Collect Recordia logs

Supported in:

Google secops SIEM

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

Recordia (by Comunycarse) is a call recording and compliance platform for financial services and contact centers. It captures and archives voice and video interactions, providing tools for quality management, regulatory compliance, and analytics. The parser extracts fields from Recordia call metadata and audit events and maps them to the Unified Data Model (UDM), capturing session details, caller/callee information, user activity, and security severity.

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 the Recordia platform with API access enabled (contact Comunycarse support to obtain API credentials)

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, recordia-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 Recordia API credentials

Obtain API credentials

1. Contact your Recordia account manager or Comunycarse support to request API access.

2. Obtain the following credentials:

   • API Base URL: The base URL for your Recordia instance (for example, https://api.recordia.net)
   • API Token: A Bearer token for authentication
   Note: The API credentials and endpoints may vary by deployment. Consult your Recordia API documentation for the exact authentication method and available endpoints.

Verify permissions

To verify the API credentials have the required permissions:

1. Sign in to the Recordia administration portal.
2. Navigate to the Settings or API section.
3. Confirm that your account has API access enabled.
4. If you cannot access the API settings, contact Comunycarse support.

Test API access

• Test your credentials before proceeding with the integration:

  # Replace with your actual credentials
  API_TOKEN="<your-api-token>"
  API_BASE="https://api.recordia.net"
  
  # Test API access - list recordings
  curl -v -H "Authorization: Bearer ${API_TOKEN}" \
    "${API_BASE}/v1/recordings?from=2024-01-01T00:00:00Z&to=2024-01-02T00:00:00Z"
  

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 recordia-collector-sa
   • Service account description: Enter Service account for Cloud Run function to collect Recordia 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 on your bucket name (for example, recordia-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, recordia-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 recordia-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 recording metadata and audit events from the Recordia API 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	recordia-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 (recordia-logs-trigger).
   4. Click Save.

6. In the Authentication section:

   1. Select Require authentication.
   2. Check Identity and Access Management (IAM).
   Note: Pub/Sub will automatically handle 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 (recordia-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	recordia-logs	GCS bucket name
   GCS_PREFIX	recordia	Prefix for log files
   STATE_KEY	recordia/state.json	State file path
   API_BASE	https://api.recordia.net	Recordia API base URL
   API_TOKEN	your-bearer-token	Recordia API Bearer token
   MAX_RECORDS	1000	Max records per run
   PAGE_SIZE	100	Records per page
   LOOKBACK_HOURS	24	Initial lookback period

10. In the Variables & Secrets section, scroll down 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 will open automatically.

Add function code

1. Enter main in the Entry point field.

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
     
     # 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()
     
     # Environment variables
     GCS_BUCKET = os.environ.get('GCS_BUCKET')
     GCS_PREFIX = os.environ.get('GCS_PREFIX', 'recordia')
     STATE_KEY = os.environ.get('STATE_KEY', 'recordia/state.json')
     API_BASE = os.environ.get('API_BASE')
     API_TOKEN = os.environ.get('API_TOKEN')
     MAX_RECORDS = int(os.environ.get('MAX_RECORDS', '1000'))
     PAGE_SIZE = int(os.environ.get('PAGE_SIZE', '100'))
     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 Recordia
       recording metadata and audit events and write to GCS.
     
       Args:
         cloud_event: CloudEvent object containing Pub/Sub message
       """
     
       if not all([GCS_BUCKET, API_BASE, API_TOKEN]):
         print('Error: Missing required environment variables')
         return
     
       try:
         # Get GCS bucket
         bucket = storage_client.bucket(GCS_BUCKET)
     
         # Load state
         state = load_state(bucket, STATE_KEY)
     
         # Determine time window
         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"])
             last_time = last_time - timedelta(minutes=2)
           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 from {last_time.isoformat()} to {now.isoformat()}")
     
         # Fetch recordings
         records, newest_event_time = fetch_recordings(
           api_base=API_BASE,
           token=API_TOKEN,
           start_time=last_time,
           end_time=now,
           page_size=PAGE_SIZE,
           max_records=MAX_RECORDS,
         )
     
         if not records:
           print("No new log records found.")
           save_state(bucket, STATE_KEY, now.isoformat())
           return
     
         # Write to GCS as NDJSON
         timestamp = now.strftime('%Y%m%d_%H%M%S')
         object_key = f"{GCS_PREFIX}/logs_{timestamp}.ndjson"
         blob = bucket.blob(object_key)
     
         ndjson = '\n'.join([json.dumps(record, ensure_ascii=False) for record in records]) + '\n'
         blob.upload_from_string(ndjson, content_type='application/x-ndjson')
     
         print(f"Wrote {len(records)} records to gs://{GCS_BUCKET}/{object_key}")
     
         # Update state with newest event time
         if newest_event_time:
           save_state(bucket, STATE_KEY, newest_event_time)
         else:
           save_state(bucket, STATE_KEY, now.isoformat())
     
         print(f"Successfully processed {len(records)} records")
     
       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 fetch_recordings(api_base: str, token: str, start_time: datetime, end_time: datetime, page_size: int, max_records: int):
       """
       Fetch recording metadata from Recordia API with pagination.
     
       Args:
         api_base: API base URL
         token: Bearer token for authentication
         start_time: Start time for log query
         end_time: End time for log query
         page_size: Number of records per page
         max_records: Maximum total records to fetch
     
       Returns:
         Tuple of (records list, newest_event_time ISO string)
       """
       base_url = api_base.rstrip('/')
       endpoint = f"{base_url}/v1/recordings"
     
       headers = {
         'Authorization': f'Bearer {token}',
         'Accept': 'application/json',
         'Content-Type': 'application/json',
         'User-Agent': 'GoogleSecOps-RecordiaCollector/1.0',
       }
     
       records = []
       newest_time = None
       page_num = 0
       backoff = 1.0
       offset = 0
     
       from_time = start_time.strftime('%Y-%m-%dT%H:%M:%SZ')
       to_time = end_time.strftime('%Y-%m-%dT%H:%M:%SZ')
     
       while True:
         page_num += 1
     
         if len(records) >= max_records:
           print(f"Reached max_records limit ({max_records})")
           break
     
         current_limit = min(page_size, max_records - len(records))
         url = f"{endpoint}?from={from_time}&to={to_time}&offset={offset}&limit={current_limit}"
     
         try:
           response = http.request('GET', url, headers=headers)
     
           # Handle rate limiting with exponential backoff
           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
     
           backoff = 1.0
     
           if response.status != 200:
             print(f"HTTP Error: {response.status}")
             response_text = response.data.decode('utf-8')
             print(f"Response body: {response_text}")
             return [], None
     
           data = json.loads(response.data.decode('utf-8'))
     
           if isinstance(data, list):
             page_results = data
           else:
             page_results = data.get('recordings', data.get('results', []))
     
           if not page_results:
             print(f"No more results (empty page)")
             break
     
           print(f"Page {page_num}: Retrieved {len(page_results)} recordings")
           records.extend(page_results)
     
           # Track newest event time
           for event in page_results:
             try:
               event_time = event.get('startTime') or event.get('timestamp') or event.get('date')
               if event_time:
                 if newest_time is None or parse_datetime(event_time) > parse_datetime(newest_time):
                   newest_time = event_time
             except Exception as e:
               print(f"Warning: Could not parse event time: {e}")
     
           # Check for more results
           if len(page_results) < current_limit:
             print(f"Reached last page (size={len(page_results)} < limit={current_limit})")
             break
     
           offset += len(page_results)
     
         except Exception as e:
           print(f"Error fetching recordings: {e}")
           return [], None
     
       print(f"Retrieved {len(records)} total recordings from {page_num} pages")
       return records, newest_time
     

   • 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	recordia-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 (recordia-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.
2. Click Force run to trigger the job manually.
3. Wait a few seconds.
4. Go to Cloud Run > Services.
5. Click on your function name (recordia-collector).
6. Click the Logs tab.

7. Verify the function executed successfully. Look for:

   Fetching logs from YYYY-MM-DDTHH:MM:SS+00:00 to YYYY-MM-DDTHH:MM:SS+00:00
   Page 1: Retrieved X recordings
   Wrote X records to gs://recordia-logs/recordia/logs_YYYYMMDD_HHMMSS.ndjson
   Successfully processed X records
   

8. Go to Cloud Storage > Buckets.

9. Click on your bucket name (recordia-logs).

10. Navigate to the prefix folder (recordia/).

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

If you see errors in the logs:

• HTTP 401: Check the API token in environment variables
• HTTP 403: Verify the API token has access to the recordings endpoint
• 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, Recordia Logs).
5. Select Google Cloud Storage V2 as the Source type.
6. Select Recordia as the Log type.
7. Click Get Service Account.

8. A unique service account email will be displayed, for example:

   [e-mail]
   

9. 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.

10. Click Next.

11. Specify values for the following input parameters:

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

      gs://recordia-logs/recordia/
      

      • Replace:
        • recordia-logs: Your GCS bucket name.
        • recordia: Optional prefix/folder path where logs are stored (leave empty for root).
    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

12. Click Next.

13. 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 on your bucket name (for example, recordia-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.

UDM mapping table

Log Field	UDM Mapping	Logic
record_id, batch_id, ProviderId, ProviderGroupId, TrackingId, RecordingType, Format, Owner, NotEncrypted, Hash, CustomData, CustomDataFormat	additional.fields	Merged with label objects constructed from each field if not empty, where label.key is set to a specific string and label.value.string_value to the field value
client_ip,client_ip1	intermediary.ip	Merged with client_ip, then merged with client_ip1
corp_user	intermediary.user.userid	Value copied directly
description	metadata.description	Value copied directly
auth_user,src_ip	metadata.event_type	Set to "USER_UNCATEGORIZED" if auth_user not empty, else "STATUS_UNCATEGORIZED" if src_ip not empty, else "GENERIC_EVENT"
	metadata.product_event_type	Set to "RECORDING BATCH" if event_info matches 'RECORDING BATCH'
CallId	metadata.product_log_id	Value copied directly
user_agent	network.http.parsed_user_agent	Value copied and converted to parseduseragent type
user_agent	network.http.user_agent	Value copied directly
session_id	network.session_id	Value copied directly
src_ip	principal.ip	Value copied directly
url	principal.url	Value copied directly
CallingParty	principal.user.phone_numbers	Value copied directly
auth_user	principal.user.userid	Value copied directly
severity	security_result.action_details	Value copied directly if severity in ["INFO", "DEBUG"]
severity	security_result.severity	Set to "LOW" if severity in ["INFO", "DEBUG"]
CalledParty	target.user.phone_numbers	Value copied directly
	metadata.vendor_name	Set to "Comunycarse"
	metadata.product_name	Set to "Recordia"

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