Collect Sentry logs
Supported in:
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:
- Go to Settings > Developer Settings > Personal Tokens.
- Click Create New Token.
- Scopes (minimum):
org:read,project:read,event:read. - Click Create Token.
- Copy the token value (shown once). This is used as:
Authorization: Bearer <token>.
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(If self-hosted): Note your base URL (for example,
https://<your-domain>); otherwise usehttps://sentry.io.
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.
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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.
- Service account name: Enter
- Click Create and Continue.
- In the Grant this service account access to projectsection, add the following roles:
- Click Select a role.
- Search for and select Storage Object Admin.
- Click + Add another role.
- Search for and select Cloud Run Invoker.
- Click + Add another role.
- 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 Permissionstab.
- 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.
- Add principals: Enter the service account email (for example,
- 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.
- Topic ID: Enter
- 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).
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In the Configuresection, provide the following configuration details:
Setting Value Service name sentry-logs-collectorRegion Select region matching your GCS bucket (for example, us-central1)Runtime Select Python 3.12or later -
In the Trigger (optional)section:
- Click + Add trigger.
- Select Cloud Pub/Sub.
- In Select a Cloud Pub/Sub topic, choose the topic (
sentry-logs-trigger). - Click Save.
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In the Authenticationsection:
- Select Require authentication.
- Check Identity and Access Management (IAM).
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Scroll down and expand Containers, Networking, Security.
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Go to the Securitytab:
- Service account: Select the service account (
sentry-logs-collector-sa).
- Service account: Select the service account (
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Go to the Containerstab:
- Click Variables & Secrets.
- Click + Add variablefor each environment variable:
Variable Name Example Value Description GCS_BUCKETsentry-logsGCS bucket name where data will be stored. GCS_PREFIXsentry/events/Optional GCS prefix (subfolder) for objects. STATE_KEYsentry/events/state.jsonOptional state/checkpoint file key. SENTRY_ORGyour-org-slugSentry organization slug. SENTRY_AUTH_TOKENsntrys_************************Sentry Auth Token with org:read, project:read, event:read. SENTRY_API_BASEhttps://sentry.ioSentry API base URL (self-hosted: https://<your-domain>).MAX_PROJECTS100Maximum number of projects to process. MAX_PAGES_PER_PROJECT5Maximum pages per project per execution. -
Scroll down in the Variables & Secretstab to Requests:
- Request timeout: Enter
600seconds (10 minutes).
- Request timeout: Enter
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Go to the Settingstab in Containers:
- In the Resourcessection:
- Memory: Select 512 MiBor higher.
- CPU: Select 1.
- Click Done.
- In the Resourcessection:
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Scroll to Execution environment:
- Select Default(recommended).
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In the Revision scalingsection:
- Minimum number of instances: Enter
0. - Maximum number of instances: Enter
100(or adjust based on expected load).
- Minimum number of instances: Enter
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Click Create.
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Wait for the service to be created (1-2 minutes).
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After the service is created, the inline code editoropens automatically.
Add function code
- Enter mainin Function entry point
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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-framework 3.* google-cloud-storage 2.* urllib3>=2.0.0 ```
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Click Deployto save and deploy the function.
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Wait for deployment to complete (2-3 minutes).
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.
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Provide the following configuration details:
Setting Value Name sentry-logs-collector-hourlyRegion 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
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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 hour0 * * * *Standard (recommended) Every 6 hours0 */6 * * *Low volume, batch processing Daily0 0 * * *Historical data collection
Test the scheduler job
- In the Cloud Schedulerconsole, find your job.
- Click Force runto 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 namefield, enter a name for the feed (for example,
Sentry Logs). - Select Google Cloud Storage V2as the Source type.
- Select Sentryas the Log type.
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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.
Grant IAM permissions to the Google SecOps service account
The Google SecOps service account needs Storage Object Viewerrole on your GCS bucket.
- Go to Cloud Storage > Buckets.
- Click your bucket name.
- Go to the Permissionstab.
- Click Grant access.
- Provide the following configuration details:
- Add principals: Paste the Google SecOps service account email.
- Assign roles: Select Storage Object Viewer.
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Click Save.
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 namefield, enter a name for the feed (for example,
Sentry Logs). - Select Google Cloud Storage V2as the Source type.
- Select Sentryas the Log type.
- Click Next.
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Specify values for the following input parameters:
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Storage bucket URL: Enter the GCS bucket URI with the prefix path:
gs://sentry-logs/sentry/events/-
Replace:
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sentry-logs: Your GCS bucket name. -
sentry/events/: Optional prefix/folder path where logs are stored (leave empty for root).
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Examples:
- Root bucket:
gs://company-logs/ - With prefix:
gs://company-logs/sentry-logs/ - With subfolder:
gs://company-logs/sentry/events/
- Root bucket:
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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.
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Delete transferred files and empty directories: Deletes files and empty directories after successful transfer.
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Maximum File Age: Include files modified in the last number of days. Default is 180 days.
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Asset namespace: The asset namespace .
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Ingestion labels: The label to be applied to the events from this feed.
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Click Next.
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Review your new feed configuration in the Finalizescreen, and then click Submit.
Need more help? Get answers from Community members and Google SecOps professionals.
