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    Collect PingOne Advanced Identity Cloud logs

    Supported in:

    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 Settingstab, 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 ).

    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.

    The Cloud Run function needs a service account with permissions to write to GCS bucket and be invoked by Pub/Sub.

    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 projectsection, 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 Permissionstab.
    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 Configuresection, 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 3.12or 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 Authenticationsection:

      1. Select Require authentication.
      2. Check Identity and Access Management (IAM).

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

    8. Go to the Securitytab:

      • Service account: Select the service account ( pingone-aic-collector-sa ).

    9. Go to the Containerstab:

      1. Click Variables & Secrets.
      2. Click + Add variablefor 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

    10. In the Variables & Secretssection, scroll to Requests:

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

    11. Go to the Settingstab:

      • In the Resourcessection:
        • Memory: Select 512 MiBor higher.
        • CPU: Select 1.

    12. In the Revision scalingsection:

      • 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 editoropens automatically.

    Add function code

    1. Enter mainin 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- 
 %d 
 T%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- 
 %d 
 T%H:%M:%SZ' 
 , 
 time 
 . 
 gmtime 
 ( 
 begin_epoch 
 ))
      • Second file: requirements.txt:
        functions 
 - 
 framework 
 == 
 3 
 .* 
 google 
 - 
 cloud 
 - 
 storage 
 == 
 2 
 .* 
 urllib3 
> = 
 2.0 
 . 
 0

    3. Click Deployto save and deploy the function.

    4. Wait for deployment to complete (2-3 minutes).

    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 Schedulerconsole, find your job ( pingone-aic-collector-hourly ).
    2. Click Force runto 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 Logstab.

    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

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

    1. Go to SIEM Settings > Feeds.
    2. Click Add New Feed.
    3. Click Configure a single feed.
    4. In the Feed namefield, enter a name for the feed (for example, PingOne Advanced Identity Cloud ).
    5. Select Google Cloud Storage V2as the Source type.
    6. Select PingOne Advanced Identity Cloudas the Log type.

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

        chronicle 
 - 
 12345678 
 @chronicle 
 - 
 gcp 
 - 
 prod 
 . 
 iam 
 . 
 gserviceaccount 
 . 
 com

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

    The Google SecOps service account needs Storage Object Viewerrole on your GCS bucket.

    1. Go to Cloud Storage > Buckets.
    2. Click your bucket name ( pingone-aic-logs ).
    3. Go to the Permissionstab.
    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.

    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 namefield, enter a name for the feed (for example, PingOne Advanced Identity Cloud ).
    5. Select Google Cloud Storage V2as the Source type.
    6. Select PingOne Advanced Identity Cloudas 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.

      • 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.

      • 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 Finalizescreen, and then click Submit.

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

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