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    Collect Citrix Analytics logs

    Supported in:

    This document explains how to ingest Citrix Analytics logs to Google Security Operations using Google Cloud Storage. Citrix Analytics for Performance (Cloud Software Group) provides aggregated performance data from Citrix Virtual Apps and Desktops environments, enabling you to fetch session, machine, and user data through the OData API. Citrix Analytics for Security provides risk insights and data source events that can be exported through Kafka-based SIEM integration.

    Before you begin

    Make sure 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 create Cloud Run services, Pub/Sub topics, and Cloud Scheduler jobs
    • Privileged access to a Citrix Analytics for Performance tenant
    • Citrix Cloud API credentials (Client ID, Client Secret, Customer ID)

    Collect Citrix Analytics API credentials

    Get Citrix Cloud API credentials

    1. Sign in to the Citrix Cloud Console .
    2. Click the menu icon in the upper left corner of the screen.
    3. Select Identity and Access Managementfrom the menu.
    4. Select the API Accesstab.
    5. Click Create Client.
    6. Copy and save the following details in a secure location:
      • Client ID
      • Client Secret
      • Customer ID(located in the Citrix Cloud URL or the IAM page)

    Determine API base URL

    The OData API base URL depends on your Citrix Cloud region:

    Region API Base URL
    United States https://api.cloud.com/casodata
    European Union https://api.eu.cloud.com/casodata
    Asia Pacific South https://api.ap-s.cloud.com/casodata

    Verify permissions

    To verify the account has the required permissions:

    1. Sign in to Citrix Cloud .
    2. Go to Identity and Access Management > Administrators.
    3. Verify that the account used to create API credentials has Full accessor Custom accesswith Citrix Analytics for Performance permissions enabled.
    4. If you cannot see the required permissions, contact your Citrix Cloud administrator to grant access.

    Test API access

    • Test your credentials before proceeding with the integration:

        CITRIX_CUSTOMER_ID 
 = 
 "your-customer-id" 
 CITRIX_CLIENT_ID 
 = 
 "your-client-id" 
 CITRIX_CLIENT_SECRET 
 = 
 "your-client-secret" 
 # Get bearer token 
 TOKEN 
 = 
 $( 
curl  
-s  
-X  
POST  
 \ 
  
 "https://api.cloud.com/cctrustoauth2/ 
 ${ 
 CITRIX_CUSTOMER_ID 
 } 
 /tokens/clients" 
  
 \ 
  
-H  
 "Content-Type: application/x-www-form-urlencoded" 
  
 \ 
  
-d  
 "grant_type=client_credentials&client_id= 
 ${ 
 CITRIX_CLIENT_ID 
 } 
& client_secret= 
 ${ 
 CITRIX_CLIENT_SECRET 
 } 
 " 
  
 \ 
  
 | 
  
python3  
-c  
 "import sys,json; print(json.load(sys.stdin)['access_token'])" 
 ) 
 # Test OData API access 
curl  
-v  
-H  
 "Authorization: CwsAuth bearer= 
 ${ 
 TOKEN 
 } 
 " 
  
 \ 
  
-H  
 "Citrix-CustomerId: 
 ${ 
 CITRIX_CUSTOMER_ID 
 } 
 " 
  
 \ 
  
-H  
 "Accept: application/json" 
  
 \ 
  
 "https://api.cloud.com/casodata/sessions?\$top=1"

    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, citrix-analytics-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 citrix-analytics-collector-sa
      • Service account description: Enter Service account for Cloud Run function to collect Citrix Analytics 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, citrix-analytics-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 citrix-analytics-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 logs from the Citrix Analytics OData 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 Configuresection, provide the following configuration details:

      Setting Value
      Service name citrix-analytics-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 topic citrix-analytics-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 citrix-analytics-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
      		citrix-analytics-logs GCS bucket name
      GCS_PREFIX
      		citrix_analytics Prefix for log files
      STATE_KEY
      		citrix_analytics/state.json State file path
      CITRIX_CLIENT_ID
      		your-client-id Citrix Cloud Client ID
      CITRIX_CLIENT_SECRET
      		your-client-secret Citrix Cloud Client Secret
      CITRIX_CUSTOMER_ID
      		your-customer-id Citrix Cloud Customer ID
      API_BASE
      		https://api.cloud.com/casodata OData API base URL
      ENTITIES
      		sessions,machines,users Entity types to collect
      TOP_N
      		1000 Records per page
      LOOKBACK_MINUTES
      		75 Initial lookback period

    10. Scroll down in the Variables & Secretssection 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 editorwill open automatically.

    Add function code

    1. Enter mainin the Entry pointfield.

    2. In the inline code editor, create two files:

      • main.py:

          import 
  
 functions_framework 
 from 
  
 google.cloud 
  
 import 
  storage 
 
 import 
  
 json 
 import 
  
 os 
 import 
  
 urllib3 
 from 
  
 datetime 
  
 import 
 datetime 
 , 
 timedelta 
 , 
 timezone 
 import 
  
 urllib.parse 
 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 
 
 () 
 CITRIX_TOKEN_URL_TMPL 
 = 
 "https://api.cloud.com/cctrustoauth2/ 
 {customerid} 
 /tokens/clients" 
 DEFAULT_API_BASE 
 = 
 "https://api.cloud.com/casodata" 
 @functions_framework 
 . 
 cloud_event 
 def 
  
 main 
 ( 
 cloud_event 
 ): 
  
 """ 
 Cloud Run function triggered by Pub/Sub to fetch logs 
 from Citrix Analytics OData 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' 
 , 
 'citrix_analytics' 
 ) 
 . 
 strip 
 ( 
 '/' 
 ) 
 state_key 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'STATE_KEY' 
 ) 
 or 
 f 
 " 
 { 
 prefix 
 } 
 /state.json" 
 customer_id 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'CITRIX_CUSTOMER_ID' 
 ) 
 client_id 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'CITRIX_CLIENT_ID' 
 ) 
 client_secret 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'CITRIX_CLIENT_SECRET' 
 ) 
 api_base 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'API_BASE' 
 , 
 DEFAULT_API_BASE 
 ) 
 entities 
 = 
 [ 
 e 
 . 
 strip 
 () 
 for 
 e 
 in 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'ENTITIES' 
 , 
 'sessions,machines,users' 
 ) 
 . 
 split 
 ( 
 ',' 
 ) 
 if 
 e 
 . 
 strip 
 ()] 
 top_n 
 = 
 int 
 ( 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'TOP_N' 
 , 
 '1000' 
 )) 
 lookback_minutes 
 = 
 int 
 ( 
 os 
 . 
 environ 
 . 
 get 
 ( 
 'LOOKBACK_MINUTES' 
 , 
 '75' 
 )) 
 if 
 not 
 all 
 ([ 
 bucket_name 
 , 
 customer_id 
 , 
 client_id 
 , 
 client_secret 
 ]): 
 print 
 ( 
 'Error: Missing required environment variables' 
 ) 
 return 
 try 
 : 
 # Get GCS bucket 
 bucket 
 = 
 storage_client 
 . 
  bucket 
 
 ( 
 bucket_name 
 ) 
 # Determine target hour to collect 
 now 
 = 
 datetime 
 . 
 now 
 ( 
 timezone 
 . 
 utc 
 ) 
 fallback_target 
 = 
 ( 
 now 
 - 
 timedelta 
 ( 
 minutes 
 = 
 lookback_minutes 
 )) 
 . 
 replace 
 ( 
 minute 
 = 
 0 
 , 
 second 
 = 
 0 
 , 
 microsecond 
 = 
 0 
 ) 
 # Load state (last processed timestamp) 
 state 
 = 
 load_state 
 ( 
 bucket 
 , 
 state_key 
 ) 
 last_processed_str 
 = 
  state 
 
 . 
 get 
 ( 
 'last_hour_utc' 
 ) 
 if 
 last_processed_str 
 : 
 last_processed 
 = 
 datetime 
 . 
 fromisoformat 
 ( 
 last_processed_str 
 . 
 replace 
 ( 
 'Z' 
 , 
 '+00:00' 
 )) 
 . 
 replace 
 ( 
 tzinfo 
 = 
 None 
 ) 
 target_hour 
 = 
 last_processed 
 + 
 timedelta 
 ( 
 hours 
 = 
 1 
 ) 
 else 
 : 
 target_hour 
 = 
 fallback_target 
 print 
 ( 
 f 
 'Processing logs for hour: 
 { 
 target_hour 
 . 
 isoformat 
 () 
 } 
 Z' 
 ) 
 # Get authentication token 
 token 
 = 
 get_citrix_token 
 ( 
 customer_id 
 , 
 client_id 
 , 
 client_secret 
 ) 
 headers 
 = 
 { 
 'Authorization' 
 : 
 f 
 'CwsAuth bearer= 
 { 
 token 
 } 
 ' 
 , 
 'Citrix-CustomerId' 
 : 
 customer_id 
 , 
 'Accept' 
 : 
 'application/json' 
 , 
 'Content-Type' 
 : 
 'application/json' 
 , 
 } 
 total_records 
 = 
 0 
 # Process each entity type 
 for 
 entity 
 in 
 entities 
 : 
 records 
 = 
 [] 
 for 
 row 
 in 
 fetch_odata_entity 
 ( 
 entity 
 , 
 target_hour 
 , 
 top_n 
 , 
 headers 
 , 
 api_base 
 ): 
 enriched_record 
 = 
 { 
 'citrix_entity' 
 : 
 entity 
 , 
 'citrix_hour_utc' 
 : 
 target_hour 
 . 
 isoformat 
 () 
 + 
 'Z' 
 , 
 'collection_timestamp' 
 : 
 datetime 
 . 
 now 
 ( 
 timezone 
 . 
 utc 
 ) 
 . 
 isoformat 
 () 
 + 
 'Z' 
 , 
 'raw' 
 : 
 row 
 } 
 records 
 . 
 append 
 ( 
 enriched_record 
 ) 
 # Write in batches to avoid memory issues 
 if 
 len 
 ( 
 records 
 ) 
> = 
 1000 
 : 
 blob_name 
 = 
 f 
 " 
 { 
 prefix 
 } 
 / 
 { 
  entity 
 
 } 
 /year= 
 { 
 target_hour 
 . 
 year 
 : 
 04d 
 } 
 /month= 
 { 
 target_hour 
 . 
 month 
 : 
 02d 
 } 
 /day= 
 { 
 target_hour 
 . 
 day 
 : 
 02d 
 } 
 /hour= 
 { 
 target_hour 
 . 
 hour 
 : 
 02d 
 } 
 /part- 
 { 
 datetime 
 . 
 now 
 ( 
 timezone 
 . 
 utc 
 ) 
 . 
 strftime 
 ( 
 '%Y%m 
 %d 
 %H%M%S 
 %f 
 ' 
 ) 
 } 
 .ndjson" 
 write_ndjson_to_gcs 
 ( 
 bucket 
 , 
 blob_name 
 , 
 records 
 ) 
 total_records 
 += 
 len 
 ( 
 records 
 ) 
 records 
 = 
 [] 
 # Write remaining records 
 if 
 records 
 : 
 blob_name 
 = 
 f 
 " 
 { 
 prefix 
 } 
 / 
 { 
  entity 
 
 } 
 /year= 
 { 
 target_hour 
 . 
 year 
 : 
 04d 
 } 
 /month= 
 { 
 target_hour 
 . 
 month 
 : 
 02d 
 } 
 /day= 
 { 
 target_hour 
 . 
 day 
 : 
 02d 
 } 
 /hour= 
 { 
 target_hour 
 . 
 hour 
 : 
 02d 
 } 
 /part- 
 { 
 datetime 
 . 
 now 
 ( 
 timezone 
 . 
 utc 
 ) 
 . 
 strftime 
 ( 
 '%Y%m 
 %d 
 %H%M%S 
 %f 
 ' 
 ) 
 } 
 .ndjson" 
 write_ndjson_to_gcs 
 ( 
 bucket 
 , 
 blob_name 
 , 
 records 
 ) 
 total_records 
 += 
 len 
 ( 
 records 
 ) 
 # Update state file 
 save_state 
 ( 
 bucket 
 , 
 state_key 
 , 
 { 
 'last_hour_utc' 
 : 
 target_hour 
 . 
 isoformat 
 () 
 + 
 'Z' 
 }) 
 print 
 ( 
 f 
 'Successfully processed 
 { 
 total_records 
 } 
 records for hour 
 { 
 target_hour 
 . 
 isoformat 
 () 
 } 
 Z' 
 ) 
 except 
 Exception 
 as 
 e 
 : 
 print 
 ( 
 f 
 'Error processing logs: 
 { 
 str 
 ( 
 e 
 ) 
 } 
 ' 
 ) 
 raise 
 def 
  
 get_citrix_token 
 ( 
 customer_id 
 , 
 client_id 
 , 
 client_secret 
 ): 
  
 """Get Citrix Cloud authentication token.""" 
 url 
 = 
 CITRIX_TOKEN_URL_TMPL 
 . 
 format 
 ( 
 customerid 
 = 
 customer_id 
 ) 
 payload 
 = 
 { 
 'grant_type' 
 : 
 'client_credentials' 
 , 
 'client_id' 
 : 
 client_id 
 , 
 'client_secret' 
 : 
 client_secret 
 , 
 } 
 data 
 = 
 urllib 
 . 
 parse 
 . 
 urlencode 
 ( 
 payload 
 ) 
 . 
 encode 
 ( 
 'utf-8' 
 ) 
 response 
 = 
 http 
 . 
 request 
 ( 
 'POST' 
 , 
 url 
 , 
 body 
 = 
 data 
 , 
 headers 
 = 
 { 
 'Accept' 
 : 
 'application/json' 
 , 
 'Content-Type' 
 : 
 'application/x-www-form-urlencoded' 
 , 
 } 
 ) 
 if 
 response 
 . 
 status 
 != 
 200 
 : 
 print 
 ( 
 f 
 'Token request failed with status 
 { 
 response 
 . 
 status 
 } 
 ' 
 ) 
 print 
 ( 
 f 
 'Response: 
 { 
 response 
 . 
 data 
 . 
 decode 
 ( 
 "utf-8" 
 ) 
 } 
 ' 
 ) 
 raise 
 Exception 
 ( 
 f 
 'Failed to get Citrix token: HTTP 
 { 
 response 
 . 
 status 
 } 
 ' 
 ) 
 token_response 
 = 
 json 
 . 
 loads 
 ( 
 response 
 . 
 data 
 . 
 decode 
 ( 
 'utf-8' 
 )) 
 return 
 token_response 
 [ 
 'access_token' 
 ] 
 def 
  
 fetch_odata_entity 
 ( 
 entity 
 , 
 when_utc 
 , 
 top 
 , 
 headers 
 , 
 api_base 
 ): 
  
 """Fetch data from Citrix Analytics OData API with pagination and rate limiting.""" 
 year 
 = 
 when_utc 
 . 
 year 
 month 
 = 
 when_utc 
 . 
 month 
 day 
 = 
 when_utc 
 . 
 day 
 hour 
 = 
 when_utc 
 . 
 hour 
 base_url 
 = 
 f 
 " 
 { 
 api_base 
 . 
 rstrip 
 ( 
 '/' 
 ) 
 } 
 / 
 { 
  entity 
 
 } 
 ?year= 
 { 
 year 
 : 
 04d 
 } 
& month= 
 { 
 month 
 : 
 02d 
 } 
& day= 
 { 
 day 
 : 
 02d 
 } 
& hour= 
 { 
 hour 
 : 
 02d 
 } 
 " 
 skip 
 = 
 0 
 backoff 
 = 
 1.0 
 while 
 True 
 : 
 url 
 = 
 f 
 " 
 { 
 base_url 
 } 
& $top= 
 { 
 top 
 } 
& $skip= 
 { 
 skip 
 } 
 " 
 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 
 data 
 = 
 json 
 . 
 loads 
 ( 
 response 
 . 
 data 
 . 
 decode 
 ( 
 'utf-8' 
 )) 
 items 
 = 
 data 
 . 
 get 
 ( 
 'value' 
 , 
 []) 
 if 
 not 
 items 
 : 
 break 
 for 
 item 
 in 
 items 
 : 
 yield 
 item 
 if 
 len 
 ( 
 items 
 ) 
< top 
 : 
 break 
 skip 
 += 
 top 
 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 
 {} 
 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 
  
 write_ndjson_to_gcs 
 ( 
 bucket 
 , 
 key 
 , 
 records 
 ): 
  
 """Write records as NDJSON to GCS.""" 
 body_lines 
 = 
 [] 
 for 
 record 
 in 
 records 
 : 
 json_line 
 = 
 json 
 . 
 dumps 
 ( 
 record 
 , 
 separators 
 = 
 ( 
 ',' 
 , 
 ':' 
 ), 
 ensure_ascii 
 = 
 False 
 ) 
 body_lines 
 . 
 append 
 ( 
 json_line 
 ) 
 body 
 = 
 ( 
 ' 
 \n 
 ' 
 . 
 join 
 ( 
 body_lines 
 ) 
 + 
 ' 
 \n 
 ' 
 ) 
 . 
 encode 
 ( 
 'utf-8' 
 ) 
 blob 
 = 
 bucket 
 . 
 blob 
 ( 
 key 
 ) 
 blob 
 . 
  upload_from_string 
 
 ( 
 body 
 , 
 content_type 
 = 
 'application/x-ndjson' 
 )

      • 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 citrix-analytics-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 citrix-analytics-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 hour
    		 0 * * * * Standard (recommended)
    Every 2 hours
    		 0 */2 * * * Lower volume
    Every 6 hours
    		 0 */6 * * * Low volume, batch processing

    Test the integration

    1. In the Cloud Schedulerconsole, find your job.
    2. Click Force runto trigger the job manually.
    3. Wait a few seconds.
    4. Go to Cloud Run > Services.
    5. Click on the function name citrix-analytics-collector .
    6. Click the Logstab.

    7. Verify the function executed successfully. Look for:

       Processing logs for hour: YYYY-MM-DDTHH:00:00Z
Successfully processed X records for hour YYYY-MM-DDTHH:00:00Z

    8. Go to Cloud Storage > Buckets.

    9. Click your bucket name.

    10. Navigate to the prefix folder citrix_analytics/ .

    11. Verify that new .ndjson files were 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 in Citrix Cloud
    • HTTP 429: Rate limiting - function will automatically retry with backoff
    • Missing environment variables: Check all required variables are set

    Configure a feed in Google SecOps to ingest Citrix Analytics 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, Citrix Analytics logs ).
    5. Select Google Cloud Storage V2as the Source type.
    6. Select Citrix Analyticsas the Log type.

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

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

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

    9. Click Next.

    10. Specify values for the following input parameters:

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

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

      • 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

    11. Click Next.

    12. Review your new feed configuration in the Finalizescreen, and then click Submit.

    The Google SecOps service account needs Storage Object Viewerrole on your 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: Paste the Google SecOps service account email
      • Assign roles: Select Storage Object Viewer

    6. Click Save.

    UDM mapping table

    Log Field UDM Mapping Logic
    occurrence_event_type
    		extensions.auth.type Mapped: Session.Logon → AUTHTYPE_UNSPECIFIED , Session.End → AUTHTYPE_UNSPECIFIED
    server_name
    		intermediary.asset.hostname Directly mapped
    server_name
    		intermediary.hostname Directly mapped
    event_type
    		metadata.description Directly mapped
    timestamp
    		metadata.event_timestamp Parsed as ISO8601
    udm_event_type
    		metadata.event_type Mapped: "USER_LOGIN", "USER_LOGOUT" → GENERIC_EVENT
    tenant_id
    		metadata.product_deployment_id Directly mapped
    occurrence_event_type
    		metadata.product_event_type Directly mapped
    event_id
    		metadata.product_log_id Directly mapped
    product
    		metadata.product_name Directly mapped
    product_version
    		metadata.product_version Directly mapped
    ui_link
    		metadata.url_back_to_product Directly mapped
    session_key
    		network.session_id Directly mapped
    domain
    		principal.administrative_domain Directly mapped
    device_id
    		principal.asset.hostname Directly mapped
    client_ip
    		principal.asset.ip Merged
    vulnerability
    		principal.asset.vulnerabilities Merged
    device_id
    		principal.hostname Directly mapped
    client_ip
    		principal.ip Merged
    os_name
    		principal.platform Mapped values (6 total, e.g. (?i)windows → WINDOWS , (?i)windows → MAC , (?i)windows ...
    os_extra_info
    		principal.platform_patch_level Directly mapped
    os_version
    		principal.platform_version Directly mapped
    entity_id
    		principal.user.email_addresses Mapped: ^.+@.+$ → entity_id
    entity_type
    		principal.user.email_addresses Mapped: user → entity_id
    session_user_name
    		principal.user.user_display_name Directly mapped
    entity_id
    		principal.user.userid Directly mapped
    session_user_name
    		principal.user.userid Directly mapped
    alert_message
    		security_result.action_details Directly mapped
    analytic
    		security_result.analytics_metadata Merged
    category
    		security_result.category Merged
    indicator_category
    		security_result.category Mapped: Data exfiltration → category
    indicator_name
    		security_result.description Directly mapped
    label
    		security_result.detection_fields Merged
    label
    		security_result.outcomes Merged
    severity
    		security_result.severity Directly mapped
    app_name
    		target.application Directly mapped
    app_name
    		target.process.file.names Merged
    printer_name
    		target.resource.name Directly mapped
    entity_id
    		target.user.email_addresses Mapped: ^.+@.+$ → entity_id
    entity_type
    		target.user.email_addresses Mapped: user → entity_id
    session_user_name
    		target.user.user_display_name Directly mapped
    entity_id
    		target.user.userid Directly mapped
    session_user_name
    		target.user.userid Directly mapped
    N/A
    		 extensions.auth.type Constant: AUTHTYPE_UNSPECIFIED
    N/A
    		 metadata.event_type Constant: GENERIC_EVENT
    N/A
    		 metadata.vendor_name Constant: CITRIX_ANALYTICS
    N/A
    		 principal.platform Constant: WINDOWS
    N/A
    		 security_result.confidence_score Constant: risk_probability
    N/A
    		 security_result.risk_score Constant: cur_riskscore

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

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