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    Collect Jamf Pro context logs

    Supported in:

    This document explains how to ingest Jamf Pro context logs (device & user context) to Google Security Operations using Google Cloud Storage with Cloud Run functions, Pub/Sub, and Cloud Scheduler. Jamf Pro is a comprehensive management solution for Apple devices, providing device inventory, user context, and configuration management capabilities.

    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 Jamf Pro tenant

    Configure Jamf API Role

    1. Sign in to Jamf web UI.
    2. Go to Settings > System section > API Roles and Clients.
    3. Select the API Rolestab.
    4. Click New.
    5. Enter a display name for the API role (for example, context_role ).

    6. In the Jamf Pro API role privileges, type the name of a privilege, and then select it from the menu:

      • Computer Inventory
      • Mobile Device Inventory

    7. Click Save.

    Configure Jamf API Client

    1. In Jamf Pro, go to Settings > System section > API roles and clients.
    2. Select the API Clientstab.
    3. Click New.
    4. Enter a display name for the API client (for example, context_client ).
    5. In the API Rolesfield, add the context_role role you previously created.
    6. Under Access Token Lifetime, enter the time in seconds for the access tokens to be valid.
    7. Click Save.
    8. Click Edit.
    9. Click Enable API Client.
    10. Click Save.

    Configure Jamf Client Secret

    1. In Jamf Pro, go to the newly created API client.
    2. Click Generate Client Secret.
    3. In a confirmation screen, click Create Secret.
    4. Save the following parameters in a secure location:
      • Base URL: https://<your>.jamfcloud.com
      • Client ID: UUID.
      • Client Secret: Value is shown once.

    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, jamfpro )
      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 jamf-pro-collector-sa .
      • Service account description: Enter Service account for Cloud Run function to collect Jamf Pro context 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, jamf-pro-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 jamf-pro-context-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 Jamf Pro 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 jamf-pro-context-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 ( jamf-pro-context-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 ( jamf-pro-collector-sa ).

    9. Go to the Containerstab:

      1. Click Variables & Secrets.
      2. Click + Add variablefor each environment variable:
      Variable Name Example Value
      GCS_BUCKET jamfpro
      GCS_PREFIX jamf-pro/context/
      JAMF_CLIENT_ID Enter Jamf Client ID
      JAMF_CLIENT_SECRET Enter Jamf Client Secret
      JAMF_BASE_URL Enter Jamf URL, replace <your> in https://<your>.jamfcloud.com
      PAGE_SIZE 200

    10. Scroll down in the Variables & Secretstab to Requests:

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

    11. Go to the Settingstab in Containers:

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

    12. Scroll down to Execution environment:

      • Select Default(recommended).

    13. In the Revision scalingsection:

      • Minimum number of instances: Enter 0 .
      • Maximum number of instances: Enter 100 (or adjust based on expected load).

    14. Click Create.

    15. Wait for the service to be created (1-2 minutes).

    16. 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 
  
 gzip 
 import 
  
 io 
 import 
  
 time 
 # Initialize HTTP client 
 http 
 = 
 urllib3 
 . 
 PoolManager 
 () 
 # Initialize Storage client 
 storage_client 
 = 
  storage 
 
 . 
  Client 
 
 () 
 # Configuration 
 BASE_URL 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 "JAMF_BASE_URL" 
 , 
 "" 
 ) 
 . 
 rstrip 
 ( 
 "/" 
 ) 
 CLIENT_ID 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 "JAMF_CLIENT_ID" 
 ) 
 CLIENT_SECRET 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 "JAMF_CLIENT_SECRET" 
 ) 
 GCS_BUCKET 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 "GCS_BUCKET" 
 ) 
 GCS_PREFIX 
 = 
 os 
 . 
 environ 
 . 
 get 
 ( 
 "GCS_PREFIX" 
 , 
 "jamf-pro/context/" 
 ) 
 PAGE_SIZE 
 = 
 int 
 ( 
 os 
 . 
 environ 
 . 
 get 
 ( 
 "PAGE_SIZE" 
 , 
 "200" 
 )) 
 SECTIONS 
 = 
 [ 
 "GENERAL" 
 , 
 "HARDWARE" 
 , 
 "OPERATING_SYSTEM" 
 , 
 "USER_AND_LOCATION" 
 , 
 "DISK_ENCRYPTION" 
 , 
 "SECURITY" 
 , 
 "EXTENSION_ATTRIBUTES" 
 , 
 "APPLICATIONS" 
 , 
 "CONFIGURATION_PROFILES" 
 , 
 "LOCAL_USER_ACCOUNTS" 
 , 
 "CERTIFICATES" 
 , 
 "SERVICES" 
 , 
 "PRINTERS" 
 , 
 "SOFTWARE_UPDATES" 
 , 
 "GROUP_MEMBERSHIPS" 
 , 
 "CONTENT_CACHING" 
 , 
 "STORAGE" 
 , 
 "FONTS" 
 , 
 "PACKAGE_RECEIPTS" 
 , 
 "PLUGINS" 
 , 
 "ATTACHMENTS" 
 , 
 "LICENSED_SOFTWARE" 
 , 
 "IBEACONS" 
 , 
 "PURCHASING" 
 ] 
 def 
  
 _now_iso 
 (): 
 return 
 datetime 
 . 
 now 
 ( 
 timezone 
 . 
 utc 
 ) 
 . 
 isoformat 
 () 
 def 
  
 get_token 
 (): 
  
 """OAuth2 client credentials > access_token""" 
 url 
 = 
 f 
 " 
 { 
 BASE_URL 
 } 
 /api/oauth/token" 
 # Encode credentials for form data 
 fields 
 = 
 { 
 "grant_type" 
 : 
 "client_credentials" 
 , 
 "client_id" 
 : 
 CLIENT_ID 
 , 
 "client_secret" 
 : 
 CLIENT_SECRET 
 } 
 headers 
 = 
 { 
 "Content-Type" 
 : 
 "application/x-www-form-urlencoded" 
 } 
 response 
 = 
 http 
 . 
 request 
 ( 
 'POST' 
 , 
 url 
 , 
 fields 
 = 
 fields 
 , 
 headers 
 = 
 headers 
 , 
 timeout 
 = 
 30.0 
 ) 
 if 
 response 
 . 
 status 
 != 
 200 
 : 
 raise 
 Exception 
 ( 
 f 
 "Failed to get token: 
 { 
 response 
 . 
 status 
 } 
  
 { 
 response 
 . 
 data 
 . 
 decode 
 ( 
 'utf-8' 
 ) 
 } 
 " 
 ) 
 data 
 = 
 json 
 . 
 loads 
 ( 
 response 
 . 
 data 
 . 
 decode 
 ( 
 'utf-8' 
 )) 
 return 
 data 
 [ 
 "access_token" 
 ], 
 int 
 ( 
 data 
 . 
 get 
 ( 
 "expires_in" 
 , 
 1200 
 )) 
 def 
  
 fetch_page 
 ( 
 token 
 , 
 page 
 ): 
  
 """GET /api/v1/computers-inventory with sections & pagination""" 
 url 
 = 
 f 
 " 
 { 
 BASE_URL 
 } 
 /api/v1/computers-inventory" 
 # Build query parameters 
 params 
 = 
 [( 
 "page" 
 , 
 str 
 ( 
 page 
 )), 
 ( 
 "page-size" 
 , 
 str 
 ( 
 PAGE_SIZE 
 ))] 
 params 
 . 
 extend 
 ([( 
 "section" 
 , 
 s 
 ) 
 for 
 s 
 in 
 SECTIONS 
 ]) 
 # Encode parameters 
 query_string 
 = 
 "&" 
 . 
 join 
 ([ 
 f 
 " 
 { 
 k 
 } 
 = 
 { 
 v 
 } 
 " 
 for 
 k 
 , 
 v 
 in 
 params 
 ]) 
 full_url 
 = 
 f 
 " 
 { 
 url 
 } 
 ? 
 { 
 query_string 
 } 
 " 
 headers 
 = 
 { 
 "Authorization" 
 : 
 f 
 "Bearer 
 { 
 token 
 } 
 " 
 , 
 "Accept" 
 : 
 "application/json" 
 } 
 response 
 = 
 http 
 . 
 request 
 ( 
 'GET' 
 , 
 full_url 
 , 
 headers 
 = 
 headers 
 , 
 timeout 
 = 
 60.0 
 ) 
 if 
 response 
 . 
 status 
 != 
 200 
 : 
 raise 
 Exception 
 ( 
 f 
 "Failed to fetch page 
 { 
 page 
 } 
 : 
 { 
 response 
 . 
 status 
 } 
  
 { 
 response 
 . 
 data 
 . 
 decode 
 ( 
 'utf-8' 
 ) 
 } 
 " 
 ) 
 return 
 json 
 . 
 loads 
 ( 
 response 
 . 
 data 
 . 
 decode 
 ( 
 'utf-8' 
 )) 
 def 
  
 to_context_event 
 ( 
 item 
 ): 
 inv 
 = 
 item 
 . 
 get 
 ( 
 "inventory" 
 , 
 {}) 
 or 
 {} 
 general 
 = 
 inv 
 . 
 get 
 ( 
 "general" 
 , 
 {}) 
 or 
 {} 
 hardware 
 = 
 inv 
 . 
 get 
 ( 
 "hardware" 
 , 
 {}) 
 or 
 {} 
 osinfo 
 = 
 inv 
 . 
 get 
 ( 
 "operatingSystem" 
 , 
 {}) 
 or 
 {} 
 loc 
 = 
 inv 
 . 
 get 
 ( 
 "location" 
 , 
 {}) 
 or 
 inv 
 . 
 get 
 ( 
 "userAndLocation" 
 , 
 {}) 
 or 
 {} 
 computer 
 = 
 { 
 "udid" 
 : 
 general 
 . 
 get 
 ( 
 "udid" 
 ) 
 or 
 hardware 
 . 
 get 
 ( 
 "udid" 
 ), 
 "deviceName" 
 : 
 general 
 . 
 get 
 ( 
 "name" 
 ) 
 or 
 general 
 . 
 get 
 ( 
 "deviceName" 
 ), 
 "serialNumber" 
 : 
 hardware 
 . 
 get 
 ( 
 "serialNumber" 
 ) 
 or 
 general 
 . 
 get 
 ( 
 "serialNumber" 
 ), 
 "model" 
 : 
 hardware 
 . 
 get 
 ( 
 "model" 
 ) 
 or 
 general 
 . 
 get 
 ( 
 "model" 
 ), 
 "osVersion" 
 : 
 osinfo 
 . 
 get 
 ( 
 "version" 
 ) 
 or 
 general 
 . 
 get 
 ( 
 "osVersion" 
 ), 
 "osBuild" 
 : 
 osinfo 
 . 
 get 
 ( 
 "build" 
 ) 
 or 
 general 
 . 
 get 
 ( 
 "osBuild" 
 ), 
 "macAddress" 
 : 
 hardware 
 . 
 get 
 ( 
 "macAddress" 
 ), 
 "alternateMacAddress" 
 : 
 hardware 
 . 
 get 
 ( 
 "wifiMacAddress" 
 ), 
 "ipAddress" 
 : 
 general 
 . 
 get 
 ( 
 "ipAddress" 
 ), 
 "reportedIpV4Address" 
 : 
 general 
 . 
 get 
 ( 
 "reportedIpV4Address" 
 ), 
 "reportedIpV6Address" 
 : 
 general 
 . 
 get 
 ( 
 "reportedIpV6Address" 
 ), 
 "modelIdentifier" 
 : 
 hardware 
 . 
 get 
 ( 
 "modelIdentifier" 
 ), 
 "assetTag" 
 : 
 general 
 . 
 get 
 ( 
 "assetTag" 
 ), 
 } 
 user_block 
 = 
 { 
 "userDirectoryID" 
 : 
 loc 
 . 
 get 
 ( 
 "username" 
 ) 
 or 
 loc 
 . 
 get 
 ( 
 "userDirectoryId" 
 ), 
 "emailAddress" 
 : 
 loc 
 . 
 get 
 ( 
 "emailAddress" 
 ), 
 "realName" 
 : 
 loc 
 . 
 get 
 ( 
 "realName" 
 ), 
 "phone" 
 : 
 loc 
 . 
 get 
 ( 
 "phone" 
 ) 
 or 
 loc 
 . 
 get 
 ( 
 "phoneNumber" 
 ), 
 "position" 
 : 
 loc 
 . 
 get 
 ( 
 "position" 
 ), 
 "department" 
 : 
 loc 
 . 
 get 
 ( 
 "department" 
 ), 
 "building" 
 : 
 loc 
 . 
 get 
 ( 
 "building" 
 ), 
 "room" 
 : 
 loc 
 . 
 get 
 ( 
 "room" 
 ), 
 } 
 return 
 { 
 "webhook" 
 : 
 { 
 "name" 
 : 
 "api.inventory" 
 }, 
 "event_type" 
 : 
 "ComputerInventory" 
 , 
 "event_action" 
 : 
 "snapshot" 
 , 
 "event_timestamp" 
 : 
 _now_iso 
 (), 
 "event_data" 
 : 
 { 
 "computer" 
 : 
 { 
 k 
 : 
 v 
 for 
 k 
 , 
 v 
 in 
 computer 
 . 
 items 
 () 
 if 
 v 
 not 
 in 
 ( 
 None 
 , 
 "" 
 )}, 
 ** 
 { 
 k 
 : 
 v 
 for 
 k 
 , 
 v 
 in 
 user_block 
 . 
 items 
 () 
 if 
 v 
 not 
 in 
 ( 
 None 
 , 
 "" 
 )} 
 }, 
 "_jamf" 
 : 
 { 
 "id" 
 : 
 item 
 . 
 get 
 ( 
 "id" 
 ), 
 "inventory" 
 : 
 inv 
 } 
 } 
 def 
  
 write_ndjson_gz 
 ( 
 objs 
 , 
 when 
 ): 
 buf 
 = 
 io 
 . 
 BytesIO 
 () 
 with 
 gzip 
 . 
 GzipFile 
 ( 
 filename 
 = 
 "-" 
 , 
 mode 
 = 
 "wb" 
 , 
 fileobj 
 = 
 buf 
 , 
 mtime 
 = 
 int 
 ( 
 time 
 . 
 time 
 ())) 
 as 
 gz 
 : 
 for 
 obj 
 in 
 objs 
 : 
 line 
 = 
 json 
 . 
 dumps 
 ( 
 obj 
 , 
 separators 
 = 
 ( 
 "," 
 , 
 ":" 
 )) 
 + 
 " 
 \n 
 " 
 gz 
 . 
 write 
 ( 
 line 
 . 
 encode 
 ( 
 "utf-8" 
 )) 
 buf 
 . 
 seek 
 ( 
 0 
 ) 
 prefix 
 = 
 GCS_PREFIX 
 . 
 strip 
 ( 
 "/" 
 ) 
 + 
 "/" 
 if 
 GCS_PREFIX 
 else 
 "" 
 key 
 = 
 f 
 " 
 { 
 prefix 
 }{ 
 when 
 : 
 %Y/%m/%d 
 } 
 /jamf_pro_context_ 
 { 
 int 
 ( 
 when 
 . 
 timestamp 
 ()) 
 } 
 .ndjson.gz" 
 bucket 
 = 
 storage_client 
 . 
  bucket 
 
 ( 
 GCS_BUCKET 
 ) 
 blob 
 = 
 bucket 
 . 
 blob 
 ( 
 key 
 ) 
 blob 
 . 
  upload_from_file 
 
 ( 
 buf 
 , 
 content_type 
 = 
 "application/gzip" 
 ) 
 return 
 key 
 @functions_framework 
 . 
 cloud_event 
 def 
  
 main 
 ( 
 cloud_event 
 ): 
  
 """ 
 Cloud Run function triggered by Pub/Sub to fetch Jamf Pro context logs and write to GCS. 
 Args: 
 cloud_event: CloudEvent object containing Pub/Sub message 
 """ 
 if 
 not 
 all 
 ([ 
 BASE_URL 
 , 
 CLIENT_ID 
 , 
 CLIENT_SECRET 
 , 
 GCS_BUCKET 
 ]): 
 print 
 ( 
 "Error: Missing required environment variables" 
 ) 
 return 
 try 
 : 
 token 
 , 
 _ttl 
 = 
 get_token 
 () 
 page 
 = 
 0 
 total 
 = 
 0 
 batch 
 = 
 [] 
 now 
 = 
 datetime 
 . 
 now 
 ( 
 timezone 
 . 
 utc 
 ) 
 while 
 True 
 : 
 payload 
 = 
 fetch_page 
 ( 
 token 
 , 
 page 
 ) 
 results 
 = 
 payload 
 . 
 get 
 ( 
 "results" 
 ) 
 or 
 [] 
 if 
 not 
 results 
 : 
 break 
 for 
 item 
 in 
 results 
 : 
 batch 
 . 
 append 
 ( 
 to_context_event 
 ( 
 item 
 )) 
 total 
 += 
 1 
 if 
 len 
 ( 
 batch 
 ) 
> = 
 5000 
 : 
 key 
 = 
 write_ndjson_gz 
 ( 
 batch 
 , 
 now 
 ) 
 print 
 ( 
 f 
 "Wrote 
 { 
 len 
 ( 
 batch 
 ) 
 } 
 records to gs:// 
 { 
 GCS_BUCKET 
 } 
 / 
 { 
 key 
 } 
 " 
 ) 
 batch 
 = 
 [] 
 if 
 len 
 ( 
 results 
 ) 
< PAGE_SIZE 
 : 
 break 
 page 
 += 
 1 
 if 
 batch 
 : 
 key 
 = 
 write_ndjson_gz 
 ( 
 batch 
 , 
 now 
 ) 
 print 
 ( 
 f 
 "Wrote 
 { 
 len 
 ( 
 batch 
 ) 
 } 
 records to gs:// 
 { 
 GCS_BUCKET 
 } 
 / 
 { 
 key 
 } 
 " 
 ) 
 print 
 ( 
 f 
 "Successfully processed 
 { 
 total 
 } 
 total records" 
 ) 
 except 
 Exception 
 as 
 e 
 : 
 print 
 ( 
 f 
 "Error processing Jamf Pro context logs: 
 { 
 str 
 ( 
 e 
 ) 
 } 
 " 
 ) 
 raise
      • 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 jamfpro-context-schedule-1h
      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 ( jamf-pro-context-trigger )
      Message body {} (empty JSON object)

    4. Click Create.

    Test the scheduler job

    1. In the Cloud Schedulerconsole, find your job.
    2. Click Force runto trigger manually.
    3. Wait a few seconds and go to Cloud Run > Services > jamf-pro-context-collector > Logs.
    4. Verify the function executed successfully.
    5. Check the GCS bucket to confirm logs were written.

    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, Jamf Pro Context logs ).
    5. Select Google Cloud Storage V2as the Source type.
    6. Select Jamf pro contextas 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.
    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 Jamf Pro context 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, Jamf Pro Context logs ).
    5. Select Google Cloud Storage V2as the Source type.
    6. Select Jamf pro contextas 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://jamfpro/jamf-pro/context/
        • Replace jamfpro with the actual name of the bucket.

      • 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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