Collect Sentry logs

Supported in:

Google secops SIEM

This document explains how to ingest Sentry logs to Google Security Operations using Google Cloud Storage. Sentry produces operational data in the form of events, issues, performance monitoring data, and error tracking information. This integration lets you send these logs to Google SecOps for analysis and monitoring, providing visibility into application errors, performance issues, and user interactions within your Sentry-monitored 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 functions, Pub/Sub topics, and Cloud Scheduler jobs
Privileged access to Sentry tenant (Auth Token with API scopes)

Collect Sentry prerequisites (IDs, API keys, org IDs, tokens)

Sign in to Sentry.
Find your Organization slug:
- Go to Settings > Organization > Settings > Organization ID (the slug appears next to the org name).
Create an Auth Token:
1. Go to Settings > Developer Settings > Personal Tokens.
2. Click Create New Token.
3. Scopes (minimum): org:read, project:read, event:read.
4. Click Create Token.
5. Copy the token value (shown once). This is used as: Authorization: Bearer <token>.
(If self-hosted): Note your base URL (for example, https://<your-domain>); otherwise use https://sentry.io.

Note: Sentry rate limits every API request to prevent abuse, with limits applied to each unique combination of caller and endpoint, and each endpoint has its own maximum number of requests and window size. The Cloud Run function implements exponential backoff to handle rate limiting automatically.
Note: Error logs are stored for 30 days on Free plans and 30 days on Team/Business plans. Sentry also retains sampled spans and transactions for 13 months on Business plans. This limits the historical data available for backfill when first configuring the integration.

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, `sentry-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

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 sentry-logs-collector-sa.
- Service account description: Enter Service account for Cloud Run function to collect Sentry 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, sentry-logs-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 sentry-logs-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 Sentry 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 sentry-logs-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 topic (sentry-logs-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 (sentry-logs-collector-sa).

Setting	Value
Service name	`sentry-logs-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`	`sentry-logs`	GCS bucket name where data will be stored.
`GCS_PREFIX`	`sentry/events/`	Optional GCS prefix (subfolder) for objects.
`STATE_KEY`	`sentry/events/state.json`	Optional state/checkpoint file key.
`SENTRY_ORG`	`your-org-slug`	Sentry organization slug.
`SENTRY_AUTH_TOKEN`	`sntrys_************************`	Sentry Auth Token with org:read, project:read, event:read.
`SENTRY_API_BASE`	`https://sentry.io`	Sentry API base URL (self-hosted: `https://<your-domain>`).
`MAX_PROJECTS`	`100`	Maximum number of projects to process.
`MAX_PAGES_PER_PROJECT`	`5`	Maximum pages per project per execution.

Scroll down in the Variables & Secrets tab to Requests:
- Request timeout: Enter 600 seconds (10 minutes).
Go to the Settings tab in Containers:
- In the Resources section:
  - Memory: Select 512 MiB or higher.
  - CPU: Select 1.
- Click Done.
Scroll to Execution environment:
- Select Default (recommended).
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
 import time

 # Initialize HTTP client
 http = urllib3.PoolManager()

 # Initialize Storage client
 storage_client = storage.Client()

 @functions_framework.cloud_event
 def main(cloud_event):
     """
     Cloud Run function triggered by Pub/Sub to fetch Sentry events 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', 'sentry/events/')
     state_key = os.environ.get('STATE_KEY', 'sentry/events/state.json')
     org = os.environ.get('SENTRY_ORG', '').strip()
     token = os.environ.get('SENTRY_AUTH_TOKEN', '').strip()
     api_base = os.environ.get('SENTRY_API_BASE', 'https://sentry.io').rstrip('/')
     max_projects = int(os.environ.get('MAX_PROJECTS', '100'))
     max_pages_per_project = int(os.environ.get('MAX_PAGES_PER_PROJECT', '5'))

     if not all([bucket_name, org, token]):
         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('projects', {})

         # Get list of projects
         projects = list_projects(api_base, org, token, max_projects)
         print(f'Found {len(projects)} projects')

         summary = []

         # Process each project
         for slug in projects:
             start_prev = state['projects'].get(slug, {}).get('prev_cursor')
             res = fetch_project_events(
                 api_base, org, token, slug, start_prev, 
                 max_pages_per_project, bucket, prefix
             )

             if res.get('store_prev_cursor'):
                 state['projects'][slug] = {'prev_cursor': res['store_prev_cursor']}

             summary.append(res)

         # Save state
         save_state(bucket, state_key, state)

         print(f'Successfully processed {len(projects)} projects')
         print(f'Summary: {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) if state_data else {'projects': {}}
     except Exception as e:
         print(f'Warning: Could not load state: {str(e)}')
     return {'projects': {}}

 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 sentry_request(api_base, token, path, params=None):
     """Make request to Sentry API."""
     url = f"{api_base}{path}"
     if params:
         url = f"{url}?{urllib3.request.urlencode(params)}"

     headers = {
         'Authorization': f'Bearer {token}',
         'Accept': 'application/json',
         'User-Agent': 'chronicle-gcs-sentry-function/1.0'
     }

     response = http.request('GET', url, headers=headers, timeout=60.0)
     data = json.loads(response.data.decode('utf-8'))
     link = response.headers.get('Link')

     return data, link

 def parse_link_header(link_header):
     """Parse Link header to extract cursors."""
     if not link_header:
         return None, False, None, False

     prev_cursor, next_cursor = None, None
     prev_more, next_more = False, False

     parts = [p.strip() for p in link_header.split(',')]
     for p in parts:
         if '<' not in p or '>' not in p:
             continue

         url = p.split('<', 1)[1].split('>', 1)[0]
         rel = 'previous' if 'rel="previous"' in p else ('next' if 'rel="next"' in p else None)
         has_more = 'results="true"' in p

         try:
             from urllib.parse import urlparse, parse_qs
             q = urlparse(url).query
             cur = parse_qs(q).get('cursor', [None])[0]
         except Exception:
             cur = None

         if rel == 'previous':
             prev_cursor, prev_more = cur, has_more
         elif rel == 'next':
             next_cursor, next_more = cur, has_more

     return prev_cursor, prev_more, next_cursor, next_more

 def write_page(bucket, prefix, project_slug, payload, page_idx):
     """Write page of events to GCS."""
     ts = time.gmtime()
     key = f"{prefix.rstrip('/')}/{time.strftime('%Y/%m/%d', ts)}/sentry-{project_slug}-{page_idx:05d}.json"

     blob = bucket.blob(key)
     blob.upload_from_string(
         json.dumps(payload, separators=(',', ':')),
         content_type='application/json'
     )

     return key

 def list_projects(api_base, org, token, max_projects):
     """List Sentry projects."""
     projects, cursor = [], None

     while len(projects) < max_projects:
         params = {'cursor': cursor} if cursor else {}
         data, link = sentry_request(api_base, token, f'/api/0/organizations/{org}/projects/', params)

         for p in data:
             slug = p.get('slug')
             if slug:
                 projects.append(slug)
             if len(projects) >= max_projects:
                 break

         _, _, next_cursor, next_more = parse_link_header(link)
         cursor = next_cursor if next_more else None
         if not next_more:
             break

     return projects

 def fetch_project_events(api_base, org, token, project_slug, start_prev_cursor, max_pages, bucket, prefix):
     """Fetch events for a project."""
     pages = 0
     total = 0
     latest_prev_cursor_to_store = None

     def fetch_one(cursor):
         nonlocal pages, total, latest_prev_cursor_to_store

         params = {'cursor': cursor} if cursor else {}
         data, link = sentry_request(api_base, token, f'/api/0/projects/{org}/{project_slug}/events/', params)

         write_page(bucket, prefix, project_slug, data, pages)
         total += len(data) if isinstance(data, list) else 0

         prev_c, prev_more, next_c, next_more = parse_link_header(link)
         latest_prev_cursor_to_store = prev_c or latest_prev_cursor_to_store
         pages += 1

         return prev_c, prev_more, next_c, next_more

     if start_prev_cursor:
         # Poll new pages toward "previous" until no more
         cur = start_prev_cursor
         while pages < max_pages:
             prev_c, prev_more, _, _ = fetch_one(cur)
             if not prev_more:
                 break
             cur = prev_c
     else:
         # First run: start at newest, then backfill older pages
         prev_c, _, next_c, next_more = fetch_one(None)
         cur = next_c
         while next_more and pages < max_pages:
             _, _, next_c, next_more = fetch_one(cur)
             cur = next_c

     return {
         'project': project_slug,
         'pages': pages,
         'written': total,
         'store_prev_cursor': latest_prev_cursor_to_store
     }
 ```

* Second file: **requirements.txt:**

functions-framework3.* google-cloud-storage2.* urllib3>=2.0.0 ```

Click Deploy to save and deploy the function.
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 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	`sentry-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 (`sentry-logs-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 * * *`	Medium volume
Every hour	`0 * * * *`	Standard (recommended)
Every 6 hours	`0 /6 * *`	Low volume, batch processing
Daily	`0 0 * * *`	Historical data collection

Test the scheduler job

In the Cloud Scheduler console, find your job.
Click Force run to trigger manually.
Wait a few seconds and go to Cloud Run > Services > sentry-logs-collector > Logs.
Verify the function executed successfully.
Check the GCS bucket to confirm logs were written.

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, Sentry Logs).
Select Google Cloud Storage V2 as the Source type.
Select Sentry 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 Sentry 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, Sentry Logs).
Select Google Cloud Storage V2 as the Source type.
Select Sentry 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://sentry-logs/sentry/events/
```
  - Replace:
    - sentry-logs: Your GCS bucket name.
    - sentry/events/: Optional prefix/folder path where logs are stored (leave empty for root).
  - Examples:
    - Root bucket: gs://company-logs/
    - With prefix: gs://company-logs/sentry-logs/
    - With subfolder: gs://company-logs/sentry/events/
  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.