Collect PingOne Advanced Identity Cloud logs

Supported in:

Google secops SIEM

Note: This feature is covered by Pre-GA Offerings Terms of the Google Security Operations Service Specific Terms. Pre-GA features might have limited support, and changes to pre-GA features might not be compatible with other pre-GA versions. For more information, see the Google SecOps Technical Support Service guidelines and the Google SecOps Service Specific Terms.

This document explains how to ingest PingOne Advanced Identity Cloud logs to Google Security Operations using Google Cloud Storage. PingOne Advanced Identity Cloud is an identity and access management platform that provides authentication, authorization, and user management capabilities for cloud-based applications.

Before you begin

Ensure that 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 PingOne Advanced Identity Cloud tenant

Get PingOne API key and tenant FQDN

1. Sign in to the Advanced Identity Cloud admin console.
2. Click the user icon > Tenant Settings.
3. On the Global Settings tab, click Log API Keys.
4. Click New Log API Key, provide a name for the key.
5. Click Create Key.
6. Copy and save the api_key_id and api_key_secret values in a secure location. The api_key_secret value is not displayed again.
7. Click Done.

8. Go to Tenant Settings > Details, and find your tenant FQDN (for example, example.tomcat.pingone.com).

   Note: PingOne Advanced Identity Cloud retains audit and debug logs for 30 days. The API cannot retrieve data older than this retention period. Plan your collection frequency accordingly.

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, pingone-aic-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.

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 pingone-aic-collector-sa.
   • Service account description: Enter Service account for Cloud Run function to collect PingOne Advanced Identity 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.
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, pingone-aic-collector-sa@PROJECT_ID.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 pingone-aic-trigger.
   • Leave other settings as default.
4. Click Create.

Create Cloud Run function to collect logs

The Cloud Run function is triggered by Pub/Sub messages from Cloud Scheduler to fetch logs from PingOne Advanced Identity Cloud API and writes 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	pingone-aic-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 Pub/Sub topic (pingone-aic-trigger).
   4. Click Save.

6. In the Authentication section:

   1. Select Require authentication.
   2. Check Identity and Access Management (IAM).
   Note: Pub/Sub automatically handles authentication when invoking the function.

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

8. Go to the Security tab:

   • Service account: Select the service account (pingone-aic-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	pingone-aic-logs	GCS bucket name
   GCS_PREFIX	pingone-aic/logs	Prefix for log files
   STATE_KEY	pingone-aic/logs/state.json	State file path
   AIC_TENANT_FQDN	example.tomcat.pingone.com	Tenant FQDN
   AIC_API_KEY_ID	your-api-key-id	API key ID
   AIC_API_SECRET	your-api-key-secret	API key secret
   SOURCES	am-everything,idm-everything	Comma-separated log sources (see note below)
   PAGE_SIZE	500	Records per page
   MAX_PAGES	20	Maximum pages per run
   LOOKBACK_SECONDS	3600	Initial lookback period

   Note: The SOURCES value shown above contains common default log sources. To discover all available log sources for your tenant, call the /monitoring/logs/sources endpoint. Available sources may include am-access, am-activity, am-authentication, am-core, idm-authentication, idm-core, idm-sync, and others. Configure the SOURCES environment variable with the appropriate comma-separated list for your deployment.

10. In the Variables & Secrets section, scroll to Requests:

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

11. Go to the Settings tab:

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

12. In the Revision scaling section:

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

13. Click Create.

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

15. After the service is created, the inline code editor opens 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
   import time
   
   # Initialize HTTP client with timeouts
   http = urllib3.PoolManager(
       timeout=urllib3.Timeout(connect=5.0, read=30.0),
       retries=False,
   )
   
   # Initialize Storage client
   storage_client = storage.Client()
   
   @functions_framework.cloud_event
   def main(cloud_event):
       """
       Cloud Run function triggered by Pub/Sub to fetch logs from PingOne Advanced Identity Cloud API and write to GCS.
   
       Args:
           cloud_event: CloudEvent object containing Pub/Sub message
       """
   
       # Get environment variables
       bucket_name = os.environ.get('GCS_BUCKET')
       prefix = os.environ.get('GCS_PREFIX', 'pingone-aic/logs')
       state_key = os.environ.get('STATE_KEY', 'pingone-aic/logs/state.json')
   
       fqdn = os.environ.get('AIC_TENANT_FQDN', '').strip('/')
       api_key_id = os.environ.get('AIC_API_KEY_ID')
       api_key_secret = os.environ.get('AIC_API_SECRET')
   
       sources = [s.strip() for s in os.environ.get('SOURCES', 'am-everything,idm-everything').split(',') if s.strip()]
       page_size = min(int(os.environ.get('PAGE_SIZE', '500')), 1000)
       max_pages = int(os.environ.get('MAX_PAGES', '20'))
       lookback_seconds = int(os.environ.get('LOOKBACK_SECONDS', '3600'))
   
       if not all([bucket_name, fqdn, api_key_id, api_key_secret]):
           print('Error: Missing required environment variables')
           return
   
       try:
           # Get GCS bucket
           bucket = storage_client.bucket(bucket_name)
   
           # Load state
           state = load_state(bucket, state_key)
           state.setdefault('sources', {})
   
           summary = []
   
           for source in sources:
               last_ts = state['sources'].get(source, {}).get('last_ts')
               res = fetch_source(bucket, prefix, fqdn, api_key_id, api_key_secret, source, last_ts, page_size, max_pages, lookback_seconds)
   
               if res.get('newest_ts'):
                   state['sources'][source] = {'last_ts': res['newest_ts']}
   
               summary.append(res)
   
           # Save state
           save_state(bucket, state_key, state)
   
           print(f'Successfully processed logs: {json.dumps(summary)}')
   
       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: {str(e)}')
       return {'sources': {}}
   
   def save_state(bucket, key, state):
       """Save state to GCS."""
       try:
           blob = bucket.blob(key)
           blob.upload_from_string(
               json.dumps(state, separators=(',', ':')),
               content_type='application/json'
           )
       except Exception as e:
           print(f'Warning: Could not save state: {str(e)}')
   
   def fetch_source(bucket, prefix, fqdn, api_key_id, api_key_secret, source, last_ts, page_size, max_pages, lookback_seconds):
       """Fetch logs for a specific source."""
       base_url = f"https://{fqdn}/monitoring/logs"
       now = time.time()
   
       begin_time = bounded_begin_time(last_ts, now, lookback_seconds)
   
       params = {
           'source': source,
           '_pageSize': str(page_size),
           '_sortKeys': 'timestamp',
           'beginTime': begin_time
       }
   
       headers = {
           'x-api-key': api_key_id,
           'x-api-secret': api_key_secret
       }
   
       pages = 0
       written = 0
       newest_ts = last_ts
       cookie = None
   
       while pages < max_pages:
           if cookie:
               params['_pagedResultsCookie'] = cookie
   
           # Build query string
           query_parts = [f"{k}={v}" for k, v in params.items()]
           query_string = '&'.join(query_parts)
           url = f"{base_url}?{query_string}"
   
           # Make request with retry logic
           data = http_get_with_retry(url, headers)
   
           # Write page to GCS
           write_page(bucket, prefix, data, source)
   
           # Process results
           results = data.get('result') or data.get('results') or []
           for item in results:
               t = item.get('timestamp') or item.get('payload', {}).get('timestamp')
               if t and (newest_ts is None or t > newest_ts):
                   newest_ts = t
   
           written += len(results)
           cookie = data.get('pagedResultsCookie')
           pages += 1
   
           if not cookie:
               break
   
       return {
           'source': source,
           'pages': pages,
           'written': written,
           'newest_ts': newest_ts
       }
   
   def http_get_with_retry(url, headers, timeout=60, max_retries=5):
       """Make HTTP GET request with retry logic."""
       attempt = 0
       backoff = 1.0
   
       while True:
           try:
               response = http.request('GET', url, headers=headers, timeout=timeout)
   
               if response.status == 429 and attempt < max_retries:
                   # Rate limited - check for X-RateLimit-Reset header
                   reset_header = response.headers.get('X-RateLimit-Reset')
                   if reset_header:
                       delay = max(1, int(reset_header) - int(time.time()))
                   else:
                       delay = int(backoff)
   
                   print(f'Rate limited, waiting {delay} seconds')
                   time.sleep(delay)
                   attempt += 1
                   backoff *= 2
                   continue
   
               if 500 <= response.status < 600 and attempt < max_retries:
                   print(f'Server error {response.status}, retrying in {backoff} seconds')
                   time.sleep(backoff)
                   attempt += 1
                   backoff *= 2
                   continue
   
               if response.status != 200:
                   raise Exception(f'HTTP {response.status}: {response.data.decode("utf-8")}')
   
               return json.loads(response.data.decode('utf-8'))
   
           except Exception as e:
               if attempt < max_retries:
                   print(f'Request failed: {str(e)}, retrying in {backoff} seconds')
                   time.sleep(backoff)
                   attempt += 1
                   backoff *= 2
                   continue
               raise
   
   def write_page(bucket, prefix, payload, source):
       """Write a page of logs to GCS."""
       ts = datetime.now(timezone.utc)
       blob_name = f"{prefix}/{ts.strftime('%Y/%m/%d/%H%M%S')}-pingone-aic-{source}.json"
   
       blob = bucket.blob(blob_name)
       blob.upload_from_string(
           json.dumps(payload, separators=(',', ':')),
           content_type='application/json'
       )
   
       print(f'Wrote logs to {blob_name}')
   
   def bounded_begin_time(last_ts, now, lookback_seconds):
       """Calculate begin time bounded by 24 hour limit."""
       twenty_four_h_ago = now - 24 * 3600
   
       if last_ts:
           try:
               # Parse ISO timestamp
               t_struct = time.strptime(last_ts[:19] + 'Z', '%Y-%m-%dT%H:%M:%SZ')
               t_epoch = int(time.mktime(t_struct))
           except Exception:
               t_epoch = int(now - lookback_seconds)
   
           begin_epoch = max(t_epoch, int(twenty_four_h_ago))
       else:
           begin_epoch = max(int(now - lookback_seconds), int(twenty_four_h_ago))
   
       return time.strftime('%Y-%m-%dT%H:%M:%SZ', time.gmtime(begin_epoch))
   

   • 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).

   Note: The Pub/Sub trigger configuration automatically creates the necessary subscriptions and permissions.

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	pingone-aic-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 Pub/Sub topic (pingone-aic-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 (pingone-aic-collector-hourly).
2. Click Force run to trigger the job manually.
3. Wait a few seconds.
4. Go to Cloud Run > Services.
5. Click the function name (pingone-aic-collector).
6. Click the Logs tab.

7. Verify the function executed successfully. Look for the following:

   Fetching logs from YYYY-MM-DDTHH:MM:SS+00:00 to YYYY-MM-DDTHH:MM:SS+00:00
   Page 1: Retrieved X events
   Wrote logs to gs://bucket-name/prefix/logs_YYYYMMDD_HHMMSS.json
   Successfully processed X records
   

8. Go to Cloud Storage > Buckets.

9. Click your bucket name (pingone-aic-logs).

10. Navigate to the prefix folder (pingone-aic/logs/).

11. Verify that a new .json file was created with the current timestamp.

If you see errors in the logs:

• HTTP 401: Check API credentials in environment variables
• HTTP 403: Verify account has required permissions
• HTTP 429: Rate limiting - function will automatically retry with backoff
• Missing environment variables: Check all required variables are set

Retrieve the Google SecOps service account

Google SecOps uses a unique service account to read data from your GCS bucket. You must grant this service account access to your bucket.

Get the service account email

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, PingOne Advanced Identity Cloud).
5. Select Google Cloud Storage V2 as the Source type.
6. Select PingOne Advanced Identity Cloud as the Log type.

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

   [e-mail]
   

8. Copy this email address for use in the next step.

   Note: Each Google SecOps instance has a unique service account. Don't use service accounts from other documentation or examples.

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 (pingone-aic-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.

   Note: If you plan to use the deletion option "Delete transferred files" or "Delete transferred files and empty directories," grant Storage Object Admin role instead of Storage Object Viewer.

Configure a feed in Google SecOps to ingest PingOne Advanced Identity 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, PingOne Advanced Identity Cloud).
5. Select Google Cloud Storage V2 as the Source type.
6. Select PingOne Advanced Identity Cloud as the Log type.
7. Click Next.

8. Specify values for the following input parameters:

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

     gs://pingone-aic-logs/pingone-aic/logs/
     

     • Replace:

       • pingone-aic-logs: Your GCS bucket name.
       • pingone-aic/logs/: Optional prefix/folder path where logs are stored.
     Note: Always include the trailing slash (/) at the end of the URI.

   • 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.

       Note: If you select a deletion option, the service account must have Storage Object Admin role instead of Storage Object Viewer. Update IAM permissions accordingly.

   • 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.

9. Click Next.

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

Need more help? Get answers from Community members and Google SecOps professionals.