Collect Swimlane Platform logs

Supported in:

Google secops SIEM

This document explains how to ingest Swimlane Platform logs to Google Security Operations using Google Cloud Storage. Swimlane Platform is a security orchestration, automation, and response (SOAR) platform that provides audit logging capabilities for tracking user activities, configuration changes, and system events across accounts and tenants.

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 Swimlane Platform with Account Admin permissions to access audit logs
Swimlane Platform instance URL and account credentials

Collect Swimlane Platform credentials

Get Swimlane Platform instance URL

Sign in to your Swimlane Platform instance.
Note your instance URL from the browser address bar.
- Format: https://<region>.swimlane.app (for example, https://us.swimlane.app or https://eu.swimlane.app)
- Example: If you access Swimlane at https://us.swimlane.app/workspace, your base URL is https://us.swimlane.app

Create Personal Access Token

Sign in to the Swimlane Platform as an Account Admin.
Go to Profile Options.
Click Profile to open the profile editor.
Navigate to the Personal Access Token section.
Click Generate token to create a new Personal Access Token.
Copy the token immediately and store it securely (it won't be shown again).

Get Account ID

Contact your Swimlane administrator if you don't know your Account ID. The Account ID is required for the Audit Log API path.

Record the following details for the integration:

Personal Access Token (PAT): Used in the Private-Token header for API calls.
Account ID: Required for the Audit Log API path /api/public/audit/account/{ACCOUNT_ID}/auditlogs.
Base URL: Your Swimlane domain (for example, https://eu.swimlane.app, https://us.swimlane.app).

Verify permissions

To verify your account has the required permissions to access audit logs:

Sign in to Swimlane Platform.
Confirm you have Account Admin access.
Contact your Swimlane administrator if you cannot access audit log features.

Note: Audit log access requires Account Admin privileges in Swimlane Platform. Only Account Admins can access the Audit Logs API.

Test API access

Before proceeding with the integration, verify your API credentials work correctly:

# Replace with your actual credentials
SWIMLANE_BASE_URL="https://<region>.swimlane.app"
SWIMLANE_ACCOUNT_ID="<your-account-id>"
SWIMLANE_PAT_TOKEN="<your-personal-access-token>"

# Test API access
curl -v -X GET "${SWIMLANE_BASE_URL}/api/public/audit/account/${SWIMLANE_ACCOUNT_ID}/auditlogs?pageNumber=1&pageSize=10" \
  -H "Private-Token: ${SWIMLANE_PAT_TOKEN}" \
  -H "Accept: application/json"

Expected response: HTTP 200 with JSON containing audit logs.

If you receive errors:

HTTP 401: Verify your Personal Access Token is correct
HTTP 403: Verify your account has Account Admin permissions
HTTP 404: Verify the Account ID and base URL are correct

Create Google Cloud Storage bucket

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

Provide the following configuration details:

Setting	Value
Name your bucket	Enter a globally unique name (for example, `swimlane-audit`)
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

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

In the GCP Console, go to IAM & Admin > Service Accounts.
Click Create Service Account.
Provide the following configuration details:
- Service account name: Enter swimlane-audit-collector-sa.
- Service account description: Enter Service account for Cloud Run function to collect Swimlane Platform logs.
Click Create and Continue.
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.
Click Continue.
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:

Go to Cloud Storage > Buckets.
Click your bucket name.
Go to the Permissions tab.
Click Grant access.
Provide the following configuration details:
- Add principals: Enter the service account email (for example, swimlane-audit-collector-sa@PROJECT_ID.iam.gserviceaccount.com).
- Assign roles: Select Storage Object Admin.
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.

In the GCP Console, go to Pub/Sub > Topics.
Click Create topic.
Provide the following configuration details:
- Topic ID: Enter swimlane-audit-trigger.
- Leave other settings as default.
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 Swimlane Platform API and writes them to GCS.

In the GCP Console, go to Cloud Run.
Click Create service.
Select Function (use an inline editor to create a function).
In the Configure section, provide the following configuration details:

Setting Value

Service name swimlane-audit-collector

Region Select region matching your GCS bucket (for example, us-central1)

Runtime Select Python 3.12 or later
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 (swimlane-audit-trigger).
4. Click Save.
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.
Scroll down and expand Containers, Networking, Security.
Go to the Security tab:
- Service account: Select the service account (swimlane-audit-collector-sa).

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

Go to the Containers tab:

Click Variables & Secrets.
Click + Add variable for each environment variable:

Variable Name	Example Value	Description
`GCS_BUCKET`	`swimlane-audit`	GCS bucket name
`GCS_PREFIX`	`swimlane/audit/`	Prefix for log files
`STATE_KEY`	`swimlane/audit/state.json`	State file path
`SWIMLANE_BASE_URL`	`https://us.swimlane.app`	Swimlane Platform base URL
`SWIMLANE_PAT_TOKEN`	`your-personal-access-token`	Swimlane Personal Access Token
`SWIMLANE_ACCOUNT_ID`	`your-account-id`	Swimlane account identifier
`SWIMLANE_TENANT_LIST`	``	Comma-separated tenant IDs (optional, leave empty for all tenants)
`INCLUDE_ACCOUNT`	`true`	Include account-level logs (true/false)
`PAGE_SIZE`	`100`	Records per page (max 100)
`LOOKBACK_HOURS`	`24`	Initial lookback period
`TIMEOUT`	`30`	API request timeout in seconds

In the Variables & Secrets section, scroll down to Requests:
- Request timeout: Enter 600 seconds (10 minutes).
Go to the Settings tab:
- In the Resources section:
  - Memory: Select 512 MiB or higher.
  - CPU: Select 1.
In the Revision scaling section:
- Minimum number of instances: Enter 0.
- Maximum number of instances: Enter 100 (or adjust based on expected load).
Click Create.
Wait for the service to be created (1-2 minutes).
After the service is created, the inline code editor opens automatically.

Add function code

Enter main in Function entry point

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 uuid
import gzip
import io

# 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', 'swimlane/audit/')
STATE_KEY = os.environ.get('STATE_KEY', 'swimlane/audit/state.json')
SWIMLANE_BASE_URL = os.environ.get('SWIMLANE_BASE_URL', '').rstrip('/')
SWIMLANE_PAT_TOKEN = os.environ.get('SWIMLANE_PAT_TOKEN')
SWIMLANE_ACCOUNT_ID = os.environ.get('SWIMLANE_ACCOUNT_ID')
SWIMLANE_TENANT_LIST = os.environ.get('SWIMLANE_TENANT_LIST', '')
INCLUDE_ACCOUNT = os.environ.get('INCLUDE_ACCOUNT', 'true').lower() == 'true'
PAGE_SIZE = int(os.environ.get('PAGE_SIZE', '100'))
LOOKBACK_HOURS = int(os.environ.get('LOOKBACK_HOURS', '24'))
TIMEOUT = int(os.environ.get('TIMEOUT', '30'))

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 Swimlane Platform logs and write to GCS.

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

    if not all([GCS_BUCKET, SWIMLANE_BASE_URL, SWIMLANE_PAT_TOKEN, SWIMLANE_ACCOUNT_ID]):
        print('Error: Missing required environment variables (GCS_BUCKET, SWIMLANE_BASE_URL, SWIMLANE_PAT_TOKEN, SWIMLANE_ACCOUNT_ID)')
        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"])
                # Overlap by 2 minutes to catch any delayed events
                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 logs
        records, newest_event_time = fetch_logs(
            base_url=SWIMLANE_BASE_URL,
            pat_token=SWIMLANE_PAT_TOKEN,
            account_id=SWIMLANE_ACCOUNT_ID,
            tenant_list=SWIMLANE_TENANT_LIST,
            include_account=INCLUDE_ACCOUNT,
            start_time=last_time,
            end_time=now,
            page_size=PAGE_SIZE,
        )

        if not records:
            print("No new log records found.")
            save_state(bucket, STATE_KEY, now.isoformat())
            return

        # Write to GCS as gzipped NDJSON
        timestamp = now.strftime('%Y%m%d_%H%M%S')
        object_key = f"{GCS_PREFIX}{now:%Y/%m/%d}/swimlane-audit-{uuid.uuid4()}.json.gz"

        buf = io.BytesIO()
        with gzip.GzipFile(fileobj=buf, mode='w') as gz:
            for record in records:
                gz.write((json.dumps(record, ensure_ascii=False) + '\n').encode())

        buf.seek(0)
        blob = bucket.blob(object_key)
        blob.upload_from_file(buf, content_type='application/gzip')

        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,
            'updated_at': datetime.now(timezone.utc).isoformat() + 'Z'
        }
        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_logs(base_url: str, pat_token: str, account_id: str, tenant_list: str, include_account: bool, start_time: datetime, end_time: datetime, page_size: int):
    """
    Fetch logs from Swimlane Platform API with pagination and rate limiting.

    Args:
        base_url: Swimlane Platform base URL
        pat_token: Personal Access Token
        account_id: Swimlane account identifier
        tenant_list: Comma-separated tenant IDs (optional)
        include_account: Include account-level logs
        start_time: Start time for log query
        end_time: End time for log query
        page_size: Number of records per page (max 100)

    Returns:
        Tuple of (records list, newest_event_time ISO string)
    """

    endpoint = f"{base_url}/api/public/audit/account/{account_id}/auditlogs"

    headers = {
        'Private-Token': pat_token,
        'Accept': 'application/json',
        'Content-Type': 'application/json',
        'User-Agent': 'GoogleSecOps-SwimlaneCollector/1.0'
    }

    records = []
    newest_time = None
    page_num = 1
    backoff = 1.0

    while True:
        params = []
        params.append(f"pageNumber={page_num}")
        params.append(f"pageSize={min(page_size, 100)}")
        params.append(f"fromdate={start_time.isoformat()}")
        params.append(f"todate={end_time.isoformat()}")

        if tenant_list:
            params.append(f"tenantList={tenant_list}")

        params.append(f"includeAccount={'true' if include_account else 'false'}")

        url = f"{endpoint}?{'&'.join(params)}"

        try:
            response = http.request('GET', url, headers=headers, timeout=TIMEOUT)

            # 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 == 401:
                print(f"Authentication failed (401). Verify SWIMLANE_PAT_TOKEN is correct.")
                return [], None

            if response.status == 403:
                print(f"Access forbidden (403). Verify account has Account Admin permissions to access audit logs.")
                return [], None

            if response.status == 400:
                print(f"Bad request (400). Verify account_id and query parameters are correct.")
                response_text = response.data.decode('utf-8')
                print(f"Response body: {response_text}")
                return [], None

            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'))

            page_results = data.get('auditlogs', [])

            if not page_results:
                print(f"No more results (empty page)")
                break

            print(f"Page {page_num}: Retrieved {len(page_results)} events")
            records.extend(page_results)

            # Track newest event time
            for event in page_results:
                try:
                    event_time = event.get('eventTime') or event.get('EventTime')
                    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
            has_next = data.get('next')
            total_count = data.get('totalCount', 0)

            if not has_next:
                print(f"Reached last page (no next link)")
                break

            # Check if we've hit the 10,000 log limit
            if total_count > 10000 and len(records) >= 10000:
                print(f"Warning: Reached Swimlane API limit of 10,000 logs. Consider narrowing the time range.")
                break

            page_num += 1

        except Exception as e:
            print(f"Error fetching logs: {e}")
            return [], None

    print(f"Retrieved {len(records)} total records from {page_num} pages")
    return records, newest_time

Second file: requirements.txt:

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

Click Deploy to save and deploy the function.
Wait for deployment to complete (2-3 minutes).

Note: The Swimlane audit log API has a limit of 10,000 logs per request. If you have high log volume, adjust the LOOKBACK_HOURS and Cloud Scheduler frequency to ensure you stay within this limit.
Note: Data retention for Swimlane audit logs is limited to 7 days. Ensure your Cloud Scheduler runs frequently enough to capture all logs before they expire.
Note: The Pub/Sub trigger configuration automatically creates the necessary subscriptions and permissions.

Create Cloud Scheduler job

Cloud scheduler publishes messages to the Pub/Sub topic at regular intervals, triggering the Cloud Run function.

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

Provide the following configuration details:

Setting	Value
Name	`swimlane-audit-schedule-15min`
Region	Select same region as Cloud Run function
Frequency	`/15 * * *` (every 15 minutes)
Timezone	Select timezone (UTC recommended)
Target type	Pub/Sub
Topic	Select the Pub/Sub topic (`swimlane-audit-trigger`)
Message body	`{}` (empty JSON object)

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 * * *`	Standard (recommended)
Every hour	`0 * * * *`	Medium volume
Every 6 hours	`0 /6 * *`	Low volume, batch processing
Daily	`0 0 * * *`	Historical data collection

Test the integration

In the Cloud Scheduler console, find your job.
Click Force run to trigger the job manually.
Wait a few seconds.
Go to Cloud Run > Services.
Click on your function name (swimlane-audit-collector).
Click the Logs tab.

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 X records to gs://bucket-name/swimlane/audit/YYYY/MM/DD/swimlane-audit-UUID.json.gz
Successfully processed X records

Go to Cloud Storage > Buckets.
Click your bucket name.
Navigate to the prefix folder (swimlane/audit/).
Verify that a new .json.gz file was created with the current timestamp.

If you see errors in the logs:

HTTP 401: Check SWIMLANE_PAT_TOKEN in environment variables and verify the Personal Access Token is correct
HTTP 403: Verify account has Account Admin permissions to access audit logs
HTTP 400: Verify SWIMLANE_ACCOUNT_ID is correct and query parameters are valid
HTTP 404: Verify SWIMLANE_BASE_URL and API endpoint path are correct
HTTP 429: Rate limiting - function will automatically retry with backoff
Missing environment variables: Check all required variables are set (GCS_BUCKET, SWIMLANE_BASE_URL, SWIMLANE_PAT_TOKEN, SWIMLANE_ACCOUNT_ID)
Connection errors: Verify network connectivity to Swimlane Platform and firewall rules
10,000 log limit warning: Reduce LOOKBACK_HOURS or increase Cloud Scheduler frequency to stay within Swimlane's API limit

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

Go to SIEM Settings > Feeds.
Click Add New Feed.
Click Configure a single feed.
In the Feed name field, enter a name for the feed (for example, Swimlane Platform logs).
Select Google Cloud Storage V2 as the Source type.
Select Swimlane Platform as the Log type.
Click Get Service Account. A unique service account email is displayed, for example:
```
chronicle-12345678@chronicle-gcp-prod.iam.gserviceaccount.com
```
Copy this email address for use in the next step.

Note: Each Google SecOps instance has a unique service account. Do not 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.

Go to Cloud Storage > Buckets.
Click your bucket name.
Go to the Permissions tab.
Click Grant access.
Provide the following configuration details:
- Add principals: Paste the Google SecOps service account email.
- Assign roles: Select Storage Object Viewer.
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 Swimlane Platform logs

Go to SIEM Settings > Feeds.
Click Add New Feed.
Click Configure a single feed.
In the Feed name field, enter a name for the feed (for example, Swimlane Platform logs).
Select Google Cloud Storage V2 as the Source type.
Select Swimlane Platform as the Log type.
Click Next.
Specify values for the following input parameters:
- Storage bucket URL: Enter the GCS bucket URI with the prefix path:
```
gs://swimlane-audit/swimlane/audit/
```
  - Replace:
    - swimlane-audit: Your GCS bucket name.
    - swimlane/audit/: 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.
Click Next.
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.