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Release: Australia · Updated: 2026-03-12 · Official documentation · View source

Download Oracle Global License Advisory Services (GLAS) data

Download Oracle GLAS data in CSV format to get detailed information on patterns and configuration items. You can also download reports for Oracle Database, Middleware, Oracle Java, VM, and vCenter hardware information.

Before you begin

Role required: admin or glas_admin

About this task

ServiceNow maintains regular verification with Oracle GLAS to provide you with insights on licensing data for your Oracle estate. The following Oracle GLAS reporting versions are currently verified:

  • Database: 25.2
  • Middleware: 23.2
  • Java: 24.4

Procedure

  1. Navigate to All > Oracle GLAS Data Collection > Download GLAS Data Collection.
Image omitted: oracle-glas-download.png
Oracle GLAS download page
  1. Download the following reports for Oracle GLAS data:

    • For downloading Oracle Database, Middleware, and Java reports, navigate to Step 1: Download GLAS Data Collection and select your data collection options.
    • For downloading vCenter hardware information based on your environment setup, navigate to Step 2: Download vCenter Hardware Information.
    • For downloading VM information, navigate to Step 3: Download VM Information.
    • Select the download icon (
Image omitted: download-icon.png
Download icon\).
  1. In the Enter email address dialog box, enter the email address where you want to receive a notification when the report is ready.

  2. Select OK.

    After the report creation status message appears, you can check the status of the download job by selecting the link provided in the message.

Image omitted: report-creation-msg.png
Message for report creation status
The Oracle GLAS Report Job Log \[sn\_itom\_oracleglas\_job\_log\] table opens in a new window. After your report is successfully created, the status of the report changes to Complete in the Oracle GLAS Report Job Logs table.
  1. Select a job log record to view its details including the unique number, name, status, description, and the date and time when the job log is created and updated.

  2. On the Oracle GLAS Report Job Log form that opens, download your report by navigating to Manage Attachments and selecting download.

    • Depending on your selection in Step 1: Download GLAS Data Collection, the following folders are downloaded:

      • Oracle Database
        • DB folder – contains the following CSV files:
          • ORCL_V$SESSION.csv
          • ORCL_OPTIONS.csv
          • ORCL_DBA_USERS.csv
          • ORCL_DETAIL.csv
          • ORCL_V$LICENSE.csv
          • ORCL_OVERVIEW.csv
        • CPUQ folder – contains CPUQ files, vCenter Hardware, and VM information
      • Oracle Middleware

        The following files are exported, where the file name reflects your server name and Oracle product:

        • ORCL_OVERVIEW.csv
        • Collection-<Server Name>_<Oracle Product>.tar.bz with the files and directories of the format FMW/u01/app/oracle/config/domains/soa_domain/config/config.xml in it - Oracle Java
        • Java folder – contains Java installation information

          Note: The report that you download for Oracle Java GLAS includes only Java deployments from the Oracle publisher. Java deployments from non‑Oracle publishers are excluded from the report.

        • CPUQ folder – contains CPUQ files, vCenter Hardware, and VM information

          • If you selected Step 2: Download vCenter Hardware Information, one hardware inventory CSV file is downloaded per vCenter in your environment.
          • If you selected Step 3: Download VM Information, one VM information CSV file is downloaded per vCenter in your environment. Note: For V1, you can also download the CSV files for Oracle Database by navigating to Oracle GLAS Data Collection > Oracle GLAS Data. From the list that opens, select the table that you want to download and then select Download GLAS Report.

Result

The downloaded files appear in the location that you select.

If the files are empty or contain an error message, check their sizes to verify that they haven't exceeded the limits set in the following properties. Navigate to All > System Properties > All Properties to find the following properties.

Important: Consult with ServiceNow support before changing these properties.

PropertyDescription
glide.discovery.file_tracking.max_file_sizeThe maximum file size for tracked configuration file content. Type: integer Default value: 500000
glide.discovery.file_tracking.max_files_per_ciThe maximum number of tracked configuration files per CI. Type: integer Default value: 50
glide.discovery.file_tracking.change_limit_countNumber of changes permitted on a tracked configuration file in the defined time window. Type: integer Default value: 4
glide.discovery.file_tracking.change_limit_daysTime window \(in days\) that limits the number of changes on a tracked configuration file. Type: integer Default value: 7

If you receive an error Error: Skipped sensor for Horizontal Pattern because of error in payload: Payload length 5056040 exceeded the limit of 300000, verify that the payload hasn't exceeded the system limit. Navigate to All > MID Server > Properties to find the following properties.

PropertyDescription
mid.discovery.max_payload_sizeDefines the maximum overall payload size for the payload of results that come from patterns. Type: integer \(bytes\) Default value: 300000

If you receive an SSH timeout error, you must create and set the following properties. See "Create a MID Server property" in MID Server Properties for details.

PropertyDescription
mid.ssh.command_timeout_msNumber of milliseconds an SSH command is permitted to run before timing out \(default is configurable per MID Server\). Type: integer
mid.sa.ssh.timeoutThe SSH timeout in milliseconds. Type: integer
channel_timeout_msThe amount of time, in milliseconds, that a MID Server waits for activity when processing an SSH command. If the MID Server doesn’t detect activity within the specified window, the system terminates the command. Type: integer

Parent Topic:Oracle GLAS data collection using patterns