamp to GCS state file."""
  try:
    state = {'last_event_time': last_event_time_iso}
    blob = bucket.blob(key)
    blob.upload_from_string(
      json.dumps(state, indent=2),
      content_type='application/json'
    )
    print(f"Saved state: last_event_time={last_event_time_iso}")
  except Exception as e:
    print(f"Warning: Could not save state: {e}")

def list_webdav_files(webdav_url: str, headers: dict):
  """List files in a WebDAV directory using PROPFIND."""
  backoff = 1.0
  max_retries = 3

  for attempt in range(max_retries):
    response = http.request('PROPFIND', webdav_url, headers={**headers, 'Depth': '1'})

    if response.status == 429:
      retry_after = int(response.headers.get('Retry-After', str(int(backoff))))
      print(f"Rate limited (429). Retrying after {retry_after}s...")
      time.sleep(retry_after)
      backoff = min(backoff * 2, 30.0)
      continue

    if response.status not in (200, 207):
      print(f"HTTP Error listing {webdav_url}: {response.status}")
      return []

    content = response.data.decode('utf-8')
    # Parse file names from WebDAV PROPFIND XML response
    files = re.findall(r'<D:href>([^<]+)</D:href>', content)
    return [f for f in files if not f.endswith('/')]

  return []

def fetch_and_upload_logs(bucket, webdav_base: str, log_dir: str, headers: dict, since: datetime, now: datetime):
  """
  Fetch log files from a WebDAV directory and upload to GCS.

  Args:
    bucket: GCS bucket object
    webdav_base: WebDAV base URL
    log_dir: Log directory name
    headers: HTTP headers with auth
    since: Only process files newer than this
    now: Current time for file naming

  Returns:
    Number of files processed
  """
  dir_url = f"{webdav_base}/{log_dir}/"
  files = list_webdav_files(dir_url, headers)
  files_processed = 0
  backoff = 1.0

  for file_path in files:
    file_name = file_path.split('/')[-1]
    if not file_name:
      continue

    # Download file
    file_url = f"https://{SFCC_HOST}{file_path}"

    response = http.request('GET', file_url, headers=headers)

    if response.status == 429:
      retry_after = int(response.headers.get('Retry-After', str(int(backoff))))
      print(f"Rate limited (429). Retrying after {retry_after}s...")
      time.sleep(retry_after)
      backoff = min(backoff * 2, 30.0)
      response = http.request('GET', file_url, headers=headers)

    if response.status != 200:
      print(f"Error downloading {file_name}: {response.status}")
      continue

    backoff = 1.0
    content = response.data

    if not content:
      continue

    # Upload to GCS
    timestamp = now.strftime('%Y%m%d_%H%M%S')
    object_key = f"{GCS_PREFIX}/{log_dir}/{file_name}_{timestamp}"
    blob = bucket.blob(object_key)

    # Convert log lines to NDJSON
    lines = content.decode('utf-8', errors='replace').splitlines()
    records = []
    for line in lines:
      line = line.strip()
      if line:
        try:
          record = json.loads(line)
        except json.JSONDecodeError:
          record = {'raw_log': line, 'log_dir': log_dir, 'source_file': file_name}
        records.append(record)

    if records:
      ndjson = '\n'.join([json.dumps(r, ensure_ascii=False) for r in records]) + '\n'
      blob.upload_from_string(ndjson, content_type='application/x-ndjson')
      print(f"Uploaded {len(records)} records from {file_name} to gs://{GCS_BUCKET}/{object_key}")
      files_processed += 1

  return files_processed

    • Second file - requirements.txt:

      functions-framework==3.*
google-cloud-storage==2.*
urllib3>=2.0.0

  3. Click Deploy to save and deploy the function.

  4. Wait for deployment to complete (2-3 minutes).

Create Cloud Scheduler job

Cloud Scheduler will publish messages to the Pub/Sub topic at regular intervals, triggering the Cloud Run function.

  1. In the GCP Console, go to Cloud Scheduler.
  2. Click Create Job.

  3. Provide the following configuration details:

    Setting Value
    Name sfcc-logs-collector-hourly
    Region Select same region as Cloud Run function
    Frequency 0 * * * * (every hour, on the hour)
    Timezone Select timezone (UTC recommended)
    Target type Pub/Sub
    Topic Select the topic sfcc-logs-trigger
    Message body {} (empty JSON object)

  4. Click Create.

Schedule frequency options

Choose frequency based on log volume and latency requirements:

Frequency Cron Expression Use Case
Every 5 minutes */5 * * * * High-volume, low-latency
Every 15 minutes */15 * * * * Medium volume
Every hour 0 * * * * Standard (recommended)
Every 6 hours 0 */6 * * * Low volume, batch processing
Daily 0 0 * * * Historical data collection

Test the integration

  1. In the Cloud Scheduler console, find your job (sfcc-logs-collector-hourly).
  2. Click Force run to trigger manually.
  3. Wait a few seconds and go to Cloud Run > Services > sfcc-logs-collector > Logs.

  4. Verify the function executed successfully. Look for:

    Fetching logs since YYYY-MM-DDTHH:MM:SS+00:00
Processing log directory: security
Uploaded X records from filename.log to gs://sfcc-logs/sfcc/security/filename.log_YYYYMMDD_HHMMSS
Successfully processed X log files

  5. Check the GCS bucket (sfcc-logs) to confirm logs were written.

If you see errors in the logs:

  • HTTP 401: Check SFCC credentials in environment variables
  • HTTP 403: Verify account has WebDAV File Access permission in Business Manager
  • HTTP 429: Rate limiting - function will automatically retry with backoff
  • Missing environment variables: Check all required variables are set

Configure a feed in Google SecOps to ingest Salesforce Commerce Cloud logs

  1. Go to SIEM Settings > Feeds.
  2. Click Add New Feed.
  3. Click Configure a single feed.
  4. In the Feed name field, enter a name for the feed (for example, Salesforce Commerce Cloud Logs).
  5. Select Google Cloud Storage V2 as the Source type.
  6. Select Salesforce Commerce Cloud as the Log type.

  7. Click Get Service Account. A unique service account email will be displayed, for example:

    chronicle-12345678@chronicle-gcp-prod.iam.gserviceaccount.com

  8. Copy this email address. You will use it in the next step.

  9. Click Next.

  10. Specify values for the following input parameters:

    • Storage bucket URL: Enter the GCS bucket URI with the prefix path:

      gs://sfcc-logs/sfcc/
      • Replace:
        • sfcc-logs: Your GCS bucket name.
        • sfcc/: Prefix/folder path where logs are stored.

    • Source deletion option: Select the deletion option according to your preference:

      • Never: Never deletes any files after transfers (recommended for testing).
      • Delete transferred files: Deletes files after successful transfer.

      • Delete transferred files and empty directories: Deletes files and empty directories after successful transfer.

    • Maximum File Age: Include files modified in the last number of days (default is 180 days).

    • Asset namespace: The asset namespace.

    • Ingestion labels: The label to be applied to the events from this feed.

  11. Click Next.

  12. Review your new feed configuration in the Finalize screen, and then click Submit.

Grant IAM permissions to the Google SecOps service account

The Google SecOps service account needs Storage Object Viewer role on your GCS bucket.

  1. Go to Cloud Storage > Buckets.
  2. Click your bucket name (sfcc-logs).
  3. Go to the Permissions tab.
  4. Click Grant access.
  5. Provide the following configuration details:
    • Add principals: Paste the Google SecOps service account email.
    • Assign roles: Select Storage Object Viewer.

  6. Click Save.

UDM mapping table

Log Field UDM Mapping Logic
auth.mechanism extensions.auth.mechanism Merged
csv_format extensions.auth.mechanism Mapped: false → auth.mechanism
event_id extensions.auth.mechanism Mapped: Login: Success → auth.mechanism
mechanism extensions.auth.mechanism Merged
LoginType extensions.auth.type Mapped: Application → AUTHTYPE_UNSPECIFIED
csv_format extensions.auth.type Mapped: false → AUTHTYPE_UNSPECIFIED
event_id extensions.auth.type Mapped values (6 total, e.g. ` "Login", "LoginAsEvent", "IdentityVerificationEvent", "LoginE...
eventType.name metadata.description Directly mapped
metadata_description metadata.description Directly mapped
collected_timestamp metadata.event_timestamp Parsed as yyyyMMddHHmmss
createdAt metadata.event_timestamp Parsed as UNIX_MS
createdDate metadata.event_timestamp Parsed as yyyy-MM-ddTHH:mm:ss.SSS
timestamp metadata.event_timestamp Parsed as yyyyMMddHHmmss
ts_date metadata.event_timestamp Parsed as yyyy-MM-dd HH:mm:ss.SSSZ
csv_format metadata.event_type Mapped: false → USER_LOGIN, false → USER_LOGOUT, false → `USER_RESOURCE_UPDATE_CON...
event_id metadata.event_type Mapped: Login: Success → USER_LOGIN, Logout → USER_LOGOUT
event_type metadata.event_type Directly mapped
label metadata.ingestion_labels Merged
resource_name metadata.ingestion_labels Mapped: `"ReportEvent","SessionHijackingEventStore","BulkApiResultEventStore","CredentialStu...
attrs.cat metadata.product_event_type Renamed/mapped
eventType.id metadata.product_event_type Directly mapped
event_id metadata.product_event_type Directly mapped
event_identifier metadata.product_log_id Directly mapped
id metadata.product_log_id Directly mapped
protocol network.application_protocol Directly mapped
transaction_id network.dhcp.transaction_id Directly mapped
referral_url network.http.referral_url Directly mapped
request_status network.http.response_code Directly mapped
attrs.Application principal.application Renamed/mapped
enterpriseId principal.group.product_object_id Directly mapped
attrs.src principal.ip Merged
csv_format principal.ip Mapped: false → attrs.src
event_id principal.ip Mapped: Login: Success → attrs.src
Status_LK principal.labels Merged
Status_LK principal.resource.attribute.labels Merged
browser_name principal.resource.name Directly mapped
memberId principal.resource.product_object_id Directly mapped
principal_resource_type principal.resource.type Directly mapped
attrs.usrName principal.user.email_addresses Merged
csv_format principal.user.email_addresses Mapped: false → attrs.usrName
src_email principal.user.email_addresses Merged
attrs.USER_ID_DERIVED principal.user.product_object_id Renamed/mapped
employee.employeeName principal.user.user_display_name Directly mapped
user_display_name principal.user.user_display_name Directly mapped
attrs.usrName principal.user.userid Directly mapped
employee.userName principal.user.userid Directly mapped
login_key principal.user.userid Directly mapped
user_id principal.user.userid Directly mapped
csv_format security_result Mapped: false → sec_result
event_id security_result Mapped: Login: Success → sec_result
sec_result security_result Merged
sr security_result Merged
action security_result.action Merged
eventSource.name src.resource.name Directly mapped
eventSource.id src.resource.product_object_id Directly mapped
organization_id target.administrative_domain Directly mapped
target_hostname target.asset.hostname Directly mapped
device_id target.asset_id Directly mapped
target_hostname target.hostname Directly mapped
call_time target.resource.attribute.labels Merged
cpu target.resource.attribute.labels Merged
db_cpu target.resource.attribute.labels Merged
db_type target.resource.attribute.labels Merged
duration_time target.resource.attribute.labels Merged
entry_p target.resource.attribute.labels Merged
exe_time target.resource.attribute.labels Merged
no_sql_que target.resource.attribute.labels Merged
ope target.resource.attribute.labels Merged
rows_proc target.resource.attribute.labels Merged
run target.resource.attribute.labels Merged
ses_level target.resource.attribute.labels Merged
ss_type target.resource.attribute.labels Merged
total_time target.resource.attribute.labels Merged
user_ty target.resource.attribute.labels Merged
verify_method target.resource.attribute.labels Merged
attrs.AccountId target.resource.id Renamed/mapped
attrs.CaseId target.resource.id Renamed/mapped
attrs.ContactId target.resource.id Renamed/mapped
eventSource.id target.resource.id Directly mapped
request_id target.resource.id Directly mapped
eventSource.name target.resource.name Directly mapped
object.name target.resource.name Directly mapped
resource_name target.resource.name Directly mapped
object.id target.resource.product_object_id Directly mapped
event_id target.resource.resource_type Mapped: PlatformEncryption → ACCESS_POLICY, ApexCallout → ACCESS_POLICY, `ApexTrigge...
target_resource_type target.resource.resource_type Directly mapped
event_id target.resource.type Mapped: (QueuedExecution/ApexExecution) → BATCH, ApexTrigger → DATABASE_TRIGGER, `Co...
attrs.LoginUrl target.url Renamed/mapped
attrs.attributes.url target.url Renamed/mapped
uri target.url Directly mapped
attrs.usrName target.user.email_addresses Merged
csv_format target.user.email_addresses Mapped: false → attrs.usrName
event_id target.user.email_addresses Mapped: Logout → attrs.usrName
target_user_display_name target.user.user_display_name Directly mapped
target_user_name target.user.userid Directly mapped
N/A extensions.auth.auth_details Constant: ACTIVE
N/A extensions.auth.type Constant: SSO
N/A metadata.event_type Constant: GENERIC_EVENT
N/A metadata.product_name Constant: SALESFORCE
N/A metadata.vendor_name Constant: SALESFORCE
N/A target.resource.resource_type Constant: ACCESS_POLICY
N/A target.resource.type Constant: BATCH

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